Explaining Behavioral Intention to Use AI in Tourism: Competence Satisfaction, Autonomy Support, and AI Hallucination Concerns

While traditional technology acceptance models are insufficient for modern, agentic AI systems, this study explains Behavioral Intention to use AI in tourism by proposing a new model grounded in Self-Determination Theory (SDT). We posit that Competence Satisfaction and Autonomy Support are the primary drivers of adoption. The model also incorporates AI Hallucination Concerns as a key moderator. It was tested using structural equation modeling (SEM) on survey data from 900 consumers. Results provide strong support for the model, with competence satisfaction emerging as the strongest predictor, followed by autonomy support. A user's prior experience was fully mediated by these psychological needs. Critically, a significant and unexpected positive interaction revealed that as hallucination concerns increase, the positive effect of competence on intention becomes stronger, suggesting a "compensatory confidence" mechanism. This study advances IS adoption theory by integrating SDT to provide a more nuanced explanation for AI acceptance and contributes a novel mechanism to explain user adoption of imperfect technologies. Our findings offer actionable guidance for practitioners on designing and managing AI systems to support user needs and calibrate trust.