Unravelling the Landscape of Mental Accounting Research Using Machine Learning: A Topic Modelling Approach

The heightened global recognition of mental accounting in the realm of behavioural finance research has attracted the attention of academics, scholars, industry professionals, financial institutions, and decision-makers. This study utilizes bibliometric analysis and structural topic modelling to investigate a dataset of 388 articles from Elsevier’s Scopus database over the past two decades (2002-2022), with a specific focus on the field of mental accounting. It analyses publication trends, influential countries, and notable journals. The United States leads with 102 articles, mainly single-country publications (85 SCPs and 17 MCPs), resulting in an MCP Ratio of 0.167. The "Journal of Economic Psychology" emerges as a prominent source, contributing 18 articles (4.6% of the total articles). Structural topic modelling results reveal five thematic clusters: Financial decision-making and investment biases; Consumer behaviour in purchases, spending, and payments; Consumption patterns and economic decisions; Accounting, taxation, and pricing effects; and Perceived value of mental accounting. The future research agenda for mental accounting research encompasses interdisciplinary approaches, innovative methodologies, and a strong focus on practical applications aimed at enhancing financial decision-making and overall financial well-being. These findings enhance understanding of key topics and keywords in mental accounting. These findings carry substantial significance for a diverse audience, including scholars, financial institutions, and professionals.