Digital Risk Amplification in App-Based Equity Investing: Trading Apps, Finfluencers, Gamified Interface Features, and Retail Investor Risk-Taking Behaviour in Rajasthan, India

Abstract

The proliferation of mobile trading applications, social-media investment communities, and algorithmically curated financial content has fundamentally reconfigured the decision environment of retail equity investors in India. This study investigates how trading-app influence, social-media and finfluencer exposure, gamified interface features, algorithmic vulnerability, digital misinformation risk, perceived risk, and expected return perception jointly shape the risk-taking behaviour of retail equity investors in Rajasthan. Using primary survey data collected from five Rajasthan cities (Jaipur, Jodhpur, Kota, Ajmer, and Udaipur) and applying rigorous four-stage inclusion screening, a final analytical sample of N = 520 verified retail equity investors was obtained. The study employs reliability analysis, descriptive statistics, Pearson correlation analysis, chi-square tests, one-way ANOVA, multiple regression with heteroskedasticity-consistent standard errors, bootstrap-based mediation analysis, and exploratory factor analysis. A novel theoretical framework, the Digital Behavioural Risk Amplification Model (D-BRAM), integrating Prospect Theory, Social Influence Theory, Attention Theory, Technology Acceptance with Vulnerability Extension, and Gamification Theory, is proposed. Results demonstrate that the revised Risk-Taking Behaviour Index (RTBI-5), constructed from five behavioural indicators excluding expected return perception, maintains strong construct coherence. Expected return perception is the strongest positive predictor of RTBI-5 (B = 0.178, p < .001). Trading-app influence is a significant positive predictor of perceived risk (B = 0.726, p < .001) but exhibits a negative association with RTBI-5 after controls (B = -0.098, p = .004), consistent with a risk-awareness inhibition mechanism. Bootstrap mediation analysis (5,000 resamples) confirms that social-media influence operates on risk-taking behaviour indirectly through expected return perception (indirect effect = 0.069, 95% CI [0.038, 0.107]). Significant demographic differences in risk-taking behaviour are identified by educational qualification (F = 6.488, p < .001, η2 = .048) and household income (F = 8.748, p < .001, η2 = .048). The findings advance a layered understanding of digital risk amplification, with implications for SEBI regulation, platform design, and digital financial literacy programmes..