The past, present, and future of AI in hospitality and tourism: a bibliometric analysis
Junyun Liao, Wu Mingyue, Peng Du, Raffaele Filieri, Kai He
Abstract
Purpose Research on artificial intelligence (AI) in the tourism and hospitality (T&H) sector is continuously evolving. This paper aims to offer a comprehensive bibliometric analysis of AI research within the T&H industry, examining its developmental trajectory, underlying knowledge structure. Design/methodology/approach This study conducted a bibliometric analysis of 2,045 articles (1976–2024). Various bibliometric techniques, such as performance analysis, keyword co-occurrence mapping and bibliographic coupling, were used to identify the research progress. Findings This research discerns four crucial research themes, the frontiers of AI in T&H, and the most frequently adopted theories, including the theory of planned behavior (TPB), grounded theory and technology acceptance model (TAM). Research limitations/implications This research offers deeper understanding of the prominent research themes, prevalent theories and frontiers in the field of AI within T&H context over the past four decades. Furthermore, the research discusses future research directions. Originality/value This study offers a comprehensive review of AI research in T&H. Employing the bibliometric method, it yields the primary research topics and frontiers. These findings furnish offer insightful future research directions.