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dc.contributor.authorSimchi-Levi, David
dc.contributor.authorSchmidt, William
dc.contributor.authorCombs, Keith
dc.contributor.authorGe, Yao
dc.contributor.authorGusikhin, Oleg
dc.contributor.authorSanders, Michael
dc.contributor.authorZhang, Don
dc.contributor.authorZhang, Yun
dc.contributor.authorWei, Yehua, Ph. D. Massachusetts Institute of Technology
dc.date.accessioned2016-03-24T23:41:10Z
dc.date.available2016-03-24T23:41:10Z
dc.date.issued2015-10
dc.identifier.issn0092-2102
dc.identifier.issn1526-551X
dc.identifier.urihttp://hdl.handle.net/1721.1/101782
dc.description.abstractFirms are exposed to a variety of low-probability, high-impact risks that can disrupt their operations and supply chains. These risks are difficult to predict and quantify; therefore, they are difficult to manage. As a result, managers may suboptimally deploy countermeasures, leaving their firms exposed to some risks, while wasting resources to mitigate other risks that would not cause significant damage. In a three-year research engagement with Ford Motor Company, we addressed this practical need by developing a novel risk-exposure model that assesses the impact of a disruption originating anywhere in a firm’s supply chain. Our approach defers the need for a company to estimate the probability associated with any specific disruption risk until after it has learned the effect such a disruption will have on its operations. As a result, the company can make more informed decisions about where to focus its limited risk-management resources. We demonstrate how Ford applied this model to identify previously unrecognized risk exposures, evaluate predisruption risk-mitigation actions, and develop optimal postdisruption contingency plans, including circumstances in which the duration of the disruption is unknown.en_US
dc.description.sponsorshipFord-MIT Allianceen_US
dc.language.isoen_US
dc.publisherInstitute for Operations Research and the Management Sciences (INFORMS)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1287/inte.2015.0804en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceProf. Simchi-Levi via Anne Grahamen_US
dc.titleIdentifying Risks and Mitigating Disruptions in the Automotive Supply Chainen_US
dc.typeArticleen_US
dc.identifier.citationSimchi-Levi, David, William Schmidt, Yehua Wei, Peter Yun Zhang, Keith Combs, Yao Ge, Oleg Gusikhin, Michael Sanders, and Don Zhang. “Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain.” Interfaces 45, no. 5 (October 2015): 375–390.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Societyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Divisionen_US
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Centeren_US
dc.contributor.approverSimchi-Levi, Daviden_US
dc.contributor.mitauthorSimchi-Levi, Daviden_US
dc.contributor.mitauthorZhang, Yunen_US
dc.relation.journalInterfacesen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsSimchi-Levi, David; Schmidt, William; Wei, Yehua; Zhang, Peter Yun; Combs, Keith; Ge, Yao; Gusikhin, Oleg; Sanders, Michael; Zhang, Donen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-4650-1519
mit.licenseOPEN_ACCESS_POLICYen_US


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