Acta Informatica Pragensia - Forthcoming articles

Blockchain Applications and Governance Implications in the Public Sector: A Literature Review

Linda Nuryanti, Fara Ayuningtyas, Monica Dwi Wahyu Sumunaringrum, Wenwen Ruswendi, Agoeng Srimoeljanto, Agus Sutejo, Triyono Susanto, Ratna Nurmayni

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.315613  

Background: Blockchain is increasingly recognized as a transformative enabler of e-governance, offering capabilities to enhance transparency, efficiency, security, and citizen trust in public-sector administration. However, widespread adoption remains constrained by persistent technical, regulatory, and socio-institutional challenges, particularly the absence of coherent governance frameworks across jurisdictions.Objective: This study aims to systematically map the evolution of blockchain applications in e-governance, identify dominant research themes and collaboration patterns, and highlight governance-related challenges that inform future policy...

Transformative Impact of Generative AI Tools on Information Creativity and AI Literacy in Higher Education: Case Studies

Jela Steinerová

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.316152  

Background: Generative artificial intelligence (GenAI) tools can have a transformative impact on information creativity.Objective: The objectives of this study are to explore the use of GenAI by doctoral and master students as part of information creativity, AI literacy and transformation of higher education. We ask the question: What is the impact of GenAI tools on information creativity?Methods: Studies of information creativity, AI literacy, and creative writing of university students were analysed. We report on two qualitative case studies, including 17 doctoral students (a focus group, essays), and a qualitative experiment with 8 master students...

Acceptability of Telemedicine Among Nurses Caring for Older Adults: A Quantitative Descriptive Study

Simona Hvalič-Touzery, Nejc Berzelak, Mojca Šetinc, Vesna Dolničar, Angela Kydd, Jerneja Laznik

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.319361  

Background: Telemedicine, though decades old, saw only limited use until the COVID-19 pandemic, but despite increasing adoption, barriers to using telemedicine remain pervasive.Objective: We sought to explore the acceptability of telemedicine among nurses caring for older adults by extending the Technology Acceptance Model (TAM).Methods: A descriptive, non-experimental, quantitative research design was used. An online survey was administered to Slovenian registered nurses experienced in caring for older adults (n = 244), of whom 111 with no prior telemedicine experience were included in the analysis. Data were collected between September and December...

Enterprise Conversational AI with Retrieval-Augmented Generation: A CRM Case Study

Martin Sasinka, Martin Kotyrba, Eva Volna, Martin Pavlicek

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.320174  

Background: The integration of Large Language Models (LLMs) into enterprise information systems represents a major challenge in Artificial Intelligence (AI) and digital transformation. Retrieval-Augmented Generation (RAG) has emerged as a promising approach to improve knowledge management and reduce information overload in enterprise environments.Objective: This study aimed to design, implement, and evaluate a conversational assistant that combines RAG with fine-tuned LLMs in a Customer Relationship Management (CRM) environment. The research further sought to identify an optimal balance between performance, operational efficiency, and data governance.Methods:...

Enhancing Fraud Detection Performance on Imbalanced Datasets: A ResNet-Based Approach Integrating Multi-Attention Techniques and SMOTE-ENN

Mohammed Khaldoon Altalib, Karam Abdullah, Naomie Salim

Acta Informatica Pragensia X:X | DOI: 10.18267/j.aip.3278  

Background: The detection of financial fraud has become increasingly significant because electronic transactions and advanced frauds have been growing rapidly, leading to huge losses for the economy. Yet, significant class imbalance, data heterogeneity, evolving fraud trends, and a small number of labelled samples remain as challenges for building effective fraud detection systems.Objective: This article assesses an integrated approach to a fraud-detection framework based on residual networks (ResNet), different attention mechanisms, and class-imbalance handling techniques across heterogeneous financial datasets.Methods: The proposed experimental framework...