Extending the Technology Acceptance Model in AI-Driven Tourism Marketing: The Roles of Two-Way Communication, Personalization, and Co-Creation - Achmad Yanu Alif Fianto; Sharmini Abdullah (Journal of Computers and Digital Business, 2026)
This study extends the Technology Acceptance Model (TAM) to explain tourists' acceptance of AI-driven tourism marketing, which functions as an interactive, personalized, and participatory interface supporting destination search, recommendation, itinerary design, and engagement. Drawing on an extended TAM, this study examines the effects of perceived two-way communication, perceived personalization, and perceived co-creation on perceived usefulness, attitude, and tourist behavioral intention. A quantitative survey of 420 tourists who had interacted with AI-supported tourism platforms was analyzed using PLS-SEM. The measurement model demonstrated satisfactory reliability and validity, with outer loadings ranging from 0.724 to 0.891, Cronbach's alpha from 0.837 to 0.902, composite reliability from 0.885 to 0.928, and AVE from 0.606 to 0.721. The structural model revealed that two-way communication, personalization, and co-creation significantly influenced perceived usefulness and attitude, while attitude emerged as the strongest predictor of behavioral intention. The model demonstrated acceptable fit (SRMR = 0.057; NFI = 0.912) and explained 68.4% of the variance in tourist behavioral intention. The findings suggest that tourists accept AI-driven tourism marketing not only because it is useful and easy to use, but also because it enables responsive communication, relevant recommendations, and meaningful participation in travel experience design.