AI-Driven Personalization and Traveler Satisfaction: The Role of Trust and Perceived Value, and Technology Readiness

This study investigates how AI-driven personalization shapes traveler satisfaction in a post-adoption tourism context, with particular attention to the mechanisms and boundary conditions through which personalization is associated with experiential outcomes. Using an integrated post-adoption framework, the study conceptualizes AI-driven personalization as an experiential input influencing satisfaction through trust formation, perceived value, and individual readiness to engage with technology. Survey data were collected from 347 tourists with direct experience of AI-enabled tourism services in Kosovo. The relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that AI-driven personalization is positively associated with traveler satisfaction. It enhances trust in AI-powered systems, and trust is positively associated with perceived value. Perceived value mediates the relationship between trust in AI-powered systems and traveler satisfaction, highlighting value appraisal as a central post-adoption mechanism. AI-driven personalization is also indirectly associated with traveler satisfaction through a sequential mechanism, in which trust precedes perceived value in the experiential evaluation process. Technology readiness moderates the relationship between perceived value and traveler satisfaction, indicating heterogeneous experiential responses to AI-enabled tourism services. The study contributes to tourism and hospitality research by demonstrating a sequential relational–evaluative mechanism through which AI-driven personalization is associated with traveler satisfaction, shifting the focus from adoption-based explanations toward post-adoption experiential pathways. It further clarifies the role of trust as a relational mechanism preceding value formation and identifies technology readiness as a boundary condition shaping satisfaction outcomes in an emerging destination context. The findings also offer practical guidance for designing AI-enabled services that strengthen trust, enhance value perceptions, and align personalization strategies with varying levels of traveler technology readiness.