Unpacking AI for Hospitality and Tourism Services: Exploring the Role of Perceived Enjoyment on Future Use Intentions

Keywords

Expectation-confirmation models; Future use intention; Hospitality and tourism; Perceived Enjoyment; Perceived performance; Satisfaction with AI; Technology adoption

Abstract

Emergent technologies such as artificial intelligence (AI) have shown the power to transform the hospitality and tourism industry. There is an increasing need for empirical insight into the antecedents of AI-based tourism and hospitality services. This study expanded the expectation-confirmation model to examine determining factors of customers' future use intentions of AI services. A self-administered online survey was administered to test the new model. 380 responses from tourists and guests who used AI-based services in the prior eighteen months of the survey delivery were analyzed through confirmatory factor analysis and structural equation modeling. The results indicated that confirmation of expectations, perceived enjoyment, and perceived performance were significant predictors of satisfaction with AI and future use intentions. Further, confirmation of expectations and perceived performance were also found to be antecedents of perceived enjoyment. The results highlighted the importance of leveraging the hedonic dimensions and expectation formation to support the adoption of AI. • This paper expanded the expectation-confirmation model to examine key determining factors of customers' continuance intentions of AI-based hospitality and tourism services. • This paper substantiated the direct positive impact of perceived performance and confirmation on consumers' continuance intentions of AI in hospitality and tourism settings. • Perceived performance and consumers' intention to continue to use were partially mediated by perceived enjoyment, highlighting the importance of hedonic attributes for AI applications. • We proposed practical management suggestions for effective strategies to ensure the successful implementation of AI-based services.

Publication Date

3-2024

Original Citation

Huang, A., Ozturk, A. B., Zhang, T., de la Mora Velasco, E., & Haney, A. (2024). Unpacking AI for hospitality and tourism services: Exploring the role of perceived enjoyment on future use intentions. International Journal of Hospitality Management, 119, N.PAG. https://doi.org/10.1016/j.ijhm.2024.103693

Document Type

Paper

Source Title

International Journal of Hospitality Management

Volume

119

College

Rosen College of Hospitality Management

Location

Rosen College of Hospitality Management

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