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dc.contributor.authorChauhan, Vinod Kumaren_AU
dc.contributor.authorPerera, Supunen_AU
dc.contributor.authorBrintrup, Alexandraen_AU
dc.date.accessioned2020-11-17
dc.date.available2020-11-17
dc.date.issued2020en_AU
dc.identifier.urihttps://hdl.handle.net/2123/23804
dc.description.abstractSupply networks (SNs) play a vital role in fuelling trade and economic growth. Due to their interconnectedness, firm-level disruptions can cause perturbations to ripple through SNs, magnifying initial impact. Contemporary research on ripple effects focussed on understanding various structural features of SNs to predict and control disruption propagation. Our work adds to this body of knowledge by analysing an intriguing topological property that emerges in SNs: �nestedness�, which is defined as a pattern of organisation where products that are supplied by specialist suppliers are a subset of products that are supplied by generalist suppliers. In other words, generalists are also specialists. While previous research examined the emergence of nestedness and its possible reasons, its relationship to SN resilience remained unknown. Here, we develop a cascade model by bringing together the product-supplier-buyer structure; which provides us with fine-grained information on SN dependencies. We simulate disruptions in nested and non-nested organisations of the global automotive SN, and find that nested organisations are significantly more robust to random disruptions but vulnerable to hub disruptions under cascade conditions. However, nested structures are not as resilient; as they do not benefit from a response strategy where buyers seek alternative suppliers; because alternative suppliers do not exist. On the other hand, randomly connected SNs are vulnerable to cascades but can allow network reconfiguration.en_AU
dc.language.isoenen_AU
dc.subjectCOVID-19en_AU
dc.subjectCoronavirusen_AU
dc.titleThe relationship between nested patterns and the ripple effect in complex supply networksen_AU
dc.typeArticleen_AU
dc.identifier.doi10.1080/00207543.2020.1831096


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