The role of AI in financial analysis on investment intentions among economics students: Mediating effect of analytical self-efficacy

Abstract

This research deals with the influence of artificial intelligence (AI) technologies in financial analysis on the investment decision intention, highlighting the mediating role of analytical self-efficacy. Drawing upon the theory of planned behavior (TPB), the technology acceptance model (TAM), and self-efficacy theory, a conceptual framework was developed and put to test based on information gathered from 300 economics students chosen through a process of stratified random sampling. A structured questionnaire captured dimensions of AI usage, analytical self-efficacy, and investment intention, and the data were analyzed using structural equation modeling (SEM) and the Bootstrap method. Results indicated that AI usage has a significant and positive influence on both analytical self-efficacy and investment decision intention. Further, analytical self-efficacy was a partial mediator of the relationship between AI usage and investment intention. The research adds to the body of knowledge by fusing behavioral intention models with AI adoption within higher educational settings and suggesting workable solutions for curriculum construction and technology-oriented training to enhance the readiness of students to invest.