Abstract:

Affected by the epidemic， the global supply chain network has been severely impacted by supply chain disruptions， forcing many enterprises to suspend production， resulting in serious economic losses. Notably， even in the face of uncertainties such as disruptions， supply chain sustainability is still valued. This is because it has become inevitable to build a supply chain network that focuses on environmental performance under the “carbon peaking and carbon neutrality” target. Therefore， it is necessary to adopt corresponding response strategies to scientifically design the supply chain network structure and ensure the multi-dimensional dynamic performance of the supply chain network. However， existing studies have not explored supply chain network performance along three dimensions： economic， reliability， and sustainability of the supply chain. And the supply chain network structure with multi-level matching relationship formed by multiple suppliers， manufacturers， etc. is more realistic， which has been paid less attention to. In addition， dealing with disruption risk based on probability theory requires giving the probability distribution of disruptions， and the history data of supply chain disruption are very scarce， so using uncertainty theory to address subjective uncertainty can effectively improve the scientificity and credibility of quantifying disruption risk when historical data are scarce. The supply chain network is in a dynamic uncertain environment， affected by various linear， nonlinear， quantitative and qualitative factors， and the supply chain network itself is also a complex system in which factors and links interact with each other. The system dynamic （SD） approach can address nonlinear and time-sensitive behaviors in a realistic and relatively intuitive way by capturing the causal relationships between relevant factors and their corresponding behaviors， combining quantitative and qualitative aspects. Therefore， it is of great significance to investigate the supply chain network performance based on a multi-level backup strategy in a dynamic and uncertain environment using SD approach in terms of three dimensions： economic， environment and reliability.For this purpose， uncertainty theory is used to quantify and analyze supply chain disruption risk in response to the low frequency and the difficulty of obtaining data of supply and transportation disruptions. And a multi-level backup strategy is used to cope with disruption risks， and the SD model for supply chain network performance analysis is constructed based on the formed supply chain network with multi-subject and multi-level matching relationships. The metrics for evaluating supply chain network performance are extended to three dimensions： economic， environment， and reliability， to analyze the supply chain network performance based on the multi-level backup strategy in a dynamic and uncertain environment. The results show that： （1） Although the multi-level backup strategy may lead to lower profit in the initial stage of supply chain operation， it can effectively mitigate the adverse effects of disruptions on the supply chain network in the long run. Therefore， the decision of the optimal backup level should be combined with the supply chain network operation time， integrating long-term development with short-term adjustment. （2） As the belief degree of disruption increases， the profit will decrease and the supply chain risk will increase， and the larger the belief degree of disruption， the longer the supply chain network operates， and the more significant the effect of adopting multi-level backup strategy. Therefore， the higher the possibility of disruptions in the long-term， the more important it is for decision-makers to plan for “chain preparedness” and optimize the supply chain network structure in order to adapt quickly in the event of external shocks. （3） When belief degree of disruption is large， supply disruption leads to a more significant decrease in profit compared to transportation disruption if the multi-level backup strategy is not adopted. Therefore， to achieve the stability of the supply chain， the reliability of suppliers should be focused on when selecting them， and the mutual cooperation of the supply chain should be strengthened to diversify the risks. （4） The reduced stability of demand results in fluctuations in the supply chain network performance in different directions in terms of economic， environment and reliability dimensions. Therefore， decision makers should weigh the factors they care about and shift from the previous pursuit of profit optimization to a continuous shift in balancing supply chain reliability， economic efficiency and environmental benefits to shape core competitiveness. This provides a basis for optimizing the supply chain network structure and selecting supplier， and gives theoretical support for achieving low-carbon and robust development of the supply chain network.

Key words: supply chain network performance, multi-level backup strategy, system dynamic model, uncertainty theory