A network-of-networks adaptation for cross-industry manufacturing repurposing

During a crisis, manufacturing processes in supply chains of different industries may network with each other as an adaptation response. We propose and examine a “network-of-networks” mechanism of such a cross-industry adaptation to learn about the value of reducing uncertainty through collaborative...

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Veröffentlicht in:IIE transactions 2024-06, Vol.56 (6), p.666-682
Hauptverfasser: Dolgui, Alexandre, Gusikhin, Oleg, Ivanov, Dmitry, Li, Xingyu, Stecke, Kathryn
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Sprache:eng
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Zusammenfassung:During a crisis, manufacturing processes in supply chains of different industries may network with each other as an adaptation response. We propose and examine a “network-of-networks” mechanism of such a cross-industry adaptation to learn about the value of reducing uncertainty through collaborative crisis preparedness and response during the COVID-19 pandemic. Our study allows revelation of the underlying trade-offs between the manufacturing capacity conversion time and effort required to adapt and the gains from collaborative preparedness to uncertainty. Through a real-life data-based analysis with the help of mathematical optimization, we connect the networks-of-networks coordination design and the outcomes of scenario modeling demonstrating a superiority of the coordinated capacity repurposing when compared to ad-hoc adaptation. We conclude that an appropriate collaboration of governmental agencies, healthcare, and industry is crucial for a prompt capacity conversion to healthcare production in a pandemic. Concrete implementation ways are visibility, healthcare inventory monitoring, technology backup plans, and repurposing contingency plans at the preparedness stage. At the response stage, a correct adaptation start time determines success. The results obtained can be instructive to develop technological and managerial plans for a cross-industry adaptation. The proposed “network-of-networks” perspective contributes to theory of supply chain viability and adaptation under disruptions using intertwined supply networks.
ISSN:2472-5854
2472-5862
DOI:10.1080/24725854.2023.2253881