{"title":"EXPRESS: The Heterogeneity of Hotel Demand Curves across Consumers and Contexts","authors":"Gabrielle Lin, Jason Li Chen, Haiyan Song","doi":"10.1177/10963480241271307","DOIUrl":null,"url":null,"abstract":"This study constructs hotel demand curves at the disaggregate level to uncover the heterogeneity of demand curves across consumers and during both normal periods and times of crisis, exemplified by the pandemic. The novel demand modeling technique fits nonlinear demand curves, parameterizes elasticity dynamics, and enables the comparison of demand curves by essential value. The demand curves for three hotel types in normal and pandemic situations are fitted and decomposed by consumers’ sociodemographics, preferences, and risk tolerance. A pandemic makes the demand curve for midscale [upscale] hotels more inelastic [elastic] and mitigates [amplifies] the influence of individual differences on the demand curve, whereas the demand curve for economy hotels is unaffected by the pandemic. The findings offer insights into the business operations of different hotels, including optimal pricing, customized marketing across consumer segments, and business strategies in case of a health crisis.","PeriodicalId":517387,"journal":{"name":"Journal of Hospitality & Tourism Research","volume":"360 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-30","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/10.1177/10963480241271307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study constructs hotel demand curves at the disaggregate level to uncover the heterogeneity of demand curves across consumers and during both normal periods and times of crisis, exemplified by the pandemic. The novel demand modeling technique fits nonlinear demand curves, parameterizes elasticity dynamics, and enables the comparison of demand curves by essential value. The demand curves for three hotel types in normal and pandemic situations are fitted and decomposed by consumers’ sociodemographics, preferences, and risk tolerance. A pandemic makes the demand curve for midscale [upscale] hotels more inelastic [elastic] and mitigates [amplifies] the influence of individual differences on the demand curve, whereas the demand curve for economy hotels is unaffected by the pandemic. The findings offer insights into the business operations of different hotels, including optimal pricing, customized marketing across consumer segments, and business strategies in case of a health crisis.