Antecedents and Consequences of AI Misuse Among University Students: An Empirical Investigation

AI misuse has become a significant challenge and concern in higher education. Existing research has focused separately on either antecedents or consequences of AI misuse and has relied on a single theoretical perspective. There is a notable lack of empirical research investigating the antecedents and consequences of AI misuse among university students. To address this gap, this study constructs an integrated research model for the antecedents and consequences of AI misuse based on the fraud triangle theory, deterrence theory, and social cognitive theory. Data were collected from 493 university students through a questionnaire survey and analyzed using structural equation modeling (SEM) to test the proposed hypotheses. The results indicate that ease of use, academic pressure, and peer influence significantly promote AI misuse. Policy deterrence and academic self-efficacy can effectively inhibit AI misuse. Furthermore, AI misuse impairs students’ innovation ability. This study advances the systematic understanding of AI misuse and consolidates its theoretical and empirical underpinnings. It enables universities to better govern AI misuse and foster students’ innovation ability.