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dc.contributor.authorDoege, Patrick-
dc.contributor.authorScherrer, Maike-
dc.date.accessioned2021-07-09T06:45:54Z-
dc.date.available2021-07-09T06:45:54Z-
dc.date.issued2021-07-06-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/22782-
dc.description.abstractSupply chain network disruptions have become an increasingly relevant topic in literature and industry. Just recently the COVID-19 pandemic demonstrated the need for greater resilience in global supply chain networks. We present a quantitative social network analysis (SNA) approach to selectively fortify nodes in complex supply chain networks targeting ripple-effect mitigation and enhancing supply chain network resilience (SCNR). Our model can be used to analyze supply chain resilience and derive strategies to mitigate disruptions, specifically using betweenness centrality for fortification. The model can be applied by supply chain managers to existing supply chain networks regardless of the underlying network type.de_CH
dc.language.isoende_CH
dc.publisherEuropean Operations Management Associationde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectResiliencede_CH
dc.subjectRipple effectde_CH
dc.subjectSocial network analysisde_CH
dc.subject.ddc658.5: Produktionssteuerungde_CH
dc.titleA quantitative social network analysis approach to mitigate the ripple effect in supply chain networksde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Nachhaltige Entwicklung (INE)de_CH
zhaw.conference.details28th International Annual EurOMA Conference, Berlin, Germany (online), 5-7 July 2021de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedingsProceedings of the 28th EurOMA Conferencede_CH
zhaw.webfeedIndustrie 4.0de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Doege, P., & Scherrer, M. (2021, July 6). A quantitative social network analysis approach to mitigate the ripple effect in supply chain networks. Proceedings of the 28th EurOMA Conference.
Doege, P. and Scherrer, M. (2021) ‘A quantitative social network analysis approach to mitigate the ripple effect in supply chain networks’, in Proceedings of the 28th EurOMA Conference. European Operations Management Association.
P. Doege and M. Scherrer, “A quantitative social network analysis approach to mitigate the ripple effect in supply chain networks,” in Proceedings of the 28th EurOMA Conference, Jul. 2021.
DOEGE, Patrick und Maike SCHERRER, 2021. A quantitative social network analysis approach to mitigate the ripple effect in supply chain networks. In: Proceedings of the 28th EurOMA Conference. Conference paper. European Operations Management Association. 6 Juli 2021
Doege, Patrick, and Maike Scherrer. 2021. “A Quantitative Social Network Analysis Approach to Mitigate the Ripple Effect in Supply Chain Networks.” Conference paper. In Proceedings of the 28th EurOMA Conference. European Operations Management Association.
Doege, Patrick, and Maike Scherrer. “A Quantitative Social Network Analysis Approach to Mitigate the Ripple Effect in Supply Chain Networks.” Proceedings of the 28th EurOMA Conference, European Operations Management Association, 2021.


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