ChatGPT adoption disposition and sustainable travel planning intention in a non-random international sample

Type of the article: Research ArticleAbstractTourism decision-making increasingly relies on digital assistants, yet the mechanism through which conversational AI may support sustainable travel planning remains unclear. The purpose of this study was to examine whether ChatGPT adoption disposition is associated with sustainable travel planning intention and whether this association operates through ChatGPT relationship engagement and AI-assisted travel-planning experience. A quantitative cross-sectional survey was conducted online between January and March 2025 among adults from Tunisia, France, Italy, Germany, and other countries who had previously used ChatGPT to search for environmentally responsible travel information. From 234 questionnaires initially received, 48 were excluded after screening and quality control, leaving 186 valid responses. Partial Least Squares Structural Equation Modeling was used to test the measurement model, structural paths, mediation effects, and dummy-coded country controls, with France as the reference category. The results show that attitude (β = 0.421, p < 0.001), subjective norms (β = 0.353, p < 0.001), and perceived behavioral control (β = 0.297, p < 0.001) are positively associated with ChatGPT adoption disposition. The direct path from ChatGPT adoption disposition to sustainable travel planning intention is not significant (β = 0.080, p = 0.734). However, two indirect effects are significant: through ChatGPT relationship engagement (β = 0.250, p < 0.001) and through AI-assisted travel-planning experience (β = 0.124, p < 0.001). Country controls are non-significant. The study concludes that ChatGPT is more relevant as an experiential and relational facilitator than as a direct driver of sustainable travel intention, within the limits of a pooled non-probability international sample.