 The impact of public health emergencies on hotel demand - Estimation from a new foresight perspective on the COVID-19Ling-Yang He, Hui Li, Jian-Wu Bi, Jing-Jing Yang and Qing Zhou Annals of Tourism Research, 2022, vol. 94, issue C Abstract: This paper proposes a new foresight approach to estimate the impact of public health emergencies on hotel demand. The forecasting-based influence evaluation consists of four modules: decomposing hotel demand before an emergency, matching each decomposed component to a forecasting model, combining the predictions as the expected demand after the emergency, and estimating the impact by comparing actual demand against that predicted. The method is applied to analyze the impact of COVID-19 on Macao's hotel industry. The empirical results show that: 1) the new approach accurately estimates COVID-19's impact on hotel demand; 2) the seasonal and industry development components contribute significantly to the estimate of expected demand; 3) COVID-19's impact is heterogeneous across hotel services. Keywords: Prediction-based management; Tourism demand forecasting; Long short-term memory (LSTM); Support vector machine (SVM); Complete ensemble empirical mode decomposition (CEEMD) (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:anture:v:94:y:2022:i:c:s0160738322000536 DOI: 10.1016/j.annals.2022.103402 Access Statistics for this article Annals of Tourism Research is currently edited by John Tribe More articles in Annals of Tourism Research from Elsevier |
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