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

被引：78

作者：

Qiu, Richard T. R. ^{[1
]}

Wu, Doris Chenguang ^{[2
]}

Dropsy, Vincent ^{[3
]}

Petit, Sylvain ^{[3
,4
,5
]}

Pratt, Stephen ^{[6
]}

Ohe, Yasuo ^{[7
]}

机构：

[1] Univ Macau, Fac Business Adm, Dept Integrated Resort & Tourism Management, Taipa, Macao, Peoples R China

[2] Sun Yat Sen Univ, Business Sch, Guangzhou, Peoples R China

[3] Univ French Polynesia, Ctr Res Tourism Oceania Pacific CETOP, Governance & Insular Dev, GDI,EA 1384,Res Ctr, Punaauia, French Polynesi, France

[4] Polytech Univ Hauts de France, CRISS, EA 4343, Valenciennes, France

[5] Univ Perpignan, CRESEM, EA 7397, Via Dominitia, Perpignan, France

[6] Univ South Pacific, Sch Tourism & Hospitality Management, Suva, Fiji

[7] Tokyo Univ Agr, Fac Int Agr & Food Studies, Dept Agribusiness Management, Tokyo, Japan

来源：

ANNALS OF TOURISM RESEARCH | 2021年 / 88卷

关键词：

COVID-19; Tourism forecasting competition; Stacking models; Recovery scenarios; Judgmental-adjusted forecasting; TOURISM DEMAND;

D O I：

10.1016/j.annals.2021.103155

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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. (C) 2021 Elsevier Ltd. All rights reserved.

引用

页数：16

共 41 条

[1] The tourism forecasting competition
Athanasopoulos, George
Hyndman, Rob J.
Song, Haiyan
Wu, Doris C.
[J]. INTERNATIONAL JOURNAL OF FORECASTING, 2011, 27 (03) : 822 - 844
[2] Casas I., 2020, TVREG TIME VARYING C
[3] Crouch G. I., 1994, Journal of Travel Research, V32, P41, DOI 10.1177/004728759403200408
[4] International Tourism and Outbreak of Coronavirus (COVID-19): A Cross-Country Analysis
Farzanegan, Mohammad Reza
Gholipour, Hassan F.
Feizi, Mehdi
Nunkoo, Robin
Andargoli, Amir Eslami
[J]. JOURNAL OF TRAVEL RESEARCH, 2021, 60 (03) : 687 - 692
[5] Fernandez-Casal R, 2019, TVREG TIME VARYING C
[6] France Diplomatie, 2020, CONS AUX VOYAG CONS
[7] Harvey Andrew C., 1990, Forecasting, structural time series models and the Kalman filter, DOI DOI 10.1017/CBO9781107049994
[8] Hyndman R., 2020, Forecast: Forecasting Functions for Time Series and Linear Models R Package Version 8.13
[9] Another look at measures of forecast accuracy
Hyndman, Rob J.
Koehler, Anne B.
[J]. INTERNATIONAL JOURNAL OF FORECASTING, 2006, 22 (04) : 679 - 688
[10] Automatic time series forecasting: The forecast package for R
Hyndman, Rob J.
Khandakar, Yeasmin
[J]. JOURNAL OF STATISTICAL SOFTWARE, 2008, 27 (03): : 1 - 22

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