Building trust for sustained generative AI travel adoption
Behzad Foroughi, Hanh Thi My Vu, Park Thaichon
Abstract
Purpose Despite the growing integration of generative AI (GenAI) in travel planning, research on sustained user engagement remains limited. This study, grounded in the “Stimulus-Organism-Response” (SOR) framework, aims to investigate how content- and technology-related factors influence cognitive and affective trust, which affects the sustained use of GenAI in travel decision-making. Design/methodology/approach Data from 408 users were analyzed using a hybrid “Partial Least Squares Structural Equation Modeling” (PLS-SEM) and “Artificial Neural Network” (ANN) approach to examine the relationships among key determinants and identify the relative importance of predictors. Findings Findings reveal that perceived intelligence, information accuracy, personalization, ease of use, interactivity and anthropomorphism significantly shape trust. Both cognitive and affective trust positively influence sustained use, with novelty seeking amplifying the impact of affective trust and technology anxiety diminishing the effect of cognitive trust. The hybrid approach highlights complementary insights of explanatory and predictive modeling. Originality/value This study advances research on AI adoption and trust in the context of travel planning by clarifying the roles of rational and emotional factors in sustained GenAI use. The findings offer actionable insights for travel and hospitality service providers seeking to improve traveler engagement and encourage continued use of GenAI-driven platforms.