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Stream/Area:
-
Subject:
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Paper ID:
IJSREM68376
Volume:
10 |
10 |
Oct 2026
Pages:
1-30
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
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Research on consumer risk in investment decision making has expanded rapidly as individuals and households have taken on greater responsibility for their own financial futures, from retirement savings to cryptocurrency and app-based investing. This study is a bibliometric review to trace the development of the field, identify the intellectual structure and emerging directions in this field. All documents were retrieved from Scopus using the following terms: consumer, investment and risk; the number of documents retrieved were 1656, published by 1009 sources, and filtered by time span (2008–2027), document type, language and source type. Data were analysed in R by using the packages Bibliometrix and Biblioshiny. The number of documents produced each year increased from 27 documents in 2008 to 214 in 2025, representing approximately 36% of the data for the last 3 years. With USA in first place, followed by China, U.K., India and Australia, and a wide distribution of sources including energy and sustainability journals, it’s clear that the field is interdisciplinary. Thematic analysis shows a shift from risk tolerance, financial literacy and investor sentiment towards consumer protection, uncertainty and resilience, and more recently FinTech, artificial intelligence, ESG and sustainable development. The review identifies fragmentation across behavioural, portfolio, technology and regulatory streams and sets out an agenda for future research.
KEYWORDS
Overall, future studies on consumer risk in investment decisions should consider and integrate the following elements: (1) linking the consumer’s behaviour to financial risk; (2) focusing on the emerging role of technology; (3) making cross-national and cross-demographic comparisons; and (4) gaining insight into the temporal dimension of risk perception. The conclusions of the present investigation give a starting point of these investigations. The broader datasets, more clear research timeframes, more suitable empirical methods and more interdisciplinary research can be used by future researchers to build upon and fill gaps in the existing knowledge. These strategies can contribute to the understanding of the investment risks and enhance the dissemination of these risks to academia and to financial institutions, policy makers or consumers.
Aftab, R., Fazal, A., & Andleeb, R. (2025). Behavioral biases and Fintech adoption: Investigating the role of financial literacy. Acta Psychologica, 257, Article 105065. https://doi.org/10.1016/j.actpsy.2025.105065 Agarwal, S., Amromin, G., Ben-David, I., Chomsisengphet, S., & Evanoff, D. D. (2015). Financial literacy and financial planning: Evidence from India. Journal of Housing Economics, 27, 4–21. https://doi.org/10.1016/j.jhe.2015.02.003 Agnew, S., & Dargusch, P. (2017). Consumer preferences for household-level battery energy storage. Renewable and Sustainable Energy Reviews, 75, 609–617. https://doi.org/10.1016/j.rser.2016.11.030 Ahad, M., Imran, Z. A., & Shahzad, K. (2024). Safe haven between European ESG and energy sector under Russian-Ukraine war: Role of sustainable investments for portfolio diversification. Energy Economics, 138, Article 107853. https://doi.org/10.1016/j.eneco.2024.107853 Assaf, A., Charif, H., & Mokni, K. (2021). Dynamic connectedness between uncertainty and energy markets: Do investor sentiments matter? Resources Policy, 72, Article 102112. https://doi.org/10.1016/j.resourpol.2021.102112 Atwal, G., & Bryson, D. (2021). Antecedents of intention to adopt artificial intelligence services by consumers in personal financial investing. Strategic Change, 30(3), 293–298. https://doi.org/10.1002/jsc.2412 Baker, T., & Dellaert, B. (2018). Regulating robo advice across the financial services industry. Iowa Law Review, 103(2), 713–750. Balaskas, S. (2026). Trust as predictor and mechanism in green FinTech adoption: A systematic review and meta-analysis. FinTech, 5(1). https://doi.org/10.3390/fintech5010022 Chen, Y., Kirshner, S. N., Ovchinnikov, A., Andiappan, M., & Jenkin, T. (2025). A Manager and an AI Walk into a Bar: Does ChatGPT Make Biased Decisions Like We Do? Manufacturing and Service Operations Management, 27(2), 354–368. https://doi.org/10.1287/msom.2023.0279
Publication Date
10/27/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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