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Modeling supply chain viability and adaptation against underload cascading failure during the COVID-19 pandemic
Nonlinear Dynamics ; : 1-17, 2022.
Article in English | EuropePMC | ID: covidwho-1999028
ABSTRACT
Supply chain viability concerns the entire supply system rather than one company or one single chain to survive COVID-19 disruptions. Mobility restriction and overall demand decline lead to systematically cascading disruptions that are more severe and longer lasting than those caused by natural disasters and political conflicts. In the present study, the authors find that large companies and manufacturers with traditional advantages suffer greater losses than small ones, which is conceptualized as the “Hub Paradox” by empirically investigating one Warp Knitting Industrial Zone of China. An underload cascading failure model is employed to simulate supply chain viability under disruptions. Numerical simulations demonstrate that when the load decreases beyond a threshold, the viability will drop down critically. Besides, supply chain viability depends on two aspects the adaptive capability of the manufacturers themselves and the adaptive capability of the connections of the supply network. The comparison study demonstrates that enhancing cooperative relations between hub and non-hub manufacturers will facilitate the entire supply network viability. The present study sheds light on viable supply chain management. Compared with conventionally linear or resilient supply chains, intertwined supply networks can leverage viability with higher adaptation of redistributing production capacities among manufacturers to re-establish overall scale advantages. Finally, the present study also suggests solving the “Hub Paradox” from the perspective of complex adaptive system. Supplementary Information The online version contains supplementary material available at 10.1007/s11071-022-07741-8.
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Collection: Databases of international organizations Database: EuropePMC Language: English Journal: Nonlinear Dynamics Year: 2022 Document Type: Article

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Collection: Databases of international organizations Database: EuropePMC Language: English Journal: Nonlinear Dynamics Year: 2022 Document Type: Article