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Strong–weak collaborative management in coping supply chain disruption risk transmission based on scale-free networks

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  • Youyu Chen
  • Tong Shu
  • Shou Chen
  • Shouyang Wang
  • Kin Keung Lai
  • Lu Gan

Abstract

Supply chain disruption causes tremendous loss to supply chains and global businesses. Organizational structure and operational features of supply chain networks, therefore, constitute a major portion of research for coping with supply chain disruption risk. This article first discusses the theoretical foundation, analyses the strength theory of strong and weak ties and the collaborative theory of strong and weak ties. Also, research methods are explicated; the scale-free networks and the theory of strong ties are integrated; the features of supply chain networks are considered from single statistical parameters and comprehensive analyses. Next, we provide numeric simulation of the properties of supply chain networks, verifying the accuracy of parameter analyses of single statistics and comprehensive analyses. Ultimately, when coping with supply chain disruption risk, each node enterprise of supply chain network is supposed to deploy the characteristics of scale-free networks to systematically manage existing weak ties, weak ties newly introduced, existing strong ties and strong ties newly introduced. This study is conducive to node enterprises of supply chains to recognize and apply the scale-free networks and the strength theory of ties to analyze the properties of supply chain networks, and to improve the capacity to cope with disruption risk.

Suggested Citation

  • Youyu Chen & Tong Shu & Shou Chen & Shouyang Wang & Kin Keung Lai & Lu Gan, 2017. "Strong–weak collaborative management in coping supply chain disruption risk transmission based on scale-free networks," Applied Economics, Taylor & Francis Journals, vol. 49(39), pages 3943-3958, August.
  • Handle: RePEc:taf:applec:v:49:y:2017:i:39:p:3943-3958
    DOI: 10.1080/00036846.2016.1273494
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    Cited by:

    1. Li, Zhuyue & Zhao, Peixin & Han, Xue, 2022. "Agri-food supply chain network disruption propagation and recovery based on cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).

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