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Drivers and barriers to generative AI adoption in tourism: A weigth-based perspective from tourists
Abstract   Open access   Peer reviewed

Drivers and barriers to generative AI adoption in tourism: A weigth-based perspective from tourists

CAUTHE 2026 Conference Handbook: Cultivating cohesion and connection through tourism, hospitality, and events, pp.162-162
Council for Australasian Tourism and Hospitality Education Conference 2026 (CAUTHE 2026) (Adelaide, 09/02/2026–12/02/2026)
2026
Handle:
https://hdl.handle.net/10863/51718

Abstract

Tourism, Marketing and Regional Development Netnography Generative artificial intelligence Sustainable tourism development AI adoption Digital technology adoption Barriers Drivers
With the rapid rise of Generative AI, tourism and hospitality have become important areas to study its adoption. Tools like ChatGPT support tourists’ trip planning and make decisions more easily. However, existing research offers mixed and fragmented findings, with little agreement on the main factors that encourage or limit adoption. To address this gap, this study conducts a systematic literature review and weight analysis of 42 quantitative studies, covering 370 relationships and 15,214 consumers. The results show that trust, authenticity, satisfaction, and user attitude are the most consistent predictors of adoption, while concerns over information quality represent the strongest deterrent. A complementary netnographic analysis of Reddit discussions further highlights widespread dissatisfaction with inaccurate or inconsistent information. The study contributes by consolidating scattered constructs into a clear classification of drivers and barriers and by clarifying their relative strength through weight analysis. Practically, it underscores the importance of accuracy, transparency, and reliability for sustaining trust in GenAI-enabled tourism services.
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