AI-Mediated Travel Planning: The Impact of Public and Private AI on Certitude, Attitude, and Booking Behavior

Despite the rapid adoption of AI in tourism, limited research has systematically compared how public versus private AI systems differentially influence traveler psychology and behavior. Drawing on Human-Computer Intra-Action (HCIA) theory, this study addresses a critical gap in the tourism literature by distinguishing the socio-technical roles of public and private AI in AI-mediated travel planning. A sequential exploratory mixed-methods design was employed: Study 1 conducted thematic analysis of 66 interviews, while Study 2 utilized structural equation modeling based on 421 survey responses (pilot study of n = 45). Findings reveal that private AI significantly enhances certitude (β: 0.632, p < 0.001) and personalization, while public AI strengthens trust and attitude (β: 0.772, p < 0.001). Private AI more effectively drives travel intention through tailored engagement, whereas public AI promotes informational equity and social responsibility, positively influencing destination recognition and emotional response. Certitude and attitude emerge as key mediators in shaping travel decisions. This research advances theoretical understanding of HCIA and offers practical guidance for designing ethical, inclusive, and user-centered AI systems in tourism.