Acta Informatica Pragensia 2023, 12(2), 468-489 | DOI: 10.18267/j.aip.2227735

Consumer Behaviour and Acceptance in Fintech Adoption: A Systematic Literature Review

Muhardi Saputra ORCID...1,2, Paulus Insap Santosa ORCID...1, Adhistya Erna Permanasari ORCID...1
1 Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Indonesia
2 Department Information System, Telkom University, Indonesia

The literature review was conducted systematically, following a rigorous process to address specific research questions. The review procedure was designed to provide guidance and minimize researcher bias. It outlined the study selection process, including inclusion and exclusion criteria, research questions, search methods, quality evaluation, and data extraction and synthesis. The Scopus database was utilized for this systematic literature review, and a comprehensive search was conducted to identify relevant studies. We used the Kitchenham systematic literature review (SLR) method required to process metadata at the time of processing this SLR, and PRISMA guidelines for reporting systematic literature reviews and meta-analyses. Additionally, VOSviewer analysis was employed to gather data on the sources used by individuals and organizations to access information about fintech products and services, and to understand their influence on acceptance behaviour. A total of 850 publications were identified and screened, with 70 fintech customer acceptance studies meeting the inclusion and exclusion criteria. These studies were published between 2012 and 2022 and were limited to Scopus indexed journals. To maintain focus, specific research questions (RQ) were developed, and data were gathered accordingly to address each RQ while adhering to quality standards. Reviews and quality checklists were used to extract relevant data, prioritizing the most comprehensive publication when multiple sources reported the same data. The primary studies analysed indicated that research into fintech acceptability spans various scientific disciplines, including computer science, information technology, business management and marketing. The technology acceptance model (TAM) emerged as the most used approach for measuring user acceptance of fintech services, as identified in 43 out of 70 publications. Furthermore, several researchers have incorporated additional factors such as performance, social influence, cultural and religious values, knowledge, and service quality to enhance the understanding of fintech acceptance.

Keywords: Fintech; Customer behaviour; Fintech adoption; Literature review; Scopus.

Received: May 14, 2023; Revised: July 27, 2023; Accepted: August 27, 2023; Prepublished online: September 11, 2023; Published: October 10, 2023  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Saputra, M., Santosa, P.I., & Permanasari, A.E. (2023). Consumer Behaviour and Acceptance in Fintech Adoption: A Systematic Literature Review. Acta Informatica Pragensia12(2), 468-489. doi: 10.18267/j.aip.222
Download citation

References

  1. Abu Daqar, M. A. M., Arqawi, S., & Karsh, S. A. (2020). Fintech in the eyes of Millennials and Generation Z (the financial behavior and Fintech perception). Banks and Bank Systems, 15(3), 20-28. https://doi.org/10.21511/bbs.15(3).2020.03 Go to original source...
  2. Adjei, J. K., Odei-Appiah, S., & Tobbin, P. E. (2020). Explaining the determinants of continual use of mobile financial services. Digital Policy, Regulation and Governance, 22(1), 15-31. https://doi.org/10.1108/DPRG-09-2019-0074 Go to original source...
  3. Agyei, J., Sun, S., Penney, E. K., Abrokwah, E., Boadi, E. K., & Fiifi, D. D. (2022). Internet Banking Services User Adoption in Ghana: An Empirical Study. Journal of African Business, 23(3), 599-616. https://doi.org/10.1080/15228916.2021.1904756 Go to original source...
  4. Akhtar, S., Irfan, M., Sarwar, A., Asma, & Rashid, Q. U. A. (2019). Factors influencing individuals' intention to adopt mobile banking in China and Pakistan: The moderating role of cultural values. Journal of Public Affairs, 19(1), 1-15. https://doi.org/10.1002/pa.1884 Go to original source...
  5. Akinwale, Y. O., & Kyari, A. K. (2022). Factors influencing attitudes and intention to adopt financial technology services among the end-users in Lagos State, Nigeria. African Journal of Science, Technology, Innovation and Development, 14(1), 272-279. https://doi.org/10.1080/20421338.2020.1835177 Go to original source...
  6. Akturan, U., & Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence and Planning, 30(4), 444-459. https://doi.org/10.1108/02634501211231928 Go to original source...
  7. Alam, A., Ratnasari, R. T., Mua'awanah, C., & Hamidah, R. A. (2022). Generation Z perceptions in paying Zakat, Infaq, and Sadaqah using Fintech: A comparative study of Indonesia and Malaysia. Investment Management and Financial Innovations, 19(2), 320-330. https://doi.org/10.21511/imfi.19(2).2022.28 Go to original source...
  8. Albayati, H., Kim, S. K., & Rho, J. J. (2020). Accepting financial transactions using blockchain technology and cryptocurrency: A customer perspective approach. Technology in Society, 62(December 2019), 101320. https://doi.org/10.1016/j.techsoc.2020.101320 Go to original source...
  9. Almuzaini, K. K., Sinhal, A. K., Ranjan, R., Goel, V., Shrivastava, R., & Halifa, A. (2022). Key Aggregation Cryptosystem and Double Encryption Method for Cloud-Based Intelligent Machine Learning Techniques-Based Health Monitoring Systems. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/3767912 Go to original source...
  10. Almuzaini, K. K., Sinhal, A., Ranjan, R., Goel, V., Shrivastava, R., & Halifa, A. (2022). Key Aggregation cryptosystem and double encryption method for Cloud-Based Intelligent Machine Learning Techniques-Based health monitoring systems. Computational Intelligence and Neuroscience, 2022, Article ID 3767912. https://doi.org/10.1155/2022/3767912 Go to original source...
  11. Baber, H. (2021). Examining the intentions to use crowdfunding platform - An extended technology acceptance model. International Journal of Services, Economics and Management, 12(2), 149-163. https://doi.org/10.1504/IJSEM.2021.117226 Go to original source...
  12. Balakrishnan, V., & Shuib, N. L. M. (2021). Drivers and inhibitors for digital payment adoption using the Cashless Society Readiness-Adoption model in Malaysia. Technology in Society, 65, 101554. https://doi.org/10.1016/j.techsoc.2021.101554 Go to original source...
  13. Bao, H., & Roubaud, D. (2022). Non-Fungible Token: A Systematic Review and Research Agenda. Journal of Risk and Financial Management, 15(5), 215. https://doi.org/10.3390/jrfm15050215 Go to original source...
  14. Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418-430. https://doi.org/10.1016/j.chb.2015.04.024 Go to original source...
  15. Bartlett, R., Morse, A., Stanton, R., & Wallace, N. (2022). Consumer-lending discrimination in the FinTech Era. Journal of Financial Economics, 143(1), 30-56. https://doi.org/10.1016/j.jfineco.2021.05.047 Go to original source...
  16. Bazarbash, M., & Beaton, K. (2020). Filling the Gap: Digital Credit and Financial Inclusion. Working Paper No. 2020/150. https://www.imf.org/en/Publications/WP/Issues/2020/08/07/Filling-the-Gap-Digital-Credit-and-Financial-Inclusion-49638 Go to original source...
  17. Biucky, S. T., Abdolvand, N., & Harandi, S. R. (2017). The effects of perceived risk on social commerce adoption based on the tam model. International Journal of Electronic Commerce Studies, 8(2), 173-196. https://doi.org/10.7903/ijecs.1538 Go to original source...
  18. Candra, S., Nuruttarwiyah, F., & Hapsari, I. H. (2020). Revisited the Technology Acceptance Model with E-Trust for Peer-to-Peer Lending in Indonesia (Perspective from Fintech Users). International Journal of Technology, 11(4), 710-721. https://doi.org/10.14716/ijtech.v11i4.4032 Go to original source...
  19. Çera, G., Khan, K. A., & Solenièki, M. (2021). Linking Individual Demographics to Antecedents of Mobile Banking Usage: Evidence from Developing Countries in Southeast Europe. Global Business Review, (in press). https://doi.org/10.1177/09721509211008686 Go to original source...
  20. Chan, R. (2022). Towards an understanding of consumers' FinTech adoption: the case of Open Banking. International Journal of Bank Marketing, 40(4), 886-917. https://doi.org/10.1108/IJBM-08-2021-0397 Go to original source...
  21. Chan, R., Troshani, I., Rao Hill, S., & Hoffmann, A. (2022). Towards an understanding of consumers' FinTech adoption: the case of Open Banking. International Journal of Bank Marketing, 40(4), 886-917. https://doi.org/10.1108/IJBM-08-2021-0397 Go to original source...
  22. Chawla, D., & Joshi, H. (2019). Consumer attitude and intention to adopt mobile wallet in India - An empirical study. International Journal of Bank Marketing, 37(7), 1590-1618. https://doi.org/10.1108/IJBM-09-2018-0256 Go to original source...
  23. Chen, T. H., & Chang, R. C. (2021). Using machine learning to evaluate the influence of FinTech patents: The case of Taiwan's financial industry. Journal of Computational and Applied Mathematics, 390, 113215. https://doi.org/10.1016/j.cam.2020.113215 Go to original source...
  24. Chen, Y., Siddik, A. B., Akter, N., & Dong, Q. (2021). Factors influencing the adoption intention of using mobile financial service during the COVID-19 pandemic: the role of FinTech. Environmental Science and Pollution Research, 30(22), 61271-61289. https://doi.org/10.1007/s11356-021-17437-y Go to original source...
  25. Chiou, J. S., & Shen, C. C. (2012). The antecedents of online financial service adoption: The impact of physical banking services on Internet banking acceptance. Behaviour and Information Technology, 31(9), 859-871. https://doi.org/10.1080/0144929X.2010.549509 Go to original source...
  26. Cornelli, G., Frost, J., Gambacorta, L., Rau, R., Wardrop, R., & Ziegler, T. (2020). Fintech and big tech credit: a new database. https://www.bis.org/publ/work887.htm
  27. Daragmeh, A., Lentner, C., & Sági, J. (2021). FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of "Generation X" in Hungary to use mobile payment. Journal of Behavioral and Experimental Finance, 32, 100574. https://doi.org/10.1016/j.jbef.2021.100574 Go to original source...
  28. Darmansyah, Fianto, B. A., Hendratmi, A., & Aziz, P. F. (2020). Factors determining behavioral intentions to use Islamic financial technology: Three competing models. Journal of Islamic Marketing, 12(4), 794-812. https://doi.org/10.1108/JIMA-12-2019-0252 Go to original source...
  29. Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. MIT, Ph.D. thesis (January 1985). https://dspace.mit.edu/handle/1721.1/15192
  30. Dawood, H. M., Liew, C. Y., & Lau, T. (2022). Mobile perceived trust mediation on the intention and adoption of FinTech innovations using mobile technology: A systematic literature review. F1000Research, 10, 1252. https://doi.org/10.12688/f1000research.74656.2 Go to original source...
  31. Deb, M., & Agrawal, A. (2017). Factors impacting the adoption of m-banking: understanding brand India's potential for financial inclusion. Journal of Asia Business Studies, 11(1), 22-40. https://doi.org/10.1108/JABS-11-2015-0191 Go to original source...
  32. Djimesah, I. E., Zhao, H., Okine, A. N. D., Li, Y., Duah, E., & Kissi Mireku, K. (2022). Analyzing the technology of acceptance model of Ghanaian crowdfunding stakeholders. Technological Forecasting and Social Change, 175(2006), 121323. https://doi.org/10.1016/j.techfore.2021.121323 Go to original source...
  33. Folkinshteyn, D., & Lennon, M. (2016). Braving Bitcoin: A technology acceptance model (TAM) analysis. Journal of Information Technology Case and Application Research, 18(4), 220-249. https://doi.org/10.1080/15228053.2016.1275242 Go to original source...
  34. Frederiks, A., Costa, S. F., Hulst, B., & Groen, A. J. (2022). The early bird catches the worm: The role of regulatory uncertainty in early adoption of blockchain's cryptocurrency by fintech ventures. Journal of Small Business Management, (in press), 1-34. https://doi.org/10.1080/00472778.2022.2089355 Go to original source...
  35. Fu, J., & Mishra, M. (2022). Fintech in the time of COVID-19: Technological adoption during crises. Journal of Financial Intermediation, 50(740272). https://doi.org/10.1016/j.jfi.2021.100945 Go to original source...
  36. Giovanis, A. N., Binioris, S., & Polychronopoulos, G. (2012). An extension of TAM model with IDT and security/privacy risk in the adoption of internet banking services in Greece. EuroMed Journal of Business, 7(1), 24-53. https://doi.org/10.1108/14502191211225365 Go to original source...
  37. Haider, M. J., Gao, C., Akram, T., & Hussain, S. T. (2018). Does gender differences play any role in intention to adopt Islamic mobile banking in Pakistan? Journal of Islamic Marketing, 9(2), 439-460. https://doi.org/10.1108/jima-11-2016-0082 Go to original source...
  38. Hasan, R., Ashfaq, M., & Shao, L. (2021). Evaluating drivers of fintech adoption in the Netherlands. Global Business Review, (in press). https://doi.org/10.1177/09721509211027402 Go to original source...
  39. Hiew, L. C., Lee Hung, A., Leong, C. M., Liew, C. Y., & Soe, M. H. (2022). Do They Really Intend to Adopt E-Wallet? Prevalence Estimates for Government Support and Perceived Susceptibility. Asian Journal of Business Research, 12(1), 77-98. https://doi.org/10.14707/ajbr.220121 Go to original source...
  40. Ho, J. C., Wu, C. G., Lee, C. S., & Pham, T. T. T. (2020). Factors affecting the behavioral intention to adopt mobile banking: An international comparison. Technology in Society, 63, 101360. https://doi.org/10.1016/j.techsoc.2020.101360 Go to original source...
  41. Hodula, M. (2022). Does Fintech credit substitute for traditional credit? Evidence from 78 countries. Finance Research Letters, 46, 102469. https://doi.org/10.1016/j.frl.2021.102469 Go to original source...
  42. Hodula, M. (2023). Interest rates as a finance battleground? The rise of Fintech and big tech credit providers and bank interest margin. Finance Research Letters, 53, 103685. https://doi.org/10.1016/j.frl.2023.103685 Go to original source...
  43. Huang, S. Y. B., Lee, C. J., & Lee, S. C. (2021). Toward a unified theory of customer continuance model for financial technology chatbots. Sensors, 21(17), 5687. https://doi.org/10.3390/s21175687 Go to original source...
  44. Jain, K., & Chowdhary, R. (2021). A Study on Intention to Adopt Digital Payment Systems in India: Impact of COVID-19 Pandemic. Asia Pacific Journal of Information Systems, 31(1), 76-101. https://doi.org/10.14329/apjis.2021.31.1.76 Go to original source...
  45. Jamshidi, D., & Hussin, N. (2016). Forecasting patronage factors of Islamic credit card as a new e-commerce banking service. Journal of Islamic Marketing, 7(4), 378-404. https://doi.org/10.1108/jima-07-2014-0050 Go to original source...
  46. Julianto, I. P., Pasek, N. S., & Wiguna, I. Gd. N. H. (2021). Technology Acceptance Model Approach to Analysing the Use of Fintech in MSME Transactions in Buleleng. In Proceedings of the 6th International Conference on Tourism, Economics, Accounting, Management, and Social Science (pp. 5-11). Atlantis Press. https://doi.org/10.2991/aebmr.k.211124.002 Go to original source...
  47. Jünger, M., & Mietzner, M. (2020). Banking goes digital: The adoption of FinTech services by German households. Finance Research Letters, 34, 101260. https://doi.org/10.1016/j.frl.2019.08.008 Go to original source...
  48. Kala Kamdjoug, J. R., Wamba-Taguimdje, S. L., Wamba, S. F., & Kake, I. B. e. (2021). Determining factors and impacts of the intention to adopt mobile banking app in Cameroon: Case of SARA by afriland First Bank. Journal of Retailing and Consumer Services, 61, 102509. https://doi.org/10.1016/j.jretconser.2021.102509 Go to original source...
  49. Kathiravan, C., Rajasekar, A., Velmurgan, S., Mahalakshmi, P., Chandramouli, E., Suresh, V., Padmaja, B., & Dhanalakshmi, K. (2021). Sentiment Analysis and Text Mining of Online Customer Reviews for Digital Wallet Apps Of Fintech Industry. International Journal of Aquatic Science, 12(3), 2139-2150.
  50. Kesharwani, A., & Bisht, S. S. (2012). The impact of trust and perceived risk on internet banking adoption in India: An extension of technology acceptance model. International Journal of Bank Marketing, 30(4), 303-322. https://doi.org/10.1108/02652321211236923 Go to original source...
  51. Khan, I. U., Hameed, Z., & Khan, S. U. (2017). Understanding online banking adoption in a developing country: UTAUT2 with cultural moderators. Journal of Global Information Management, 25(1), 43-65. https://doi.org/10.4018/JGIM.2017010103 Go to original source...
  52. Kitchenham, B., & Charters, S. M. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. EBSE Technical Report EBSE-2007-01. Software Engineering Group, School of Computer Science and Mathematics, Keele University.
  53. Kotarba, M. (2016). New factors inducing changes in the retail banking customer relationship management (CRM) and their exploration by the FinTech industry. Foundations of Management, 8(1), 69-78. https://doi.org/10.1515/fman-2016-0006 Go to original source...
  54. Ku-Mahamud, K. R., Omar, M., Abu Bakar, N. A., & Muraina, I. D. (2019). Awareness, trust, and adoption of blockchain technology and cryptocurrency among blockchain communities in Malaysia. International Journal on Advanced Science, Engineering and Information Technology, 9(4), 1217-1222. https://doi.org/10.18517/ijaseit.9.4.6280 Go to original source...
  55. Kuo Chuen, D. L. (2017). Fintech Tsunami: Blockchain as the Driver of the Fourth Industrial Revolution. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2998093 Go to original source...
  56. Lee, J. M., Lee, B., & Rha, J. Y. (2019). Determinants of mobile payment usage and the moderating effect of gender: Extending the UTAUT model with privacy risk. International Journal of Electronic Commerce Studies, 10(1), 43-64. https://doi.org/10.7903/ijecs.1644 Go to original source...
  57. Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C. D., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Journal of Clinical Epidemiology, 62(10), e1-e34. https://doi.org/10.1016/j.jclinepi.2009.06.006 Go to original source...
  58. Lim, S. H., Kim, D. J., Hur, Y., & Park, K. (2019). An Empirical Study of the Impacts of Perceived Security and Knowledge on Continuous Intention to Use Mobile Fintech Payment Services. International Journal of Human-Computer Interaction, 35(10), 886-898. https://doi.org/10.1080/10447318.2018.1507132 Go to original source...
  59. Lubis, M., Saputra, M., & Nurtrisha, W. A. (2021). Financial technology development framework for prosperity of the nation and potential direction. In ICCCM '21: Proceedings of the 9th International Conference on Computer and Communications Management, (pp. 212-218). ACM. https://doi.org/10.1145/3479162.3479194 Go to original source...
  60. Majumdar, S., & Pujari, V. (2022). Exploring usage of mobile banking apps in the UAE: a categorical regression analysis. Journal of Financial Services Marketing, 27(3), 177-189. https://doi.org/10.1057/s41264-021-00112-1 Go to original source...
  61. Matemba, E. D., Li, G., & Maiseli, B. J. (2018). Consumers' stickiness to mobile payment applications: An empirical study of wechat wallet. Journal of Database Management, 29(3), 43-66. https://doi.org/10.4018/JDM.2018070103 Go to original source...
  62. Mengist, W., Soromessa, T., & Legese, G. (2020). Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX, 7, 100777. https://doi.org/10.1016/J.MEX.2019.100777 Go to original source...
  63. Moorthy, K., Chun T'ing, L., Chea Yee, K., Wen Huey, A., Joe In, L., Chyi Feng, P., & Jia Yi, T. (2020). What drives the adoption of mobile payment? A Malaysian perspective. International Journal of Finance and Economics, 25(3), 349-364. https://doi.org/10.1002/ijfe.1756 Go to original source...
  64. Munikrishnan, U. T., Mamun, A. al, Xin, N. K. S., Chian, H. S., & Naznen, F. (2022). Modelling the intention and adoption of cashless payment methods among the young adults in Malaysia. Journal of Science and Technology Policy Management, (in press). https://doi.org/10.1108/JSTPM-04-2022-0077 Go to original source...
  65. Muñoz-Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinantes de la intención de uso de las aplicaciones de banca para móviles: una extensión del modelo TAM clásico. Spanish Journal of Marketing - ESIC, 21(1), 25-38. https://doi.org/10.1016/j.sjme.2016.12.001 Go to original source...
  66. Najib, M., & Fahma, F. (2020). Investigating the adoption of digital payment system through an extended technology acceptance model: An insight from the Indonesian small and medium enterprises. International Journal on Advanced Science, Engineering and Information Technology, 10(4), 1702-1708. https://doi.org/10.18517/ijaseit.10.4.11616 Go to original source...
  67. Namahoot, K. S., & Jantasri, V. (2022). Integration of UTAUT model in Thailand cashless payment system adoption: the mediating role of perceived risk and trust. Journal of Science and Technology Policy Management, 14(4), 634-658. https://doi.org/10.1108/JSTPM-07-2020-0102 Go to original source...
  68. Nanggala, A. Y. A. (2020). Use of fintech for payment: Approach to technology acceptance model modified. Journal of Contemporary Information Technology, Management, and Accounting, 1(1), 1-8.
  69. Nasri, W., & Charfeddine, L. (2012). Factors affecting the adoption of Internet banking in Tunisia: An integration theory of acceptance model and theory of planned behavior. Journal of High Technology Management Research, 23(1), 1-14. https://doi.org/10.1016/j.hitech.2012.03.001 Go to original source...
  70. Nayak Kini, A., & Basri, S. (2022). An empirical examination of customer advocacy influenced by engagement behaviour and predispositions of FinTech customers in India. F1000Research, 11, 27. https://doi.org/10.12688/f1000research.74928.2 Go to original source...
  71. Okello Candiya Bongomin, G., & Ntayi, J. (2020). Trust: mediator between mobile money adoption and usage and financial inclusion. Social Responsibility Journal, 16(8), 1215-1237. https://doi.org/10.1108/SRJ-01-2019-0011 Go to original source...
  72. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. The BMJ, 372, n71. https://doi.org/10.1136/bmj.n71 Go to original source...
  73. Philippas, N. D., & Avdoulas, C. (2020). Financial literacy and financial well-being among generation-Z university students: Evidence from Greece. European Journal of Finance, 26(4-5), 360-381. https://doi.org/10.1080/1351847X.2019.1701512 Go to original source...
  74. Rafiq, M., & Boccia, S. (2018). Application of the GRADE approach in the development of guidelines and recommendations in genomic medicine. Genomics Insights, 11, 117863101775336. https://doi.org/10.1177/1178631017753360 Go to original source...
  75. Rahim, N. F., Bakri, M. H., Fianto, B. A., Zainal, N., & Shami, S. (2022). Measurement and structural modelling on factors of Islamic Fintech adoption among millennials in Malaysia. Journal of Islamic Marketing, 14(6), 1463-1487. https://doi.org/10.1108/jima-09-2020-0279 Go to original source...
  76. Reith, R., Fischer, M., & Lis, B. (2019). Explaining the intention to use social trading platforms: an empirical investigation. Journal of Business Economics, 90(3), 427-460. https://doi.org/10.1007/s11573-019-00961-2 Go to original source...
  77. Rodiana, R. (2020). Analysis of investment interests, motivation, social environment, financial literacy (comparative study of generation z and millennial generation). International Journal of Business, Economics and Law, 22(1), 111-121.
  78. Rosariana, B. (2021). Generasi "Milenial" Dan Generasi "Kolonial". https://www.djkn.kemenkeu.go.id/kpknl-pontianak/baca-artikel/14262/Generasi-Milenial-Dan-Generasi-Kolonial.html
  79. Safarudin, A., Kusdibyo, L., & Senalasari, W. (2020). Faktor-Faktor Pembentuk Loyalitas Generasi Z dalam Menggunakan Financial Technology E-wallet. Prosiding Industrial Research Workshop and National Seminar, 11(1), 1073-1078. https://doi.org/10.35313/irwns.v11i1.2166 Go to original source...
  80. Saputra, M., & Supangkat, S. H. (2018). Financial technology business model as branchless banking for people in rural areas: Case study: Indonesia. In 2017 International Conference on ICT for Smart Society, (pp. 1-6). IEEE. https://doi.org/10.1109/ICTSS.2017.8288890 Go to original source...
  81. Sembiring, M. J., Wibowo, W., & Dewi, G. C. (2022). Adoption of innovative mobile payment technologies in Indonesia: The role of attitude. Innovative Marketing, 18(2), 186-197. https://doi.org/10.21511/im.18(2).2022.16 Go to original source...
  82. Shaikh, I. M., Qureshi, M. A., Noordin, K., Shaikh, J. M., Khan, A., & Shahbaz, M. S. (2020). Acceptance of Islamic financial technology (FinTech) banking services by Malaysian users: an extension of technology acceptance model. Foresight, 22(3), 367-383. https://doi.org/10.1108/FS-12-2019-0105 Go to original source...
  83. Sharif, S. P., & Naghavi, N. (2021). Online Financial Trading among Young Adults: Integrating the Theory of Planned Behavior, Technology Acceptance Model, and Theory of Flow. International Journal of Human-Computer Interaction, 37(10), 949-962. https://doi.org/10.1080/10447318.2020.1861761 Go to original source...
  84. Singh, A. K., & Sharma, P. (2022). A study of Indian Gen X and Millennials consumers' intention to use FinTech payment services during COVID-19 pandemic. Journal of Modelling in Management, 18(4), 1177-1203. https://doi.org/10.1108/jm2-02-2022-0059 Go to original source...
  85. Singh, S. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675-1697. https://doi.org/10.1108/MD-09-2019-1318 Go to original source...
  86. Singh, S., Sahni, M. M., & Kovid, R. K. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675-1697. https://doi.org/10.1108/MD-09-2019-1318 Go to original source...
  87. Singh, S., Sahni, M. M., & Kovid, R. K. (2021). Exploring trust and responsiveness as antecedents for intention to use FinTech services. International Journal of Economics and Business Research, 21(2), 254-268. https://doi.org/10.1504/IJEBR.2021.113152 Go to original source...
  88. Singh, S., & Srivastava, R. K. (2020). Understanding the intention to use mobile banking by existing online banking customers: an empirical study. Journal of Financial Services Marketing, 25(3-4), 86-96. https://doi.org/10.1057/s41264-020-00074-w Go to original source...
  89. Solarz, M., & Swacha-Lech, M. (2021). Determinants of the adoption of innovative fintech services by millennials. E a M: Ekonomie a Management, 24(3), 149-166. https://doi.org/10.15240/TUL/001/2021-3-009 Go to original source...
  90. Song, F., & Thakor, A. V. (2010). Financial system architecture and the co-evolution of banks and capital markets. Economic Journal, 120(547), 1021-1055. https://doi.org/10.1111/j.1468-0297.2009.02345.x Go to original source...
  91. Sukwadi, R., Caroline, L. S., & Chen, G. Y. H. (2022). Extended technology acceptance model for Indonesian mobile wallet: Structural equation modeling approach. Engineering and Applied Science Research, 49(2), 146-154. https://doi.org/10.14456/easr.2022.17 Go to original source...
  92. Takeda, A., & Ito, Y. (2021). A review of FinTech research. International Journal of Technology Management, 86(1), 67-88. https://doi.org/10.1504/IJTM.2021.115761 Go to original source...
  93. Tang, H. (2019). Peer-to-Peer lenders versus banks: Substitutes or complements? Review of Financial Studies, 32(5), 1900-1938. https://doi.org/10.1093/rfs/hhy137 Go to original source...
  94. Thakur, R., & Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369-392. https://doi.org/10.1108/IntR-12-2012-0244 Go to original source...
  95. Tomiæ, N., Kaliniæ, Z., & Todoroviæ, V. (2022). Using the UTAUT model to analyze user intention to accept electronic payment systems in Serbia. Portuguese Economic Journal, 22(2), 251-270. https://doi.org/10.1007/s10258-022-00210-5 Go to original source...
  96. Utami, A. F., Ekaputra, I. A., & Japutra, A. (2021). Adoption of FinTech Products: A Systematic Literature Review. Journal of Creative Communications, 16(3), 233-248. https://doi.org/10.1177/09732586211032092 Go to original source...
  97. Wahono, R. (2016). Systematic Literature Review. https://romisatriawahono.net/publications/2016/wahono-slr-may2016.pdf
  98. Wamba, S. F., Queiroz, M. M., Blome, C., & Sivarajah, U. (2021). Fostering Financial Inclusion in a Developing Country: Predicting User Acceptance of Mobile Wallets in Cameroon. Journal of Global Information Management, 29(4), 195-220. https://doi.org/10.4018/JGIM.20210701.oa9 Go to original source...
  99. Wang, Z., Guan, Z., Hou, F., Li, B., & Zhou, W. (2019). What determines customers' continuance intention of FinTech? Evidence from YuEbao. Industrial Management and Data Systems, 119(8), 1625-1637. https://doi.org/10.1108/IMDS-01-2019-0011 Go to original source...
  100. Warjiyono, Aji, S., Fandhilah, Hidayatun, N., Faqih, H., & Liesnaningsih. (2019). The Sentiment Analysis of Fintech Users Using Support Vector Machine and Particle Swarm Optimization Method. In 2019 7th International Conference on Cyber and IT Service Management, CITSM 2019. IEEE. https://doi.org/10.1109/CITSM47753.2019.8965348 Go to original source...
  101. Winarno, W. A., & Putra, H. S. (2020). Technology acceptance model of the Indonesian government financial reporting information systems. International Journal of Public Sector Performance Management, 6(1), 68-84. https://doi.org/10.1504/IJPSPM.2020.105089 Go to original source...
  102. Yen, Y. S., & Wu, F. S. (2016). Predicting the adoption of mobile financial services: The impacts of perceived mobility and personal habit. Computers in Human Behavior, 65, 31-42. https://doi.org/10.1016/j.chb.2016.08.017 Go to original source...

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.