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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66847
Volume:
10 |
8 |
Aug 2026
Pages:
1-7
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.

School of Commerce
Devi Ahilya Viswavidyalaya, Indore, (M.P.)

Department of Management & Commerce
ISBA Group of Institutes, Indore, (M.P.)
The research seeks to explore and determine emerging micro-emotional, psychological, and situational triggers and drivers that influence and shape the investment behaviour of young Gen Z investors in the current scenario, beyond existing traditional behavioural biases. in which research adopted a quantitative research design, using a structured questionnaire with a 5-point Likert scale to collect primary data from Gen Z (Age group between 13 and 29 years) investors in the Bhopal region of the Indian subcontinent. The authors used Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) in JAMOVI Software, and SmartPLS 4 for PLS-SEM (Partial Least Squares Structural Equation Modelling) for measurement and structural model assessment. The studies found some novel and micro emerging drivers beyond traditional biases, i.e. socially driven impulsive investment and financially informed and seeking financial growth factors among Gen Z investors, which contribute significantly to influencing their investment behaviour and decisions. The findings of this study contribute to the existing body of knowledge in the field of behavioural finance by adding new micro dimensions that play a significant role, along with traditional biases in behavioural investing in the Indian context.
KEYWORDS
The present study was aimed at exploring the effect of Financial Growth Engagement Factor (FGEF) and Socially Driven Impulsive Investment (SDII) on Investment Decision Behaviour (IDB) of Gen Z investors through EFA, CFA and PLS-SEM methodologies. The empirical results showed that the measurement model showed sufficient internal consistency, convergent validity, and discriminant validity. The factor analytical results proved to be able to determine three significant factors with good factor loadings and cumulative variance. Furthermore, the results of the analysis of the model showed that Financial Growth Engagement Factor (FGEF) and Socially Driven Impulsive Investment (SDII) had both a positive and significant effect on Investment Decision Behaviour of Gen Z investors. The two predictors showed a relatively stronger effect on investment decision behaviour, with FGEF showing a stronger effect, suggesting that investors who are financially growth-oriented and actively engaged in investing are more likely to play an effective role in investment activities. The effect of SDII was comparatively small but statistically significant, indicating that social influence, peer behaviour and impulsive tendencies also play a part in the investment decision-making process of Gen Z investors. The model also exhibited good explanatory and predictive capability with R², Q² predict, RMSE and MAE values, indicating that the proposed framework is suitable and has good prediction power in behavioural finance research. In conclusion, the results provide further evidence to the body of research on emerging behavioural and emotional factors influencing investment behaviour, specifically for Gen Z investors. This research builds on the already rich body of Behavioural Finance literature and extends the scope of knowledge of investment behaviour beyond the scope of traditional behavioural biases. The study identifies new emotional and situational variables that are now impacting the investment choices of Gen Z investors. The study also adds to the scarce literature available on the Indian context, especially young investors in Tier-II cities, such as Bhopal. From a methodological perspective, the application of EFA, CFA and PLS-SEM offers a holistic approach to study the modern constructs of behaviour in the investment decision-making process and can be used as a guideline for further research in behavioural finance.
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Publication Date
8/20/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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