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Logistic regression for a better matching of buyers and suppliers in e-procurement

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dc.contributor.advisor Stephen C. Graves. en_US
dc.contributor.author Tian, Shuo, S.M. Massachusetts Institute of Technology en_US
dc.contributor.other Massachusetts Institute of Technology. Computation for Design and Optimization Program. en_US
dc.date.accessioned 2011-03-24T20:23:53Z
dc.date.available 2011-03-24T20:23:53Z
dc.date.copyright 2010 en_US
dc.date.issued 2010 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/61901
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2010. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 57-58). en_US
dc.description.abstract The thesis aims to provide a way to identify better matches between buyers and suppliers who are using an e-procurement platform provided by a US based worldwide online market company. The goal is to enhance the shopping experience of the clients, increase the retention rate and grow the customer base of the company. We establish two logistic regression models. The first model is to predict the probability of suppliers winning an RFQ (request for quote). From the calculated probabilities, we are able to rank all the suppliers and tell the buyers who may be the most qualified providers for them. Also, the suppliers will be aware of their odds of winning among all the competitors. Our model shows that price is the most decisive factor for winning, and geography and prior business relationships with the buyer are also important. The second model is used to estimate the probability of successfully awarding an RFQ. We model how likely the RFQ is to be awarded by the buyer. Such information will be especially helpful to suppliers. The process of the RFQ and the relation and intention of the buyer seem to be the most influential factors. en_US
dc.description.statementofresponsibility by Shuo Tian. en_US
dc.format.extent 64 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.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.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Computation for Design and Optimization Program. en_US
dc.title Logistic regression for a better matching of buyers and suppliers in e-procurement en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Computation for Design and Optimization Program. en_US
dc.identifier.oclc 706825540 en_US


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