The impact of public health emergencies on hotel demand - Estimation from a new foresight perspective on the COVID-19.

He, Ling-Yang; Li, Hui; Bi, Jian-Wu; Yang, Jing-Jing; Zhou, Qing

He, Ling-Yang; Li, Hui; Bi, Jian-Wu; Yang, Jing-Jing; Zhou, Qing.

Afiliação

He LY; College of Tourism and Service Management, Nankai University, Tianjin 300350, China.
Li H; College of Tourism and Service Management, Nankai University, Tianjin 300350, China.
Bi JW; College of Tourism and Service Management, Nankai University, Tianjin 300350, China.
Yang JJ; Macao Institute for Tourism Studies, Colina de Mong-Há, Macau 999078, China.
Zhou Q; School of Management, Hangzhou Dianzi University, Hangzhou 310018, China.

Ann Tour Res ; 94: 103402, 2022 May.

Article em En | MEDLINE | ID: mdl-35431371

Palavras-chave

Complete ensemble empirical mode decomposition (CEEMD); Long short-term memory (LSTM); Prediction-based management; Support vector machine (SVM); Tourism demand forecasting

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Texto completo: 1 Temas: ECOS / Estado_mercado_regulacao Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Aspecto: Patient_preference Idioma: En Revista: Ann Tour Res Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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