Behavioral finance has emerged as an important research domain that challenges traditional financial theories by emphasizing the role of psychological factors, cognitive biases, and human behavior in financial decision-making. This study aims to map the intellectual structure, research development, influential contributions, and future research directions of behavioral finance literature using a bibliometric analysis approach. Data were collected from the Scopus database using relevant keywords related to behavioral finance and analyzed through VOSviewer to examine publication trends, citation performance, author collaboration networks, country collaboration patterns, and keyword co-occurrence structures. The findings indicate that behavioral finance research has experienced significant growth and has been primarily shaped by influential studies focusing on behavioral biases, investor psychology, financial literacy, and market anomalies. The citation analysis identifies Barberis and Thaler (2003), Shiller (2003), Hirshleifer (2015), and Ritter (2003) as among the most influential contributions in establishing the theoretical foundation of the field. The collaboration analysis demonstrates that the United States, China, and India play central roles in global research networks, while keyword analysis reveals the dominance of themes related to behavioral finance, investments, financial decision-making, and risk perception. Furthermore, emerging research trends indicate a growing integration between behavioral finance and digital transformation, including artificial intelligence, big data, cryptocurrency, electronic trading, and sustainable finance. This study contributes to the literature by providing a comprehensive overview of the evolution of behavioral finance and identifying potential future research directions toward technology-driven and interdisciplinary financial behavior studies.
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