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

doi:10.1016/j.annals.2021.103155

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

Ann Tour Res. 2021 May:88:103155. doi: 10.1016/j.annals.2021.103155. Epub 2021 Jan 28.

Authors

Richard T R Qiu¹, Doris Chenguang Wu², Vincent Dropsy³, Sylvain Petit^{3

4

5}, Stephen Pratt⁶, Yasuo Ohe⁷

Affiliations

¹ Department of Integrated Resort and Tourism Management, Faculty of Business Administration, University of Macau, Taipa, Macao, China.
² Business School, Sun Yat-sen University, Guangzhou, China.
³ Center for Research on Tourism in Oceania Pacific (CETOP), Governance and Insular Development (GDI, EA 1384) Research Center, University of French Polynesia, French Polynesia.
⁴ CRISS (EA 4343), Polytechnic University Hauts-de-France, France.
⁵ CRESEM (EA 7397) University of Perpignan, Via Dominitia, France.
⁶ School of Tourism & Hospitality Management, University of the South Pacific, Fiji.
⁷ Department of Agribusiness Management, Faculty of International Agriculture and Food Studies, Tokyo University of Agriculture, Tokyo, Japan.

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.

Keywords: COVID-19; Judgmental-adjusted forecasting; Recovery scenarios; Stacking models; Tourism forecasting competition.