{"title":"Tourism demand forecasting using short video information","authors":"Mingming Hu , Na Dong , Fang Hu","doi":"10.1016/j.annals.2024.103838","DOIUrl":null,"url":null,"abstract":"<div><p>Based on short video information, this study extracted two explanatory variables, popularity and publicity, to empirically forecast weekly tourism demand for a destination (Macao) and a tourist attraction (Mount Siguniang, China). Results indicated that 1) models integrating the popularity or publicity of short videos outperform models without these attributes in tourism demand forecasting; 2) compared with popularity, models featuring publicity from short videos can generate more accurate forecasts; 3) models combining publicity and popularity do not necessarily exceed the performance of models including only publicity; and 4) when models account for search queries as well as publicity, search queries help improve forecasting accuracy for tourist attractions (this positive impact does not apply to destinations).</p></div>","PeriodicalId":48452,"journal":{"name":"Annals of Tourism Research","volume":"109 ","pages":"Article 103838"},"PeriodicalIF":10.4000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Tourism Research","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0160738324001154","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
引用次数: 0
Abstract
Based on short video information, this study extracted two explanatory variables, popularity and publicity, to empirically forecast weekly tourism demand for a destination (Macao) and a tourist attraction (Mount Siguniang, China). Results indicated that 1) models integrating the popularity or publicity of short videos outperform models without these attributes in tourism demand forecasting; 2) compared with popularity, models featuring publicity from short videos can generate more accurate forecasts; 3) models combining publicity and popularity do not necessarily exceed the performance of models including only publicity; and 4) when models account for search queries as well as publicity, search queries help improve forecasting accuracy for tourist attractions (this positive impact does not apply to destinations).
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.
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