Performance Evaluation of Supply Chains by Bi-Level DEA

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dc.contributor.authorHosseinzadeh Lotfi, F.
dc.contributor.authorAllahviranloo, T.
dc.contributor.authorShafiee, M.
dc.contributor.authorSaleh, H.
dc.date.accessioned2024-05-19T14:34:15Z
dc.date.available2024-05-19T14:34:15Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractToday, supply chains have become one of the dominant paradigms in the field of business. Experts believe the competition between companies in the past decades has turned into a competition between chains in the present era. Thus, supply chain management (SCM) is one of the essential and critical points in business because proper supply chain management improves the activities of various components and levels of a supply chain to improve the overall situation of the supply chain system. One of the crucial tools in supply chain management is evaluating the performance of the supply chain and each component and comparing the performance of the supply chain under evaluation with other competitors. Therefore, the calculation of relative efficiency, cost, and profit efficiency are essential factors in examining the performance of supply chains. Although to calculate the relative efficiency of DMUs under evaluation, the use of DEA models seems to be suitable, using classic DEA models by considering the supply chain as a black box or, even more precisely, assessing all components of the chain as a network and using NDEA models is not the answer to all situations in the supply chain. For example, suppose the members in a supply chain do not have the same level of importance (leader–follower). In this case, another branch of DEA is called bi-level DEA, and generally, multi-level DEA is recommended. Although the leader–follower point of view is explained in Chap. 8, we will deal with this issue with a different approach in this chapter and describe the evaluation of supply chains using bi-level DEA. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.identifier.doi10.1007/978-3-031-28247-8_10
dc.identifier.endpage442en_US
dc.identifier.issn2197-6503
dc.identifier.scopus2-s2.0-85158089176en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage419en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-28247-8_10
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4444
dc.identifier.volume122en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofStudies in Big Dataen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectEfficiencyen_US
dc.subjectBlack Boxesen_US
dc.subjectDea Modelsen_US
dc.subjectLeader-Followeren_US
dc.subjectManagement Isen_US
dc.subjectPerformanceen_US
dc.subjectPerformances Evaluationen_US
dc.subjectRelative Costsen_US
dc.subjectRelative Efficiencyen_US
dc.subjectRelative Profiten_US
dc.subjectSupply Chain Systemsen_US
dc.subjectSupply Chain Managementen_US
dc.titlePerformance Evaluation of Supply Chains by Bi-Level DEAen_US
dc.typeBook Chapteren_US

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