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This study maps how cognitive and behavioral concepts such as trust, emotion, and bias are represented in the literature on digital financial accounting-based decision-making and FinTech adoption (artificial intelligence, blockchain, big data analytics, and automated reporting). The study employs a bibliometric mapping analysis of 19,655 publications from SCOPUS, creating three visualizations through the VOSviewer software: Network, Overlay, and Density Visualization. This technique maps thematic clusters and identifies conceptual connections in the literature on cognitive and behavioral dimensions of FinTech adoption. Results highlight trust as a central node linking FinTech adoption with cognitive and behavioral factors. Key cognitive biases, including overconfidence, anchoring, and loss aversion, appear in the literature as recurrent concepts associated with FinTech adoption, while financial literacy is frequently discussed as a mitigating factor. The study extends behavioral financial accounting-based theory and technology acceptance models by integrating psychological and technological approaches into a unified conceptual framework, providing theoretical and practical implications for FinTech designers, regulatory authorities, and educational institutions.
Lampropoulos et al. (Mon,) studied this question.