When Chatbots Create Doubt: Unpacking AI-Driven Risks and Consumer Skepticism in the Hospitality Sector

This study examines how perceived risks shape consumer skepticism and booking intention toward AI chatbots in hotel services. Drawing on Perceived Risk Theory, we analyzed survey data from 309 hotel customers in Vietnam using partial least squares structural equation modeling (PLS-SEM). The findings show that misinformation, data privacy, expectation, and anthropomorphic risks significantly increase consumer skepticism, whereas interaction risk does not. Skepticism, in turn, significantly reduces booking intention and mediates the effects of most risk dimensions. By identifying skepticism as a key psychological mechanism in AI-enabled hotel booking, this study extends chatbot adoption research and offers practical guidance for improving transparency, information accuracy, privacy communication, and chatbot design.