Artificial intelligence in tourism and hospitality: Bibliometric analysis and research agenda

Artificial intelligence (AI) has received a great deal of attention in tourism and hospitality (T&H) literature and practices. The authors of this study propose a bibliometric approach aiming to examine current state-of-the-art AI research in T&H. In total, 1035 manuscripts published between 1984 and 2021 were retrieved form Scopus and Web of Science. This study highlights the evolving volume of studies, authors, affiliated institutions and coun-tries, authorship networks, keyword co-occurrences, and keyword networks and also includes a thematic map that highlights four types of research: motor themes (i.e., artificial neural networks and data mining); basic and transversal themes (i.e., text mining and sentiment analysis, Internet of things and big data, COVID and AI); emerging themes (experience with service robots); and specialized and peripheral themes (e.g., forecasting tourism models, augmented reality and virtual reality, and biometrics). The paper concludes with future per-spectives and research avenues in this field.

Automated summary

This study provides a bibliometric analysis of the current state-of-the-art AI research in the tourism and hospitality industry. The findings reveal an increasing volume of research in this field and identify several key themes, including artificial neural networks, data mining, text mining and sentiment analysis, internet of things and big data.