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dc.contributor.advisorStephen Graves and Stanley Gershwin.en_US
dc.contributor.authorCharles, Jordan Danielen_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.coverage.spatialn-us-ny n-us-ca n-us-ilen_US
dc.date.accessioned2017-09-15T15:36:05Z
dc.date.available2017-09-15T15:36:05Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/111481
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017.en_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 95).en_US
dc.description.abstractDigital retailers are currently experiencing explosive growth and mounting pressure from consumers to provide faster and cheaper delivery of product. This project develops two strategies to improve delivery speed, reliability, and cost for digital retailers operating in key North American markets (i.e. New York City, Los Angeles, and Chicago). Zone Skipping Transportation This project develops a zone skipping transportation model and associated business case for retailers with multiple consumer channels (i.e. digital and brick and mortar). Zone skipping pools digital and retail shipments, utilizing dedicated ground transportation of product from central distribution hubs to last-mile delivery hubs in key cities. For reasonable input parameters, zone skipping is shown to improve delivery speed by 20%, improve on-time delivery performance by 20%, and reduce costs by 10% over traditional carrier zone shipping. Multinodal Distribution (Ship-from-Store Simulation) Many multi-channel retailers employ multinodal distribution networks, but desire store fulfillment capabilities in key cities to improve key delivery metrics (speed and cost). To validate these capabilities, retailers can develop easily-tailorable analytical simulation models to test various hypotheses and distribution parameters. This project helps address two major ship-from-store questions: 1. What to Ship - A SKU stocking strategy that minimizes variability and ensures predictable and right-sized demand levels. The strategy needs to accurately predict future demand based on limited historical information. 2. How to Fulfill - The transformation of a store back room into a mini distribution center and all of the processes design to enable rapid fulfillment time given highly variable demand The SKU stocking strategy leverages advanced analytics, and the operational fulfillment processes are tested using simulation software that enables rapid manipulation of key variables to uncover optimal process flows. The resulting simulation model and SKU stocking framework can be leveraged by digital retailers to operationalize ship from store processes and accurately predict digital demand levels for future store fulfillment nodes.en_US
dc.description.statementofresponsibilityby Jordan Daniel Charles.en_US
dc.format.extent95 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleImproving multi-channel retail delivery performance in key market citiesen_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentLeaders for Global Operations Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentSloan School of Management
dc.identifier.oclc1003322292en_US


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