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dc.contributor.advisorDresner, Martinen_US
dc.contributor.authorWang, Zuozhengen_US
dc.date.accessioned2016-09-07T05:34:59Z
dc.date.available2016-09-07T05:34:59Z
dc.date.issued2016en_US
dc.identifierhttps://doi.org/10.13016/M25R5P
dc.identifier.urihttp://hdl.handle.net/1903/18665
dc.description.abstractThis dissertation investigates customer behavior modeling in service outsourcing and revenue management in the service sector (i.e., airline and hotel industries). In particular, it focuses on a common theme of improving firms’ strategic decisions through the understanding of customer preferences. Decisions concerning degrees of outsourcing, such as firms’ capacity choices, are important to performance outcomes. These choices are especially important in high-customer-contact services (e.g., airline industry) because of the characteristics of services: simultaneity of consumption and production, and intangibility and perishability of the offering. Essay 1 estimates how outsourcing affects customer choices and market share in the airline industry, and consequently the revenue implications from outsourcing. However, outsourcing decisions are typically endogenous. A firm may choose whether to outsource or not based on what a firm expects to be the best outcome. Essay 2 contributes to the literature by proposing a structural model which could capture a firm’s profit-maximizing decision-making behavior in a market. This makes possible the prediction of consequences (i.e., performance outcomes) of future strategic moves. Another emerging area in service operations management is revenue management. Choice-based revenue systems incorporate discrete choice models into traditional revenue management algorithms. To successfully implement a choice-based revenue system, it is necessary to estimate customer preferences as a valid input to optimization algorithms. The third essay investigates how to estimate customer preferences when part of the market is consistently unobserved. This issue is especially prominent in choice-based revenue management systems. Normally a firm only has its own observed purchases, while those customers who purchase from competitors or do not make purchases are unobserved. Most current estimation procedures depend on unrealistic assumptions about customer arriving. This study proposes a new estimation methodology, which does not require any prior knowledge about the customer arrival process and allows for arbitrary demand distributions. Compared with previous methods, this model performs superior when the true demand is highly variable.en_US
dc.language.isoenen_US
dc.titleUNDERSTANDING CUSTOMER CHOICES IN SERVICE OUTSOURCING AND REVENUE MANAGEMENTen_US
dc.typeDissertationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentBusiness and Management: Logistics, Business & Public Policyen_US
dc.subject.pqcontrolledBusiness administrationen_US
dc.subject.pquncontrolledChoice-based samplingen_US
dc.subject.pquncontrolledCustomer choiceen_US
dc.subject.pquncontrolledEM methoden_US
dc.subject.pquncontrolledRevenue managementen_US
dc.subject.pquncontrolledService outsourcingen_US
dc.subject.pquncontrolledStructural modelen_US


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