Mapping the use of heuristics in auditors’ judgment and decision making: A bibliometric analysis
DOI:
https://doi.org/10.11606/issn.1982-6486.rco.2026.243137Keywords:
Auditor judgement, Heuristics, Cognitive bias, Decision making, BibliometricAbstract
This study aims to map the static intellectual structure and identify key thematic concentrations in the literature on heuristics and cognitive biases in auditor judgment. By mapping the static intellectual structure of the field, this paper highlights dominant research themes, uncovers theoretical gaps, and provides insights into how psychological mechanisms influence audit quality and decision-making under uncertainty. A bibliometric approach was employed, based on 497 journal articles retrieved from the Web of Science database. Two science mapping techniques, co-citation analysis and co-word analysis, were conducted to investigate the foundational knowledge base and identify key thematic concentrations in behavioral auditing. The co-citation analysis revealed four core research streams: cognitive biases in decision-making, heuristics and cognitive mechanisms in audit judgment, motivated reasoning and conflicts of interest, and framing effects under risk. The co-word analysis further identified four thematic clusters reflecting current hotspots: cognitive bias modification, heuristic use under uncertainty, attentional control, and systematic audit governance frameworks. The study is limited to the Web of Science database and focuses primarily on external auditing. However, it has meaningful implications for researchers, practitioners, and regulators seeking to enhance audit quality by identifying literature-based priorities for audit training, supervision, and governance across traditional and remote audits. This review facilitates a clearer theoretical integration of behavioral and cognitive psychology perspectives within auditing research. Furthermore, it maps the crucial transition from traditional analog mental shortcuts to new technology-driven heuristics within modern digital audit environments.
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