Artificial Intelligence in Tourism, Leisure, and Hospitality; in Business and Social Sciences; and in Engineering and Computational Sciences: A Comparative Bibliometric Review

This study presents a comprehensive bibliometric review of research on artificial intelligence (AI) in tourism, leisure, and hospitality, focussing on the comparative perspectives of Business and Social Sciences and Engineering and Computational Sciences. Using a dataset of 1,013 journal articles published between 1977 and August 2024, sourced from Scopus, we analysed trends in publication output, key thematic areas, and influential authors and countries. The analysis, conducted using the biblioshiny function in R-studio, highlights a significant representation of researchers from Europe, North America, and Asia, but a noticeable lack of contributions from African countries. Key research topics span AI applications in tourism and hospitality, with techniques like deep learning, sentiment analysis, and machine learning gaining prominence. The study identifies basic, motor, niche, and emerging/declining themes across both disciplines, providing insights into the evolving intellectual structure of AI research in tourism. This bibliometric review offers a roadmap for future research, emphasising the need for interdisciplinary collaboration and greater geographic diversity in AI and tourism scholarship.