Acceptance of ChatGPT as an auxiliary tool enhancing travel experience

Amir Batouei · Davoud Nikbin · Behzad Foroughi

20 citations0/0 files storedJournal of Hospitality and Tourism Insights

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Technology Adoption and User Behaviour Diverse Aspects of Tourism Research AI in Service Interactions

Abstract

Purpose This study explores the acceptance of ChatGPT as an auxiliary tool for enhancing travel experiences by extending the technology acceptance model (TAM). It incorporates perceived convenience, information quality, personal innovativeness and compatibility to understand the factors driving ChatGPT adoption in travel and tourism. The research addresses a gap in AI adoption literature for travel and provides insights into users’ perceptions of AI-driven technologies in streamlining travel planning and offering personalized, real-time assistance. Design/methodology/approach The study follows a quantitative approach, collecting data through an online survey on the Prolific platform. A total of 441 responses were analyzed using structural equation modeling (SEM) to assess the relationships between the variables and the moderating role of compatibility. Findings The findings confirm that attitude significantly influences behavioral intention, with perceived enjoyment and convenience shaping user attitudes toward ChatGPT. Perceived ease of use impacts both attitude and usefulness but does not significantly affect enjoyment. Information quality is key to both enjoyment and usefulness, while personal innovativeness has mixed effects. Compatibility did not significantly moderate relationships between constructs, suggesting that the tool’s features may outweigh compatibility concerns in adoption. Originality/value This study extends TAM with hedonic and contextual factors for AI technologies in travel and tourism. It challenges assumptions about ease of use and personal innovativeness, suggesting that the novelty of AI like ChatGPT diminishes as it becomes mainstream. Compatibility insights offer fresh perspectives on how the technology meets users’ needs.

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References

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2025Applying UTAUT and experiential consumption theory to understand the adoption of ChatGPT’s digitalized itinerary 2025Machine learning in travel mode choice studies: A systematic literature review of applications, methods, and challenges

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