Research on Dynamic Analysis and Mitigation Strategies of Supply Chains under Different Disruption Risks

Due to the globalization of supply and production, supply chain management has tightened the connection between upstream and downstream enterprises. Although this modern strategy has significantly improved the efficiency of enterprises, the increasingly complex relationship between nodes also makes the supply chain system more vulnerable and unstable. As a result, the interruption of any node location in the supply chain will spread to other nodes via their diffusion, which could cause irreparable damage to the entire supply chain. Therefore, under this realistic background, only by quantitatively analyzing the specific impact on the supply chain of interruption events in different locations we can formulate active and effective mitigation strategies to achieve the effective recovery of node enterprises from interruption accidents. In this study, the system dynamics method was used to simulate the changes in inventory level, order accumulation, and profit level caused by disruption of supply, production, and sales of different node companies. The results show that the closer the node enterprise to the interruption source, the greater the risk of loss. Due to the conduction effect of the supply chain system, the risk spreads to other node enterprises. Based on the above results, corresponding mitigation strategies for enterprises to cope with different node interruptions are proposed to improve the overall efficiency and operational capabilities of the enterprise.

Automated summary

Due to the globalization of supply and production, supply chain management has strengthened the connection between upstream and downstream enterprises. However, the complex relationship between nodes makes the supply chain system more vulnerable, and interruption at any location can cause irreparable damage. Quantitative analysis of interruption events in different locations is essential for formulating effective mitigation strategies to achieve the recovery of node enterprises.