Abstract

The outbreak of COVID-19 has caused problems such as shortage of workforce, cost increase, cash flow tension, and uncertainty of supply chain. It has a specific negative impact on the raw material supply, procurement management, production resumption, logistics, and market of the supply chain, which can trigger cascading failures in supply chain networks. Aiming at the failure of upstream/downstream firms in supply chain networks due to the decreased product demand/material supply under the COVID-19, the present study adopted an underload cascading failure model for the supply chain networks. In this model, the hierarchical supply chain networks were constructed based on the Erdos Renyi (ER) model and Barabasi Albert (BA) model. The validity of the model was verified under random attack and target attack. In the random attack mode, the influences of model parameters were studied, and in the target attack mode, the influence of target protection and random protection measures on enhancing network invulnerability was also studied. Simulation results showed that the initial load and capacity lower bound of nodes impact cascading failure size. The former has a positive correlation with cascading failure size, while the latter negatively correlates with cascading failure size. Furthermore, random protection measures are more practical to prevent cascading failures.

Highlights

  • Introduction e ongoing COVID19 pandemic has posed severe disruptions on global supply chains [1, 2]

  • We propose an underload cascading failure model to investigate the negative outcomes of demand and supply declines caused by the ongoing COVID-19 pandemic. e extant supply chain network models are insufficient to explore the complicated and diverse characteristics among firms in the supply chain network

  • We try to capture the characteristics of the connections among the upstream and downstream firms. e numerical simulations present that the network efficiency is positively related to the firm loads, while the network efficiency is negatively related to the lower bound of production capacity. e simulation results show that the loads and lower bounds’ resilience will enhance the supply chain’s robustness when preventing the cascading failures during COVID-19

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Summary

The Cascading Failure Phenomena in Supply Chain Network

Each firm has its capacity, inventory, and demand for raw materials in the supply chain network. Any abnormality in the supply of automobile parts will affect the production; the suspension of some or some upstream suppliers will lead to the “chain break” crisis in the supply chain and cascade failure [25]. If the COVID-19 situation worsens, the spare parts firms and material firms in these countries and regions stop production and supply; the domestic firms will be unable to continue production after the stock is used up. E production of Chinese automobiles and spare parts will face a direct impact, which directly affects the regular operation of the whole automotive supply chain network. Yu et al studied the complexity and vulnerability of the supply chain network structure under the modern production mode and proposed an analysis method based on the weighted improved node contraction method [27]. Wang and Xiao studied the cascading failure in the cluster supply network and proposed a resilience method to cascading failures in the cluster supply chain network by leveraging the social resilience of ant colonies [37, 38]. e sections will employ an underload cascading failure model to investigate the COVID-19 disruption in supply chain networks

The Underload Cascading Failure Model
The Cascading Failure Process
Simulation and Analysis
Conclusions and Discussion
Theoretical and Practical Implications

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