Forecasting tourism recovery amid COVID-19

Hanyuan Zhang, Haiyan Song, Long Wen, Chang Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

The profound impact of the coronavirus disease 2019 (COVID-19) pandemic on global tourism activity has rendered forecasts of tourism demand obsolete. Accordingly, scholars have begun to seek the best methods to predict the recovery of tourism from the devastating effects of COVID-19. In this study, econometric and judgmental methods were combined to forecast the possible paths to tourism recovery in Hong Kong. The autoregressive distributed lag-error correction model was used to generate baseline forecasts, and Delphi adjustments based on different recovery scenarios were performed to reflect different levels of severity in terms of the pandemic's influence. These forecasts were also used to evaluate the economic effects of the COVID-19 pandemic on the tourism industry in Hong Kong.

Original languageEnglish
Article number103149
JournalAnnals of Tourism Research
Volume87
DOIs
Publication statusPublished - Mar 2021

Keywords

  • COVID-19
  • Crisis management
  • Delphi method
  • Forecasting scenarios
  • Tourism demand

ASJC Scopus subject areas

  • Development
  • Tourism, Leisure and Hospitality Management

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