{"title":"旅游需求建模的跨学科方法:生活质量指标","authors":"Adiyukh Berbekova, A. Assaf, Muzaffer Uysal","doi":"10.1177/10963480241229238","DOIUrl":null,"url":null,"abstract":"Tourism demand modeling remains a critical issue in tourism research and practice. To date, demand studies have predominantly focused on economic variables to explain tourism demand. While this is well established, recent research demonstrates the importance of not limiting demand specification to economic variables only. This study proposes an interdisciplinary approach to tourism demand by incorporating the relative quality of life index into the demand specification. Using data from the United States and its 30 top source markets, the findings demonstrate that, in addition to traditional economic variables, a relative quality of life index that encompasses education, health, and stability is a significant predictor of tourism demand.","PeriodicalId":369021,"journal":{"name":"Journal of Hospitality & Tourism Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interdisciplinary Approach to Tourism Demand Modeling: Quality of Life Indicators\",\"authors\":\"Adiyukh Berbekova, A. Assaf, Muzaffer Uysal\",\"doi\":\"10.1177/10963480241229238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tourism demand modeling remains a critical issue in tourism research and practice. To date, demand studies have predominantly focused on economic variables to explain tourism demand. While this is well established, recent research demonstrates the importance of not limiting demand specification to economic variables only. This study proposes an interdisciplinary approach to tourism demand by incorporating the relative quality of life index into the demand specification. Using data from the United States and its 30 top source markets, the findings demonstrate that, in addition to traditional economic variables, a relative quality of life index that encompasses education, health, and stability is a significant predictor of tourism demand.\",\"PeriodicalId\":369021,\"journal\":{\"name\":\"Journal of Hospitality & Tourism Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hospitality & Tourism Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/10963480241229238\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hospitality & Tourism Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/10963480241229238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interdisciplinary Approach to Tourism Demand Modeling: Quality of Life Indicators
Tourism demand modeling remains a critical issue in tourism research and practice. To date, demand studies have predominantly focused on economic variables to explain tourism demand. While this is well established, recent research demonstrates the importance of not limiting demand specification to economic variables only. This study proposes an interdisciplinary approach to tourism demand by incorporating the relative quality of life index into the demand specification. Using data from the United States and its 30 top source markets, the findings demonstrate that, in addition to traditional economic variables, a relative quality of life index that encompasses education, health, and stability is a significant predictor of tourism demand.