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dc.contributor.advisorWilliam C. Wheaton.en_US
dc.contributor.authorYu, Jing, S.M. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.en_US
dc.date.accessioned2015-07-31T19:07:49Z
dc.date.available2015-07-31T19:07:49Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/97956
dc.descriptionThesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2015.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 54).en_US
dc.description.abstractIn early 2010, the hotel industry began a historic demand recovery. Across hotel sectors, demand growth pushed rooms occupied above the previous year's figure by more than 10% - almost doubling peak quarterly year-over-year growth. The hotel industry has recovered ahead of the economy for the first time in U.S. history, which is unusual considering the lodging industry has run in sync with all major economic trends in the past. GDP, which traditionally correlates strongly with hotel demand growth, has failed to capture the recovery's magnitude in recent years. International tourism, an economic indicator that saw a significant surge in 2010, was suggested to be one of the probable causes. The objective of this thesis is to identify external economic factors besides GDP that have meaningful impacts on lodging demand. Instead of analyzing the lodging industry as a whole, this thesis zooms into MSA level, compares rooms sold per capita among 54 MSAs throughout the United States, and tries to figure out between market differences and within market variations. The full-service hotel analysis and limited-service hotel analysis chapters use panel data model and four estimators to derive the most appropriate regression model for each hotel sector. The author examined the correlation and significance of each independent variable to identify meaningful demand drivers at overall, between, and within MSA level. The results show evidence that convention space, domestic enplanement, and international enplanement are all important economic factors for full-service hotels. However, none of them manage to deliver a meaningful explanation on the demand growth in limited-service sector. The economic development impact chapter access the economic impact to full-service demand from convention space addition, domestic airport expansion, international airport expansion, and conversion between domestic and international terminals. The author also tracked full-service lodging demand growth with enplanement growth for each of the 54 MSAs and combined their regression results together for advanced analysis. The thesis findings reveal that top-tier MSAs and large air transportation hubs have strong correlation between enplanement and full-service lodging demand. Further, the thesis delves deep into potential economic factors that may improve limited-service model.en_US
dc.description.statementofresponsibilityby Jing Yu.en_US
dc.format.extent68 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCenter for Real Estate. Program in Real Estate Development.en_US
dc.titleWhat makes a good hotel market? : a panel based approach to examine lodging demand driversen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Real Estate Developmenten_US
dc.contributor.departmentMassachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Center for Real Estate
dc.identifier.oclc913872022en_US


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