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dc.contributor.advisorDeaton, John E.
dc.contributor.authorMehta, Rian
dc.date.accessioned2017-10-02T15:36:40Z
dc.date.available2017-10-02T15:36:40Z
dc.date.created2017-12
dc.date.issued2017-09
dc.date.submittedDecember 2017
dc.identifier.urihttp://hdl.handle.net/11141/1662
dc.descriptionThesis (Ph.D.) - Florida Institute of Technology, 2017.en_US
dc.description.abstractThe purpose of the study was to identify factors that influence a commercial airline passenger’s preference between low-cost and legacy airline carriers. In turn a prediction model of passenger preference was created for American travelers. The study utilized a correlational design with linear multiple regression analyses as the statistical analyses to build the prediction model.The study was conducted in two stages utilizing two independent samples totaling 936 participants (379 females), all from the United States. Data from the first sample was used to create the regression equation for passenger preference. Data from the second sample was used to test the regression equation and thereby validate the prediction model. Each stage conducted backward stepwise regression analyses on the independent samples using the same instrument. Nine factors were selected to be tested to determine whether they had a significant influence on passenger preference between airline types. These nine factors were age, gender, income, education level, seat type, type of travel, frequency of travel, category of frequent flier program, and risk-taking tendencies. The results of this study suggested that frequency of travel, income, seat type, and education level significantly predict an American passenger’s preference between low cost and legacy carriers. Despite certain limitations, the study has several practical benefits specifically for the commercial airline industry and provides a foundation for future research in this field.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.rightsCopyright held by author.en_US
dc.titleA Prediction Model of Airline Passenger Preference: Identifying factors that predict passenger preference between low cost and legacy carriers.en_US
dc.typeDissertationen_US
dc.date.updated2017-10-02T15:03:05Z
thesis.degree.nameDoctor of Philosophy in Aviation Sciencesen_US
thesis.degree.levelDoctoralen_US
thesis.degree.disciplineAviation Sciencesen_US
thesis.degree.departmentAeronauticsen_US
thesis.degree.grantorFlorida Institute of Technologyen_US
dc.type.materialtext


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