ZHENG Li-qiao, NAN Jin-xuan, SONG Shao-hua, SHI Xian-liang
Journal of Beijing Jiaotong University（Social Sciences Edition）. 2025, 24(4): 74-88.
Against the complexity and uncertainty of supply chain procurement decisions in a dynamic risk environment， this paper constructs a multi-period， multi-objective mixed-integer programming model based on Markov chain theory to optimize the collaborative decision-making mechanism of supply chain resilience， sustainability， and cost-effectiveness. Through numerical simulation and sensitivity analysis， the study reveals the following findings： First， the Markov chain-based decision-making model can effectively depict the dynamic evolution characteristics of suppliers’ states， thus providing enterprises with scientific procurement decision-making tools； Second， there exist inherent conflicts between cost， service level， and environmental performance in supply chain procurement decisions， requiring enterprises to dynamically adjust the priority of objectives； Third， the multi-source procurement strategy significantly improves supply chain resilience， but it is necessary to balance the conflicts among multiple objectives； Finally， although the emergency procurement strategy can mitigate the risk of supply disruption， its costs and negative environmental impacts need to be incorporated into dynamic evaluation. Therefore， this study suggests that manufacturing enterprises can construct a multi-tiered and multi-supplier supply network， establish a rigorous supplier evaluation framework， and develop decision support tools to address the challenge of dynamic balance among multiple objectives in supply chain management.
