Understanding Students’ Behavioral Intention Toward AI-Enabled Smart Cafeteria Services: Extending UTAUT with Self-Efficacy and Technology Anxiety
Yingduo Wu, Wen-Hwa Ko, Ching-Sung LeeDespite growing interest in AI-enabled hospitality services, technology acceptance in institutional foodservice remains underexamined. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates students’ behavioral intentions toward AI-enabled university cafeteria services and examines self-efficacy and technology anxiety as moderators. Survey data from 640 Chinese university students reveal positive associations of performance expectancy, effort expectancy, and social influence with behavioral intention, but no significant independent association for facilitating conditions. A positive effort expectancy × self-efficacy interaction emerged in the full model, although its adjusted statistical significance was sensitive to influential observations. None of the technology-anxiety interactions remained statistically significant after adjustment. Although the incremental explanatory contribution of the interactions was small, the findings provide tentative evidence of selective moderation and extend UTAUT research to routine institutional foodservice.