Artificial Intelligence Research in Tourism and Hospitality Journals: Trends, Emerging Themes, and the Rise of Generative AI

This study examined the trends and key themes of artificial intelligence in the field of tourism and hospitality research. On 5 March 2025, a search was performed using “artificial intelligence” and related terms in the “Title, Abstract, and Keywords”, focusing on tourism and hospitality journals indexed in Scopus. The identified documents were subjected to performance analysis and science mapping techniques. The search yielded 921 documents, comprising 882 articles and 39 reviews. The number of documents increased from 3 in 1987 to 277 in 2024. R. Law from the University of Macau was the most prolific author, while the Hong Kong Polytechnic University recorded the highest publication count. Chinese researchers produced the most documents, totaling 262 articles and reviews. A keyword co-occurrence analysis revealed four key themes: “machine learning and sentiment analysis of online reviews”, “adoption of AI including robots and ChatGPT in the hospitality industry”, “artificial neural networks for tourism management and demand analysis”, and “random forest models in travel”. Additionally, the study noted a shift in research focus from tourism demand forecasting and sentiment analysis to using service bots and applying artificial intelligence to enhance service quality, with a recent emphasis on generative AI tools like ChatGPT.

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Publication Details

Journal
Tourism and Hospitality
Published
2025-04-03
DOI
https://doi.org/10.3390/tourhosp6020063
Citations
21
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
52.10
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article

Artificial Intelligence Research in Tourism and Hospitality Journals: Trends, Emerging Themes, and the Rise of Generative AI

Billy T.W. Yu, Wai Ming To
21 citations
Tourism and Hospitality
AI in Service Interactions
52.10
article

Artificial Intelligence Research in Tourism and Hospitality Journals: Trends, Emerging Themes, and the Rise of Generative AI

Billy T.W. Yu, Wai Ming To
article en
21 citations

Abstract

This study examined the trends and key themes of artificial intelligence in the field of tourism and hospitality research. On 5 March 2025, a search was performed using “artificial intelligence” and related terms in the “Title, Abstract, and Keywords”, focusing on tourism and hospitality journals indexed in Scopus. The identified documents were subjected to performance analysis and science mapping techniques. The search yielded 921 documents, comprising 882 articles and 39 reviews. The number of documents increased from 3 in 1987 to 277 in 2024. R. Law from the University of Macau was the most prolific author, while the Hong Kong Polytechnic University recorded the highest publication count. Chinese researchers produced the most documents, totaling 262 articles and reviews. A keyword co-occurrence analysis revealed four key themes: “machine learning and sentiment analysis of online reviews”, “adoption of AI including robots and ChatGPT in the hospitality industry”, “artificial neural networks for tourism management and demand analysis”, and “random forest models in travel”. Additionally, the study noted a shift in research focus from tourism demand forecasting and sentiment analysis to using service bots and applying artificial intelligence to enhance service quality, with a recent emphasis on generative AI tools like ChatGPT.

Tourism and HospitalityVol. 6(2)
Macao Polytechnic University (MO)
Openalex Percentile: Top 0%
AI in Service Interactions
52.10
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Artificial Intelligence Research in Tourism and Hospitality Journals: Trends, Emerging Themes, and the Rise of Generative AI — Billy T.W. Yu, Wai Ming To · Tourism and Hospitality (2025) | TGRS Research Map | TGRS