EMOTIONAL INTELLIGENCE AS A PREDICTOR OF INVESTMENT CHOICES: THE MEDIATING BRIDGE OF ARTIFICIAL INTELLIGENCE
DOI:
https://doi.org/10.59415/mjacs.330Keywords:
Emotional intelligence, Investment Decision, Artificial Intelligence, Behavioural Finance, PLS SEMAbstract
The rapid integration of Artificial Intelligence (AI) in financial markets has significantly transformed investment decision-making processes, shifting them from intuition-driven judgments to data-driven and algorithm-supported strategies. Alongside technological advancements, Emotional Intelligence (EI) remains a crucial human factor influencing investors’ perceptions, risk assessment, and behavioural responses. This study examines the relationship between Emotional Intelligence, Trust in Artificial Intelligence, and Investment Decision-making, with a particular focus on the mediating role of trust in AI. Using a quantitative research design, primary data were collected from 100 retail investors through a structured questionnaire. Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to test the proposed hypotheses and assess both the measurement and structural models. The findings reveal that Emotional Intelligence has a significant positive influence on investment decisions, while trust in AI also plays a crucial role in enhancing decision quality. Moreover, trust in AI partially mediates the relationship between EI awareness and investment decisions, indicating that emotionally intelligent investors are more likely to rely on AI tools when trust is established. The study contributes to the growing literature at the intersection of behavioural finance and financial technology by highlighting the importance of integrating human emotional capabilities with AI-driven systems. The results offer practical insights for investors, financial institutions, and policymakers seeking to promote effective and responsible adoption of AI in investment decision-making.
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References
Ahmad, M. (2018). Impact of neurotransmitters, emotional intelligence and personality on investor's behaviour and investment decisions.
Ammer, M. A., Ahmed, Z. A., Alsubari, S. N., Aldhyani, T. H., & Almaaytah, S. A. (2023). Application of artificial intelligence for better investment in human capital.
Chen, C., Ishfaq, M., Ashraf, F., Sarfaraz, A., & Wang, K. (2022). Mediating role of optimism bias and risk perception between emotional intelligence and decision-making: a serial mediation mode
Chua, A. Y. K., Pal, A., & Banerjee, S. (2023). AI-enabled investment advice: Will users buy it? Computers in Human Behavior, 138. https://doi.org/10.1016/j.chb.2022.107481
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis Eighth Edition. Www.Cengage.Com/Highered
Meyer, J. H., Friederich, F., Matute, J., & Schwarz, M. (2024). My money—My problem: How fear‐of‐missing‐out appeals can hinder sustainable investment decisions.
Rehman, M., Dhiman, D. B., & Cheema, G. S. (2024). Minds and Machines: Impact of Emotional Intelligence on Investment Decisions with Mediating the Role of Artificial Intelligence.
Rehman, M., Dhiman, Dr. B., & Cheema, G. S. (2024). Minds and Machines: Impact of Emotional Intelligence on Investment Decisions with Mediating the Role of Artificial Intelligence. International Journal of Engineering, Business and Management, 8(1). https://doi.org/10.22161/ijebm.8.1.1
Verma, B., Schulze, M., Goswami, D., & Upreti, K. (2025). Artificial intelligence attitudes and resistance to use robo-advisors: exploring investor reluctance toward cognitive financial systems.
Vijayakumar Bharathi, S., Pramod, D., & Raman, R. (2022). Intention to use Artificial Intelligence services in Financial Investment Decisions. 2022 International Conference on Decision Aid Sciences and Applications, DASA 2022. https://doi.org/10.1109/DASA54658.2022.9765183
Watson, D. (2019). The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence. Minds and Machines, 29(3). https://doi.org/10.1007/s11023-019-09506-6
Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety. Educational and Psychological Measurement, 73(6). https://doi.org/10.1177/0013164413495237
Wu, I. L., & Chen, J. L. (2005). An extension of Trust and TAM model with TPB in the initial adoption of on-line tax: An empirical study. International Journal of Human Computer Studies, 62(6). https://doi.org/10.1016/j.ijhcs.2005.03.003
Yang, M., & Rau, P. L. P. (2024). Trust building with artificial intelligence: comparing with human in investment behaviour, emotional arousal and neuro activities. Theoretical Issues in Ergonomics Science, 25(5). https://doi.org/10.1080/1463922X.2023.2290019
Zhang, Y., & Zheng, X. (2015). A Study of The Investment Behaviour Based On Behavioral Finance. European Journal of Business and Economics, 10(1). https://doi.org/10.12955/ejbe.v10i1.557
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Copyright (c) 2026 Sneha S, Varshini V Varshini, Lena Mathews
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