AI Hallucinations in Tourism: How Errors Impact Consumer Trust and Recommendation Acceptance

ABSTRACT Generative artificial intelligence (GenAI) is quickly transforming travel planning; however, its outputs can include hallucinations, which are plausible yet false statements that can undermine user judgement. Eliminating hallucinations in GenAI technology is currently impossible. This research analyses, through two experiments, how hallucinations in itineraries generated by ChatGPT influence consumer behaviour. Study 1 ( n = 1004) explores a serial‐mediation pathway where the presence of hallucinations affects the intention to follow the itinerary through perceived accuracy, perceived usefulness and trustworthiness. Hallucinations significantly reduced perceived accuracy. As accuracy increased, usefulness improved, leading to greater trustworthiness, which strongly predicted intention. Although the direct effect of hallucinations on intention was not significant, the serial indirect effect was negative and significant. Study 2 ( n = 241) investigates how the outcome's positive or negative value and the importance of error feedback influence the results. The findings indicate that the valence of outcomes moderates the relationship (i.e., positive outcomes yielded higher intention to follow the recommendation than negative outcomes). However, when errors were salient (i.e., when there was a hallucination accompanied by negative consequences) intentions to follow the recommendation decreased further. Together, these studies contribute to an integrative framework that connects cognitive factors (accuracy, usefulness), attitudinal factors (trust), experiential factors (observed outcomes) and contextual factors (error salience) to explain how and when GenAI hallucinations can reduce compliance with travel advice. The findings enhance our understanding of the potential drawbacks of GenAI in tourism and provide actionable guidance for developing more transparent, reliable and user‐centred GenAI travel systems.