# A Review of Supply Chain Resilience: A Network Modeling Perspective
## 3 Current Status of Supply Chain Network Modeling Research
### Comment on Supply Chain Resilience Based on Network Modeling Methods  
In the study of supply chain resilience, the primary goal of modeling is to accurately simulate the dynamic behavior of supply chain networks and their task execution capabilities to address the growing demands of uncertain and complex environments. By focusing on the following three aspects, the integrated application of complex network theory and agent-based modeling methods can significantly enhance the effectiveness of supply chain modeling:  
1. Behavioral Modeling of Business Entities  
Supply chain networks are not merely simplistic structures of nodes and connections; instead, the nodes represent business entities with autonomous behaviors and decision-making capabilities. Businesses within the supply chain, such as suppliers, manufacturers, and distributors, function as intelligent agents with the ability to adjust and make decisions based on external environmental factors and internal objectives. Consequently, supply chain modeling must focus on these behavioral characteristics to accurately depict the dynamic performance of the supply chain. Agent-based modeling is particularly effective for simulating the independent decision-making behaviors and task execution processes within organizations. By defining the roles, objectives, and interaction mechanisms of businesses within the supply chain, ABM enables the realistic simulation of task execution within the supply chain. This is especially valuable for analyzing scenarios involving task allocation, inventory management, and resource distribution. ABM facilitates an in-depth exploration of decision-making logic and collaboration patterns under varying conditions, thereby enhancing the task-oriented nature and practical applicability of the model. 2. Information Network Modeling as a Key Factor  
The information network within a supply chain plays a critical role in facilitating information transmission, sharing, and decision-making support among businesses, serving as the core of the supply chain's coordination and responsiveness. Information network modeling must not only address the mechanisms and efficiency of information transmission but also encompass mechanisms for information sharing and coordination, as well as their impact on business decisions. Such an information network is more than a data transmission channel--it constitutes a decision-support and collaboration-oriented information flow system. Applying complex network modeling methods can effectively describe the structural features of supply chain information networks. These methods facilitate the analysis of information transmission pathways, topological structures, and the efficiency and reliability of information flow between business nodes. By employing complex network modeling, researchers can uncover the propagation mechanisms of information within supply chains and evaluate the importance of various nodes within the information network and their influence on supply chain collaboration. This approach is critical for optimizing information-sharing strategies and enhancing the collaborative and responsive capabilities of the supply chain. 3. Task Fulfillment as the Ultimate Objective  
The ultimate goal of supply chain network modeling is to support the efficient execution of supply chain tasks, particularly by ensuring rapid response and effective resource allocation in mission-critical scenarios. The task execution capabilities of a supply chain stem from the collaboration among its business nodes and the support provided by the information network. By embedding business behavior characteristics and information network structures into the model, it becomes possible to simulate the interactions andcoordination between different businesses during task execution, optimizing resource allocation and reducing the risks of supply disruptions. In summary, the two main approaches currently used in supply chain network modeling are agent-based modeling and complex network modeling.