A Scientometric Review of Generative Artificial Intelligence Research in Tourism
Abstract
Background: With the rapid and widespread adoption of generative artificial intelligence (GenAI) in the tourism sector, scholars have examined this technology from multiple perspectives. However, a comprehensive and systematic overview of GenAI research in tourism remains lacking. Objective: This study aims to map the current research landscape, identify research hotspots, and trace the developmental trajectory of this emerging field using visualization-based scientometric tools. Methods: Relevant literature indexed in the core collection of the Web of Science was selected as the data source. CiteSpace was used to analyse collaboration networks and keyword co-occurrence, HistCite was applied to construct citation chronologies, and Pajek was employed to identify main research paths. Results: A total of 111 publications on GenAI in tourism (2023–2025) were retrieved. The findings reveal an exponential growth in the research output and demonstrate active collaboration among authors, institutions, and countries. Existing studies are mainly focused on GenAI’s technical characteristics, acceptance of technology, and practical applications. The literature exhibits strong cross-citation patterns, and a clear developmental path of knowledge evolution has been identified. Conclusion: Research interest in GenAI within tourism is expected to continue to increase. Nevertheless, cross-institutional and interdisciplinary collaboration requires further strengthening, and the scope of research topics and perspectives needs to be broadened as the field matures. Implications: This study fills an important gap by providing the first visualization-based scientometric review of GenAI research in tourism, offering valuable insights for scholars and practitioners seeking to understand and advance this rapidly evolving field.
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References
Baig, M. M., Hobson, C., GholamHosseini, H., Ullah, E., & Afifi, S. (2024). Generative AI in improving personalized patient care plans: opportunities and barriers towards its wider adoption. Applied Sciences, 14(23), 10899. https://doi.org/10.3390/app142310899
Batagelj, V., & Mrvar, A. (2008). Analysis of kinship relations with Pajek. Social Science Computer Review, 26(2), 224-246. https://doi.org/10.1177/0894439307299587
Bilgihan, A., Dogru, T., Hanks, L., Line, N., & Mody, M. (2024). The GAI marketing model: A conceptual framework and future research directions. International Journal of Hospitality Management, 123, 103929. https://doi.org/10.1016/j.ijhm.2024.103929
Buhalis, D., O'Connor, P., & Leung, R. (2023). Smart hospitality: from smart cities and smart tourism towards agile business ecosystems in networked destinations. International Journal of Contemporary Hospitality Management, 35(1), 369-393. https://doi.org/10.1108/IJCHM-04-2022-0497
Burdge, R. J. (1983). Making leisure and recreation research a scholarly topic: Views of a journal editor, 1972-1982. Leisure Sciences, 6(1), 99-126. https://doi.org/10.1080/01490408309513024
Calero, C., & Turner, L. W. (2020). Regional economic development and tourism: A literature review to highlight future directions for regional tourism research. Tourism Economics, 26(1), 3-26. https://doi.org/10.1177/1354816619881244
Carvalho, I., & Ivanov, S. (2024). ChatGPT for tourism: applications, benefits, and risks. Tourism review, 79(2), 290-303. https://doi.org/10.1108/TR-02-2023-0088
Chen, C. (2004). Searching for intellectual turning points: progressive knowledge domain visualization. Proceedings of the National Academy of Sciences, 101(suppl_1), 5303-5310. https://doi.org/10.1073pnas.0307513100
Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359-377. https://doi.org/10.1002/asi.20317
Chen, C., Dubin, R., & Kim, M. C. (2014). Orphan drugs and rare diseases: a scientometric review (2000–2014). Expert Opinion on Orphan Drugs, 2(7), 709-724. https://doi.org/10.1517/21678707.2014.920251
Chen, C., Song, I. Y., Yuan, X., & Zhang, J. (2008). The thematic and citation landscape of data and knowledge engineering (1985–2007). Data & Knowledge Engineering, 67(2), 234-259. https://doi.org/10.1016/j.datak.2008.05.004
Chen, J., Guo, Z., Xu, S., Law, R., Liao, C., He, W., & Zhang, M. (2022). A bibliometric analysis of research on intangible cultural heritage tourism using CiteSpace: The perspective of China. Land, 11(12), 2298. https://doi.org/10.3390/land11122298
Choudhary, V., Datta, B., & Mukherjee, S. (2025). Rural tourism: a hybrid review and future research agenda. International Journal of Consumer Studies, 49(1), e70006. https://doi.org/10.1111/ijcs.70006
Dai Tuyen, Q., Vo-Thanh, T., Nghi, N. H., Phuong, B. T., & Bao, B. T. T. (2025). Research on ChatGPT in tourism and hospitality: A systematic review and future directions. International Journal of Hospitality Management, 131, 104287. https://doi.org/10.1016/j.ijhm.2025.104287
Demir, M., & Demir, Ş. Ş. (2023). Is ChatGPT the right technology for service individualization and value co-creation? Evidence from the travel industry. Journal of Travel & Tourism Marketing, 40(5), 383-398. https://doi.org/10.1080/10548408.2023.2255884
Dogru, T., Line, N., Mody, M., Hanks, L., Abbott, J. A., Acikgoz, F., ... & Zhang, T. (2025). Generative artificial intelligence in the hospitality and tourism industry: Developing a framework for future research. Journal of Hospitality & Tourism Research, 49(2), 235-253. https://doi.org/10.1177/10963480231188663
Duong, C. D., Nguyen, T. H., Ngo, T. V. N., Pham, T. T. P., Vu, A. T., & Dang, N. S. (2025). Using generative artificial intelligence (ChatGPT) for travel purposes: parasocial interaction and tourists' continuance intention. Tourism Review, 80(4), 813-827. https://doi.org/10.1108/TR-01-2024-0027
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). Opinion Paper:"So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges, and implications of generative conversational AI for research, practice, and policy. International journal of information management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Dwivedi, Y. K., Malik, T., Hughes, L., & Albashrawi, M. A. (2024). Scholarly discourse on GenAI's impact on academic publishing. Journal of Computer Information Systems, 1-16. https://doi.org/10.1080/08874417.2024.2435386
Dwivedi, Y. K., Pandey, N., Currie, W., & Micu, A. (2024). Leveraging ChatGPT and other generative artificial intelligence (AI)-based applications in the hospitality and tourism industry: practices, challenges, and research agenda. International Journal of Contemporary Hospitality Management, 36(1), 1-12. https://doi.org/10.1108/IJCHM-05-2023-0686
Fakfare, P., Manosuthi, N., Lee, J. S., Han, H., & Jin, M. (2025). Customer word-of-mouth for generative AI: Innovation and adoption in hospitality and tourism. International Journal of Hospitality Management, 126, 104070. https://doi.org/10.1016/j.ijhm.2024.104070
Fan, N., Li, X., Liu, C., & Fan, Z. P. (2025). The Power of AI-Generated Content: Evidence From the Peer-to-Peer Accommodation Market. Journal of Travel Research, 00472875251332951. https://doi.org/10.1177/00472875251332951
Garfield, E. (2009). From the science of science to Scientometrics, visualizing the history of science with HistCite software. Journal of Informetrics, 3(3), 173-179. https://doi.org/10.1016/j.joi.2009.03.009
Geng, Y., Jiang, X., Bai, W., Yan, Y., & Gao, J. (2024b). Research progress of tourism marketing over 30 years: Bibliometrics based on CiteSpace. Ecological Indicators, 162, 112059. https://doi.org/10.1016/j.ecolind.2024.112059
Geng, Y., Zhang, X., Gao, J., Yan, Y., & Chen, L. (2024a). Bibliometric analysis of sustainable tourism using CiteSpace. Technological Forecasting and Social Change, 202, 123310. https://doi.org/10.1016/j.techfore.2024.123310
Gonzáles-Santiago, M. S., Loureiro, S. M. C., Langaro, D., & Ali, F. (2024). Adoption of smart technologies in the cruise tourism services: a systematic review and future research agenda. Journal of Hospitality and Tourism Technology, 15(2), 285-308. https://doi.org/10.1108/JHTT-06-2022-0159
Gursoy, D., Li, Y., & Song, H. (2023). ChatGPT and the hospitality and tourism industry: an overview of current trends and future research directions. Journal of hospitality marketing & management, 32(5), 579-592. https://doi.org/10.1080/19368623.2023.2211993
Hall, C. M. (2011). Publish and perish? Bibliometric analysis, journal ranking, and the assessment of research quality in tourism. Tourism management, 32(1), 16-27. https://doi.org/10.1016/j.tourman.2010.07.001
Haluza, D., & Jungwirth, D. (2023). Artificial intelligence and ten societal megatrends: An exploratory study using GPT-3. Systems, 11(3), 120. https://doi.org/10.3390/systems11030120
Han, H., Kim, S., Hailu, T. B., Al-Ansi, A., Loureiro, S. M. C., & Kim, J. J. (2025). Determinants of approach behavior for ChatGPT and their configurational influence in the hospitality and tourism sector: a cumulative prospect theory. International Journal of Contemporary Hospitality Management, 37(1), 113-139. https://doi.org/10.1108/IJCHM-07-2023-1072
Huang, Y., & Gursoy, D. (2024). How does AI technology integration affect employees' proactive service behaviors? A transactional theory of stress perspective. Journal of Retailing and Consumer Services, 77, 103700. https://doi.org/10.1016/j.jretconser.2023.103700
Isik, C., Aydın, E., Dogru, T., Rehman, A., Sirakaya-Turk, E., & Karagöz, D. (2022). Innovation research in the tourism and hospitality field: A bibliometric and visualization analysis. Sustainability, 14(13), 7889. https://doi.org/10.3390/su14137889
Islam, M. S. (2025). Deconstructing deception: Exploring misleading practices in tourism marketing. Journal of Travel Research. https://doi.org/10.1177/00472875241312177
Jeong, N., & Lee, J. (2024). An aspect-based review analysis using ChatGPT for the exploration of hotel service failures. Sustainability, 16(4), 1640. https://doi.org/10.3390/su16041640
Jiang, Y., Ritchie, B. W., & Benckendorff, P. (2017). Bibliometric visualisation: An application in tourism crisis and disaster management research. Current Issues in Tourism, 22(16), 1925-1957. https://doi.org/10.1080/13683500.2017.1408574
Kim, J. H., Kim, J., Kim, C., & Kim, S. (2023). Do you trust ChatGPTs? Effects of the ethical and quality issues of generative AI on travel decisions. Journal of Travel & Tourism Marketing, 40(9), 779-801. https://doi.org/10.1080/10548408.2023.2293006
Kleib, M., Darko, E. M., Akingbade, O., Kennedy, M., Majekodunmi, P., Nickel, E., & Vogelsang, L. (2024). Current trends and future implications in the utilization of ChatGPT in nursing: a rapid review. International journal of nursing studies advances, 7, 100252. https://doi.org/10.1016/j.ijnsa.2024.100252
Li, H., Xi, J., Hsu, C. H., Yu, B. X., & Zheng, X. K. (2025). Generative artificial intelligence in tourism management: An integrative review and roadmap for future research. Tourism Management, 110, 105179. https://doi.org/10.1016/j.tourman.2025.105179
Liang, Y. (2023). Capital and labour distortion in China: a systematic literature review using HistCite. Accounting & Finance, 63(2), 1759-1784. https://doi.org/10.1111/acfi.12926
Liu, J., Ma, Y., Sun, X., Zhu, Z., & Xu, Y. (2022). A systematic review of higher-order thinking by visualizing its structure through HistCite and CiteSpace software. The Asia-Pacific Education Researcher, 31(6), 635-645. https://doi.org/10.1007/s40299-021-00614-5
Lucio‐Arias, D., & Leydesdorff, L. (2008). Main‐path analysis and path‐dependent transitions in HistCite™‐based historiograms. Journal of the American Society for Information Science and Technology, 59(12), 1948-1962. https://doi.org/10.1002/asi.20903
Mellors, J. (2025). ChatGPT and the tourist trail: pathway to overtourism or sustainable travel?. Current Issues in Tourism, 1-4. https://doi.org/10.1080/13683500.2025.2522939
Mich, L., & Garigliano, R. (2023). ChatGPT for e-Tourism: a technological perspective. Information Technology & Tourism, 25(1), 1-12. https://doi.org/10.1007/s40558-023-00248-x
Mogaji, E., Viglia, G., Srivastava, P., & Dwivedi, Y. K. (2024). Is it the end of the technology acceptance model in the era of generative artificial intelligence?. International Journal of Contemporary Hospitality Management, 36(10), 3324-3339. https://doi.org/10.1108/IJCHM-08-2023-1271
Park, H., Lee, M., & Back, K. J. (2023). A critical review of technology-driven service innovation in hospitality and tourism: current discussions and future research agendas. International Journal of Contemporary Hospitality Management, 35(12), 4502-4534. https://doi.org/10.1108/IJCHM-07-2022-0875
Paul, I., & Roy, G. (2023). Tourist's engagement in eco-tourism: A review and research agenda. Journal of Hospitality and Tourism Management, 54, 316-328. https://doi.org/10.1016/j.jhtm.2023.01.002
Paul, J., Ueno, A., & Dennis, C. (2023). ChatGPT and consumers: Benefits, pitfalls and future research agenda. International Journal of Consumer Studies, 47(4), 1213-1225. https://doi.org/10.1111/ijcs.12928
Pilelienė, L., Grigaliūnaitė, V., & Bogoyavlenska, Y. (2024). A bibliometric review of innovations in sustainable tourism research: Current trends and future research agenda. Sustainability, 16(16), 7124. https://doi.org/10.3390/su16167124
Pradhan, D., Malik, G., & Vishwakarma, P. (2025). Gamification in tourism research: A systematic review, current insights, and future research avenues. Journal of Vacation Marketing, 31(1), 130-156. https://doi.org/10.1177/13567667231188879
Rathjens, B., Gunden, N., Zhang, L., Jain, G., & Law, R. (2025). A systematic review of contactless technologies research in hospitality and tourism during the COVID-Pandemic. Journal of Hospitality & Tourism Research, 49(2), 351-365. https://doi.org/10.1177/10963480231191192
Saleh, M. I. (2025). Generative artificial intelligence in hospitality and tourism: future capabilities, AI prompts and real-world applications. Journal of Hospitality Marketing & Management, 34(4), 467-498. https://doi.org/10.1080/19368623.2025.2458603
Scott, N., Zhang, R., Le, D., & Moyle, B. (2019). A review of eye-tracking research in tourism. Current Issues in Tourism, 22(10), 1244-1261. https://doi.org/10.1080/13683500.2017.1367367
Seo, I. T., Liu, H., Li, H., & Lee, J. S. (2025). AI-infused video marketing: Exploring the influence of AI-generated tourism videos on tourist decision-making. Tourism Management, 110, 105182. https://doi.org/10.1016/j.tourman.2025.105182
Seyfi, S., Gorji, A. S., Vo‐Thanh, T., & Zaman, M. (2025a). Travel Virtual Assistant or Untrusted Advisor? Developing a Typology of Resistance to AI‐Generated Travel Advice. International Journal of Tourism Research, 27(4), e70082. https://doi.org/10.1002/jtr.70082
Seyfi, S., Lee, C., Jo, Y., & Kim, M. J. (2025b). Generational differences in adopting AI-generated travel advice: What drives trust and reduces resistance?. Tourism Management Perspectives, 57, 101364. https://doi.org/10.1016/j.tmp.2025.101364
Song, M., Wang, Y., Guo, R., & Law, R. (2025). When city landmarks meet AI design: the impact of AI painting on the travel intentions of consumers. Asia Pacific Journal of Tourism Research, 1-21. https://doi.org/10.1080/10941665.2025.2486034
Suanpang, P., & Pothipassa, P. (2024). Integrating generative AI and IoT for sustainable smart tourism destinations. Sustainability, 16(17), 7435. https://doi.org/10.3390/su16177435
Tosyali, H., Tosyali, F., & Coban-Tosyali, E. (2025). Role of tourist-chatbot interaction on visit intention in tourism: the mediating role of destination image. Current Issues in Tourism, 28(4), 511-526. https://doi.org/10.1080/13683500.2023.2288937
Tribe, J. (1997). The indiscipline of tourism. Annals of tourism research, 24(3), 638-657. https://doi.org/10.1016/S0160-7383(97)00020-0
Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of tourism research, 81, 102883. https://doi.org/10.1016/j.annals.2020.102883
Van Raan, A. F. (2005). For your citations only? Hot topics in bibliometric analysis. Measurement: interdisciplinary research and perspectives, 3(1), 50-62. http://doi.org/10.1207/s15366359mea0301_7
Wang, S., & Zhang, H. (2025). Promoting sustainable development goals through generative artificial intelligence in the digital supply chain: Insights from Chinese tourism SMEs. Sustainable Development, 33(1), 1231-1248. https://doi.org/10.1002/sd.3152
Wong, I. A., Lian, Q. L., & Sun, D. (2023). Autonomous travel decision-making: An early glimpse into ChatGPT and generative AI. Journal of Hospitality and Tourism Management, 56, 253-263. https://doi.org/10.1016/j.jhtm.2023.06.022
Wong, J. W. C., Lai, I. K. W., & Lin, Y. (2025). The perceived reliability and adoption intention towards human-generated content vs. AI-generated content for travel planning: a moderating role of travel persona. Journal of Travel & Tourism Marketing, 42(4), 461-478. https://doi.org/10.1080/10548408.2025.2468468
Wu, F., Lu, P., & Hsiao, S. W. (2025). Generative Large Model-Driven Methodology for Color Matching and Shape Design in IP Products. Entropy, 27(3), 319. https://doi.org/10.3390/e27030319
Xu, H., Law, R., Lovett, J., Luo, J. M., & Liu, L. (2024). Tourist acceptance of ChatGPT in travel services: the mediating role of parasocial interaction. Journal of Travel & Tourism Marketing, 41(7), 955-972. https://doi.org/10.1080/10548408.2024.2364336
Ye, H., Sun, S., & Law, R. (2022). A review of robotic applications in hospitality and tourism research. Sustainability, 14(17), 10827. https://doi.org/10.3390/su141710827
Yu, Q., Wang, Z., Li, Z., Liu, X., Oteng Agyeman, F., & Wang, X. (2022). Hierarchical structure of depression knowledge network and co-word analysis of focus areas. Frontiers in Psychology, 13, 920920. https://doi.org/10.3389/fpsyg.2022.920920
Yuan, Y., Gretzel, U., & Tseng, Y. H. (2015). Revealing the nature of contemporary tourism research: Extracting common subject areas through bibliographic coupling. International Journal of Tourism Research, 17(5), 417-431. https://doi.org/10.1002/jtr.2004
Zhang, J. J., Wang, Y. W., Ruan, Q., & Yang, Y. (2024). Digital tourism interpretation content quality: A comparison between AI-generated content and professional-generated content. Tourism Management Perspectives, 53, 101279. https://doi.org/10.1016/j.tmp.2024.101279
Zhao, H., Yuan, B., & Song, Y. (2024). Employees' perception of generative artificial intelligence and the dark side of work outcomes. Journal of Hospitality and Tourism Management, 61, 191-199. https://doi.org/10.1016/j.jhtm.2024.10.007
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