When artificial intelligence meets the hospitality and tourism industry: an assessment framework to inform theory and management
Arthur Huang, Ying Chao, Efrén de la Mora Velasco, Anil Bilgihan, Wei Wei
University of Central Florida Florida Atlantic University
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摘要与影响
Purpose This study reviews existing research and current applications of artificial intelligence (AI) in the hospitality and tourism industry. It further proposes a new evaluation framework to inform the susceptibility of AI adoptions. Design/methodology/approach This is a synthesis and evaluation study that qualitatively summarizes and presents findings on AI applications in the hospitality and tourism industry. Current AI applications are rated using a seven-dimensional framework based on Rogers' (2003) diffusion theory. Findings AI adoption susceptibility in the hospitality and tourism industry varies based on the type of AI. Search/booking engines, virtual agents and chatbots rank high in the adoption susceptibility. Research limitations/implications This study bridges innovation diffusion theoretical underpinnings and AI applications. The findings support researchers, developers and managers in evaluating the adoption susceptibility of AI technologies in the hospitality and tourism industry. Originality/value This paper is among the few that focus on assessing AI adoption susceptibility in the hospitality and tourism industry. This paper develops a theory-based framework for systematically evaluating AI innovations in hospitality and tourism.
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学术脉络
学科主题
经济 / 管理AI in Service Interactions
Technology Adoption and User Behaviour · Artificial Intelligence Applications