Digital Technologies and Behavioral Dimensions in Financial Research: A Bibliometric Mapping of the Past Decade

Abstract

The convergence of digital technologies and behavioral research has become a defining feature of contemporary financial innovation, bringing together advances in artificial intelligence, machine learning and blockchain with evolving work on decision-making, risk perception and investor behavior. Yet the literature at this convergence remains fragmented, with few studies offering an integrated view of its intellectual structure. This paper responds to that gap through a bibliometric analysis of 4975 articles retrieved from the Web of Science Core Collection between 2015 and 2024, combining Bibliometrix R and VOSviewer for performance analysis and science mapping. The findings show a marked acceleration of research output following the Covid-19 pandemic, with China, the United States and India emerging as the leading contributors, and with technologically oriented journals such as IEEE Access, Scientific Reports and Sensors serving as the core publication outlets. Keyword co-occurrence yields five coherent thematic clusters that span the technological backbone of digital finance (machine learning, deep learning, blockchain, Internet of Things) and its behavioral dimensions (risk management, uncertainty, investor response to external shocks), with notable hotspots emerging around explainable and trustworthy artificial intelligence. By offering a large-scale mapping of this broader technological and behavioral landscape, the study provides scholars, practitioners and policymakers with a structured overview of how FinTech and behavioral research intersect and where future inquiry may concentrate.