Abstract : The rapid integration of Artificial Intelligence (AI) and mobile applications into tourism services has fundamentally transformed how travelers interact with destinations, yet the mechanisms through which these technologies drive tourist engagement remain insufficiently understood. This study examines the influence of AI and mobile applications on tourist engagement within the smart tourism ecosystem in Indonesia, while concurrently investigating the mediating roles of tourist satisfaction and technology trust, alongside the moderating effects of digital literacy, technology experience, and risk perception. A quantitative research design was employed, with primary data collected through a structured survey instrument administered to domestic and international tourists across selected smart tourism destinations in Indonesia. Hypothesised relationships were tested using Structural Equation Modeling–Partial Least Squares (SEM-PLS), which is well-suited to the complexity of the proposed integrative model. The findings confirm that AI adoption and mobile application usage exert significant positive effects on tourist engagement. Tourist satisfaction and technology trust were validated as meaningful mediators, amplifying the relationship between technology utilization and engagement. Digital literacy and technology experience moderated this relationship positively, whereas risk perception exerted an attenuating effect, diminishing engagement levels among tourists with elevated risk concerns. These results underscore that tourist engagement in smart tourism contexts is shaped not solely by technological capabilities but equally by psychological dispositions and individual competencies. Theoretically, this study contributes an integrative framework that bridges technology adoption, consumer psychology, and smart tourism literature. Practically, the findings provide actionable guidance for destination management organizations and technology developers seeking to design more responsive, experience-centred digital tourism ecosystems. Future research is encouraged to replicate and extend the model across diverse tourism contexts and cultural settings.
Cam et al. (Fri,) studied this question.