Governing health data disclosure in smart tourism: the roles of transparency, consent usability, and privacy fatigue

Smart tourism increasingly relies on health data to personalise services, yet tourists face a privacy paradox shaped by both opportunity and risk. This study investigates how system design and individual factors jointly shape health data disclosure in smart tourism. Grounded in Privacy Calculus Theory and the Antecedents–Privacy Concerns–Outcomes model, we conducted a 2 × 2 experiment (N = 412) manipulating algorithmic transparency and eConsent usability, while measuring privacy fatigue, perceived data control, trust in artificial intelligence, and digital health literacy. Using partial least squares structural equation modelling, results reveal that transparent algorithms and user-friendly consent interfaces significantly enhance both perceived control and trust, which in turn increase disclosure intention. Privacy fatigue substantially undermines these effects, yet digital health literacy buffers its negative impact on perceived control. Notably, trust in artificial intelligence emerged as the strongest driver of disclosure intention, exceeding cognitive assessments of control. These findings extend privacy calculus research by integrating emotional and cognitive mechanisms and by demonstrating the moderating role of literacy in digital health contexts. For practice, the study underscores the need for transparent design, intuitive consent, and user education to foster responsible data sharing in smart tourism ecosystems.