Qiu Richard T R, Wu Doris Chenguang, Dropsy Vincent, Petit Sylvain, Pratt Stephen, Ohe Yasuo
Department of Integrated Resort and Tourism Management, Faculty of Business Administration, University of Macau, Taipa, Macao, China.
Business School, Sun Yat-sen University, Guangzhou, China.
Ann Tour Res. 2021 May;88:103155. doi: 10.1016/j.annals.2021.103155. Epub 2021 Jan 28.
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.
在围绕新冠疫情的不确定性下,提供有关旅游业未来的科学评估非常重要。为此,本文提出了一个针对20个国家入境旅游需求的两阶段三情景预测框架。主要研究结果如下:在第一阶段事后预测中,堆叠模型更准确、更稳健,尤其是在结合五个单一模型时。第二阶段事前预测基于三种复苏情景:轻度情景假设呈V型复苏,中度情景呈V/U型,重度情景呈L型。预测结果显示,与2019年相比,2021年的复苏幅度范围很广(10%-70%)。这个两阶段三情景框架有助于提高旅游需求预测的准确性和稳健性。