Resilience analysis based on multi-layer network community detection of supply chain network
从网络分析角度，将复杂供应链投影为多层网络，用社区检测方法识别工厂和仓库的紧密集群，揭示生产能力的灵活性和冗余，帮助企业管理供应短缺或需求激增。
As the economic environment becomes increasingly complex, enhancing supply chain resilience is crucial for the operations and long-term development of enterprises. Real-world supply chains, encompassing components such as goods, warehouses, and plants, often contain complex network structures, making resilience analysis a challenging task. This paper addresses this challenge from a network analysis perspective. We project the complex supply chain network into single-mode, multi-layer networks focusing on plants and warehouses. Utilizing a multi-layer community detection method, we identify local clusters within these networks. By uncovering closely connected clusters, we reveal the flexibility and redundancy in production capabilities among different plants and warehouses. An empirical study using real-world data demonstrates that multi-layer network clustering effectively uncovers indirect capacity linkages between plants and warehouses. The findings from this community detection are beneficial for strategic capacity management, aiding enterprises in managing supply shortages or sudden demand spikes.