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.
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

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.