Document Type

Article

Publication Date

10-2026

Abstract

The current study explores how AI robo-advisors (AIRA) platforms retain stock market investors over time. It examines how system reliability (REL), seamless system user interface navigation (SIN), application informativeness (INF), and perceived conversational quality (CON) affect investor retention (RET) in an emerging capital market through perceived source credibility (SCR). This empirical study included survey data from 413 Egyptian financial and investing community retail stock investors. For this study, SEM using AMOS 26 assessed direct structural routes, model fit, and indirect mediation effects after confirmatory factor analysis confirmed construct validity and reliability. Variance accounted for (VAF) calculations measuring mediation strength across all quality characteristics. According to structural route calculations, only SIN directly impacts investor retention (β=0.261, p< 0.001). REL, INF, and CON appear to have no significant effects on RET. Concerning the mediating role of SCR, it is the main factor affecting RET (β=0.686, p< 0.001), accounting for an average of 76.36% of the overall quality effect. The research findings confirmed the mediating role of SCR. It is partially mediating the effect between SIN and RET (VAF = 50.85%), whereas it has a full mediating effect on REL, INF, and CON. Based on these findings and the predictions of the overall AIRA quality dimensions, platform management should prioritise transparent decision logic, explainable stock recommendations, and validated dependability. The article's originality is highlighted by tackling the post-adoption retention gap in developing market FinTech studies, moving away from monolithic trust ideas and initial adoption goals. Cognitive SCR is the main path via which technological and informational characteristics lead to platform loyalty.

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