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Hot topics and emerging trends in tourism forecasting research: A scientometric review

Author

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  • Han Liu

    (Jilin University, China)

  • Ying Liu

    (Jilin University, China)

  • Yonglian Wang

    (Jilin University of Finance and Economics, China)

  • Changchun Pan

    (Jilin University, China)

Abstract

Tourism forecasting has been a focal point of tourism research over the past few decades as a result of the corresponding rapid development and expansion of the tourism industry. A bibliometric analysis, based on 543 articles retrieved from the Web of Science Core Collection database, was carried out to provide insights into hot topics as well as emerging trends in tourism forecasting research. The results show that the research outputs related to tourism forecasting have grown rapidly since 2006. The observed hot topics in tourism forecasting were to predict tourism demand via various models, including time series models, econometric models, and artificial intelligence-based methods, and to compare the forecasting accuracy of models. An emerging trend of tourism forecasting is to use methods based on data from a web-based search engine. Our study provides insights and valuable information for researchers to identify new perspectives on hot topics and research frontiers.

Suggested Citation

  • Han Liu & Ying Liu & Yonglian Wang & Changchun Pan, 2019. "Hot topics and emerging trends in tourism forecasting research: A scientometric review," Tourism Economics, , vol. 25(3), pages 448-468, May.
    • Handle: RePEc:sae:toueco:v:25:y:2019:i:3:p:448-468
    DOI: 10.1177/1354816618810564
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    References listed on IDEAS

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    12. Jaume Rosselló Nadal & María Santana Gallego, 2022. "Gravity models for tourism demand modeling: Empirical review and outlook," Journal of Economic Surveys, Wiley Blackwell, vol. 36(5), pages 1358-1409, December.

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