| Publication type: | Conference paper |
| Type of review: | Peer review (abstract) |
| Title: | A quantitative social network analysis approach to mitigate the ripple effect in supply chain networks |
| Authors: | Doege, Patrick Scherrer, Maike |
| et. al: | No |
| Proceedings: | Proceedings of the 28th EurOMA Conference |
| Conference details: | EurOMA 2021 : Managing the “new normal”: the future of Operations and Supply Chain Management in unprecedented times, Berlin, Germany (online), 5-7 July 2021 |
| Issue Date: | 6-Jul-2021 |
| Publisher / Ed. Institution: | European Operations Management Association |
| Language: | English |
| Subjects: | Resilience; Ripple effect; Social network analysis |
| Subject (DDC): | 658.5: Production management |
| Abstract: | Supply 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. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/22782 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Sustainable Development (INE) |
| Appears in collections: | Publikationen School of Engineering |
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