University of South Florida (USF) M3 Publishing
Abstract
With the increase in the combination of artificial intelligence and the service industry, many applications of artificial intelligence in tourism have been gradually spawned. However, most of the existing research focuses on the algorithms and models of artificial intelligence, and few scholars have systematically reviewed the intersection of tourism and artificial intelligence, this study is based on scientometric, reviewing and sorting out 2689 relevant literature published in 2000-2021, and achieving the three purposes of status carding, hot spot snooping and trend prediction. First, through the participating locations, institutions and authors of collaborative networks, the main sources of AI-related research in tourism and their distribution patterns are identified. Secondly, the research hotspots related to the tourism artificial intelligence are located at this stage by basing on literature co-citation and keyword co-emergence analysis. Finally, based on the emergent perspective, the knowledge graph is drawn to reveal the frontier issues and research trends of artificial intelligence in tourism. This paper is the first systematic review of CiteSpace 5.8 since the emergence of tourism artificial intelligence, and the results of this study will provide valuable guidance for research and practice activities to further explore the convergence of tourism and artificial intelligence.
DOI
https://www.doi.org/10.5038/9781955833080
Recommended Citation
Wang, R., Mu, Y., & Huang, Y. (2022). A scientometric review of artificial intelligence in tourism (2000-2021). In L. Altinay, O. M. Karatepe, & M. Tuna (Eds.), Advances in managing tourism across continents (Vol. 2, pp. 1–8). USF M3 Publishing. https://www.doi.org/10.5038/9781955833080
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
