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

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

Research output: Journal article publicationJournal articleAcademic researchpeer-review

33 Citations (Scopus)

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.

Original languageEnglish
Article number103155
JournalAnnals of Tourism Research
Volume88
DOIs
Publication statusPublished - May 2021
Externally publishedYes

Keywords

  • COVID-19
  • Judgmental-adjusted forecasting
  • Recovery scenarios
  • Stacking models
  • Tourism forecasting competition

ASJC Scopus subject areas

  • Development
  • Tourism, Leisure and Hospitality Management

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