Toward an Integrated View of Investor Behavior: A Bibliometric Study on Financial Literacy and Psychological Biases
DOI:
https://doi.org/10.33830/jfba.v5i1.12690.2025Keywords:
Investor behavior, Financial literacy, Behavorial biases, Gen Z, Cryptocurrency, Digital finance, Decision-makingAbstract
This study investigates the intersection between financial literacy and behavioral biases in investment decision-making, addressing the limited theoretical and empirical integration between the two domains. Adopting a quantitative bibliometric design, data were collected from 1,000 peer-reviewed journal articles indexed in CrossRef (2014–2025) using Publish or Perish, with purposive sampling based on metadata relevance. The dataset was analyzed using VOSviewer, which produced three core visualizations—network, overlay, and density—to map the intellectual structure, thematic development, and research intensity. The findings reveal four major clusters: financial literacy, behavioral biases, digital innovation, and empirical approaches. Financial literacy emerges as the cognitive foundation of investor behavior, while biases such as overconfidence and herding impede rational decision-making—especially in digital contexts and among younger generations. The study concludes that a cross-domain approach is essential for comprehensively understanding contemporary investment behavior. It recommends integrating technology-driven financial education with behavioral awareness to inform more inclusive and adaptive policy and market interventions.
References
Aftab, R., Fazal, A., & Andleeb, R. (2025). Behavioral biases and Fintech adoption: Investigating the role of financial literacy. Acta Psychologica, 257. https://doi.org/10.1016/j.actpsy.2025.105065
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/https://doi.org/10.1016/0749-5978(91)90020-T
Altaf, H., & Jan, A. (2023). Generational theory of behavioral biases in investment behavior. Borsa Istanbul Review, 23(4), 834–844. https://doi.org/10.1016/j.bir.2023.02.002
Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
Barber, B. M., Odean, T., Guercio, D., Hirshleifer, D., Karolyi, A., Loughran, T., … Viceira, L. (2001). BOYS WILL BE BOYS: GENDER, OVERCONFIDENCE, AND COMMON STOCK INVESTMENT. The Quarterly Journal of Economics. https://doi.org/https://doi.org/10.1162/003355301556400
Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades. Journal of Political Economy, 100(5), 992–1026. https://doi.org/10.1086/261849
Chen, R., Lepori, G. M., Tai, C. C., & Sung, M. C. (2022). Can salience theory explain investor behaviour? Real-world evidence from the cryptocurrency market. International Review of Financial Analysis, 84. https://doi.org/10.1016/j.irfa.2022.102419
Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. https://doi.org/10.1002/asi.21525
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
Hasanah, E. N., Koesrindartoto, D. P., Wiryono, S. K., & Angelica, A. E. (2025). Who deserves to be the finfluencer? Journal of Open Innovation: Technology, Market, and Complexity, 11(2). https://doi.org/10.1016/j.joitmc.2025.100553
Kahneman, D., & Tversky’, A. (1979). PROSPECT THEORY: AN ANALYSIS OF DECISION UNDER RISK. Source: Econometrica, 47(2), 263–292. https://doi.org/https://doi.org/10.2307/1914185
Kumari, V., Bala, P. K., & Chakraborty, S. (2023). An Empirical Study of User Adoption of Cryptocurrency Using Blockchain Technology: Analysing Role of Success Factors like Technology Awareness and Financial Literacy. Journal of Theoretical and Applied Electronic Commerce Research, 18(3), 1580–1600. https://doi.org/10.3390/jtaer18030080
Li, S., He, F., & Shi, F. (2023). Cognitive biases, downside risk shocks, and stock expected returns. North American Journal of Economics and Finance, 68. https://doi.org/10.1016/j.najef.2023.101981
Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5–44. https://doi.org/10.1257/jel.52.1.5
Lusardi, A., Mitchell, O. S., & Curto, V. (2010). Financial Literacy among the Young. The Journal of Consumer Affairs, 44(2), 358–380. https://doi.org/https://doi.org/10.1111/j.1745-6606.2010.01173.x
Mahmood, F., Arshad, R., Khan, S., Afzal, A., & Bashir, M. (2024). Impact of behavioral biases on investment decisions and the moderation effect of financial literacy; an evidence of Pakistan. Acta Psychologica, 247. https://doi.org/10.1016/j.actpsy.2024.104303
Massaro, M., Dumay, J., & Guthrie, J. (2016). On the shoulders of giants: undertaking a structured literature review in accounting. Accounting, Auditing and Accountability Journal, 29(5), 767–801. https://doi.org/10.1108/AAAJ-01-2015-1939
Merigó, J. M., & Yang, J. B. (2017). A bibliometric analysis of operations research and management science. Omega (United Kingdom), 73, 37–48. https://doi.org/10.1016/j.omega.2016.12.004
Shefrin, H. M., & Thaler, R. H. (1988). THE BEHAVIORAL LIFE-CYCLE HYPOTHESIS. Economic Inquiry, 26(4), 609–643. https://doi.org/https://doi.org/10.1111/j.1465-7295.1988.tb01520.x
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
Van Rooij, M., Lusardi, A., & Alessie, R. (2011). Financial literacy and stock market participation. Journal of Financial Economics, 101(2), 449–472. https://doi.org/10.1016/j.jfineco.2011.03.006
Wang, Y. S., Duong, N. T., Ying, C. H., & Chang, Y. C. (2024). What Drives People’s Cryptocurrency Investment Behavior. Journal of Computer Information Systems. https://doi.org/10.1080/08874417.2024.2329127
Zupic, I., & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629
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