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Visitor arrivals forecasts amid COVID-19: A perspective from the Asia and Pacific team

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  • Qiu, Richard T.R.
  • Wu, Doris Chenguang
  • Dropsy, Vincent
  • Petit, Sylvain
  • Pratt, Stephen
  • Ohe, Yasuo

Abstract

It is important to provide scientific assessments concerning the future of tourism under the uncertainty surrounding COVID-19. To this purpose, this paper presents a two-stage three-scenario forecast framework for inbound-tourism demand across 20 countries. The main findings are as follows: in the first-stage ex-post forecasts, the stacking models are more accurate and robust, especially when combining five single models. The second-stage ex-ante forecasts are based on three recovery scenarios: a mild case assuming a V-shaped recovery, a medium one with a V/U-shaped, and a severe one with an L-shaped. The forecast results show a wide range of recovery (10%–70%) in 2021 compared to 2019. This two-stage three-scenario framework contributes to the improvement in the accuracy and robustness of tourism demand forecasting.

Suggested Citation

  • Qiu, Richard T.R. & Wu, Doris Chenguang & Dropsy, Vincent & Petit, Sylvain & Pratt, Stephen & Ohe, Yasuo, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Asia and Pacific team," Annals of Tourism Research, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:anture:v:88:y:2021:i:c:s0160738321000177
    DOI: 10.1016/j.annals.2021.103155
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    6. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
    7. Xi Wu & Adam Blake, 2023. "The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
    8. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    9. Fangming Qin & Gezhi Chen, 2022. "Vulnerability of Tourist Cities’ Economic Systems Amid the COVID-19 Pandemic: System Characteristics and Formation Mechanisms—A Case Study of 46 Major Tourist Cities in China," Sustainability, MDPI, vol. 14(5), pages 1-18, February.
    10. Yi-Chung Hu, 2023. "Tourism combination forecasting using a dynamic weighting strategy with change-point analysis," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(14), pages 2357-2374, July.
    11. Yasuo Ohe, 2023. "Exploring New Opportunities for Agritourism in the Post-COVID-19 Era," Agriculture, MDPI, vol. 13(6), pages 1-4, June.
    12. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).
    13. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
    14. Hu, Yi-Chung, 2023. "Air passenger flow forecasting using nonadditive forecast combination with grey prediction," Journal of Air Transport Management, Elsevier, vol. 112(C).
    15. Kleanthis Natsiopoulos & Nickolaos G. Tzeremes, 2024. "ARDL: An R Package for ARDL Models and Cointegration," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1757-1773, September.
    16. Jiafeng Gu, 2024. "Does the Visa-Free Policy Promote Inbound Tourism? Evidence From China," SAGE Open, , vol. 14(2), pages 21582440241, June.
    17. Guan, Bo & Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed, 2022. "Forecasting tourism growth with State-Dependent Models," Annals of Tourism Research, Elsevier, vol. 94(C).
    18. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).
    19. Liu, Anyu & Kim, Yoo Ri & O'Connell, John Frankie, 2021. "COVID-19 and the aviation industry: The interrelationship between the spread of the COVID-19 pandemic and the frequency of flights on the EU market," Annals of Tourism Research, Elsevier, vol. 91(C).
    20. Marcus Roller, 2022. "Pre-Crisis Determinants of Tourism Resilience," Diskussionsschriften credresearchpaper39, Universitaet Bern, Departement Volkswirtschaft - CRED.
    21. Xi Wu & Adam Blake, 2023. "Does the combination of models with different explanatory variables improve tourism demand forecasting performance?," Tourism Economics, , vol. 29(8), pages 2032-2056, December.
    22. He, Ling-Yang & Li, Hui & Bi, Jian-Wu & Yang, Jing-Jing & Zhou, Qing, 2022. "The impact of public health emergencies on hotel demand - Estimation from a new foresight perspective on the COVID-19," Annals of Tourism Research, Elsevier, vol. 94(C).
    23. Davide Provenzano & Serena Volo, 2022. "Tourism recovery amid COVID-19: The case of Lombardy, Italy," Tourism Economics, , vol. 28(1), pages 110-130, February.
    24. Michał Roman & Kumar Bhatta & Monika Roman & Prakash Gautam, 2021. "Socio-Economic Factors Influencing Travel Decision-Making of Poles and Nepalis during the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(20), pages 1-16, October.
    25. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).

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