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dc.contributor.advisorGeorgia Perakis.en_US
dc.contributor.authorLeung, Ngai-Hang Zacharyen_US
dc.contributor.otherMassachusetts Institute of Technology. Operations Research Center.en_US
dc.date.accessioned2015-01-05T20:07:06Z
dc.date.available2015-01-05T20:07:06Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/92698
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2014.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractThe thesis applies optimization theory to three problems in operations management. In the first part of the thesis, we investigate the impact of inventory control on the availability of drugs to patients at public health facilities in Zambia. We present consistent empirical data and simulation results showing that, because of its failure to properly anticipate seasonal variations in demand and supply lead-times, this system leads to predictable patient-level stock-outs even when there is ample inventory available in the central warehouse. Secondly, we propose an alternative inventory control system relying on mobile devices and mathematical optimization, and present results from a validated simulation model suggesting that its implementation would lead to a substantial improvement of patient access to drugs relative to the current system. In the second part of the thesis, we investigate the impact of returning customers on pricing for fashion Internet retailers. Our analysis of clickstream data from an online fashion retailer shows that a significant proportion of sales is due to returning customers, i.e. customers who first visit an item at a particular price, but purchase the item in a later visit at a lower price. We propose a markdown pricing model that explicitly incorporates returning customers. We propose a model for quantifying the value of the returning pricing model relative to a pricing model that does not distinguish between first-time and returning customers, and determine the value of returning pricing both exactly and through developing bounds. Based on real data from a fashion Internet retailer, we estimate the parameters of the returning demand model and determine the value of the returning pricing model. Lastly, we study the promotion optimization problem faced by grocery retailers, i.e. deciding which items to promote and at what price. Our formulation includes several business rules that arise in practice. We build demand models from data in order to capture the stockpiling behavior through dependence on past prices. This gives rise to a hard problem. For general additive and multiplicative demand structures, we propose efficient LP based methods, show theoretical performance guarantees and validate our results using real data.en_US
dc.description.statementofresponsibilityby Ngai-Hang Zachary Leung.en_US
dc.format.extent224 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.subjectOperations Research Center.en_US
dc.titleThree essays in operations managementen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center.en_US
dc.identifier.oclc898332895en_US


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