Hanyuan Zhang , Ying Liu , Xinyang Liu , Anyu Liu , Vera Shanshan Lin
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引用次数: 0
Abstract
Forecast combinations became particularly significant in the post-pandemic era due to heightened uncertainty. This study introduces a Triple-layer Forecast Combination Framework to predict Chinese outbound tourism recovery from August 2023 to July 2024 across 20 destinations. The framework integrates baseline quantitative models, expert-based model selection, and real-time judgmental adjustments to enhance forecast accuracy in post-crisis contexts. Results show Chinese visitor arrivals rebounding, on average, to 80% of July 2019 levels by mid-2024, with East and Southeast Asia—particularly Hong Kong SAR, Macao SAR, and Thailand—recovering faster than long-haul markets such as Hawaii, Canada, and the Czech Republic. By combining statistical rigor with contextual insight, the framework supports replicable, adaptive forecasting under uncertainty for tourism recovery planning.
期刊介绍:
The Annals of Tourism Research is a scholarly journal that focuses on academic perspectives related to tourism. The journal defines tourism as a global economic activity that involves travel behavior, management and marketing activities of service industries catering to consumer demand, the effects of tourism on communities, and policy and governance at local, national, and international levels. While the journal aims to strike a balance between theory and application, its primary focus is on developing theoretical constructs that bridge the gap between business and the social and behavioral sciences. The disciplinary areas covered in the journal include, but are not limited to, service industries management, marketing science, consumer marketing, decision-making and behavior, business ethics, economics and forecasting, environment, geography and development, education and knowledge development, political science and administration, consumer-focused psychology, and anthropology and sociology.