Artificial Intelligence Chatbots in Philippine Tourism: An Extended Technology Acceptance Model of Trust, Privacy Concerns, Service Quality, and Booking Intention - Cabaraban, Loida A.; Juera, Walter B.; Ruiz-Betco, Mary Jane; Tamalla-Cabigayan, Hazel; Gregorio, Alecris V.; Doblas, Mark (International Review of Management and Marketing, 2026)
The widespread application of AI chatbots in tourism has changed the way people find information about their travels, communicate with service providers, and make booking transactions. Although the application of conversational AI in tourism systems is increasingly common, there is still no sufficient empirical evidence related to the factors affecting tourists' willingness to use AI chatbot-assisted booking system in emerging tourism destinations. Based on the extended version of Technology Acceptance Model (TAM), this study explores the impact of perceived usefulness, perceived ease of use, trust, privacy concerns, and service quality on booking intention and attitude toward AI chatbots as a mediating variable. In this study, the quantitative research design has been used, and data have been gathered through surveying 373 tourists who visited major destinations in Misamis Oriental and Bukidnon, Philippines, during February 2025 – December 2025. For data analysis, the Partial Least Squares Structural Equation Modeling method was applied. As a result, the effect of perceived usefulness, service quality, privacy concerns, and attitude toward AI chatbots on booking intention has been confirmed. Perceived usefulness, privacy concerns, and service quality have also proved to be significant predictors of attitude toward AI chatbots, while perceived ease of use and trust have failed to show significant effect on attitude. Moreover, attitude toward AI chatbots acts as a mediator between perceived usefulness, privacy concerns, service quality, and booking intention. These findings show that tourists appraise AI chatbot technologies mainly in terms of functional value and performance rather than just trust considerations. The current study extends the Technology Acceptance Model by including service-related and privacy-related variables.