# A Review of Supply Chain Resilience: A Network Modeling Perspective
## 5 Summary and Future Outlook
### Further Directions  
Exclusive reliance on complex network modeling to analyze supply chain networks presents several limitations. Although complex networks effectively uncover the network's topological structure and the relationships between nodes, they fail to fully capture the multi-layered, multi-tiered, and highly heterogeneous nature of supply chains. Moreover, they are inadequate in simulating the dynamic evolution of supply chains and the impact of external factors. In addition, complex network models often neglect the decision-making behaviors of stakeholders within the supply chain and the mechanisms underlying risk propagation, thereby hindering a comprehensive analysis of supply chain stability and emergency response. Consequently, sole dependence on complex network modeling is insufficient to represent the full complexity of supply chains. It must be complemented by other modeling techniques for a more holistic analysis. This study provides a systematic review of supply chain resilience from the network modeling perspective. This study conducts a comprehensive literature review and visual analysis to explore the theoretical foundations, research advancements, and both the applications and limitations of network modeling methods in examining supply chain resilience. The main conclusions and contributions of this paper are as follows:  
1. Theoretical Foundations and Concept Definition: The concept of supply chain resilience is clarified, and its developmental trajectory is reviewed. Supply chain resilience encompasses not only the system's ability to adapt to and absorb shocks but also its capability to recover to a normal state;
2. Research Progress and Network Modeling Applications: the importance of network modeling techniques in supply chain resilience research is highlighted, particularly in the areas of risk propagation, simulation of supply chain evolution, and dynamic behavior analysis of individual entities;
3. Methodological Advantages and Limitations: This paper examines the methods of supply chain network modeling based on complex networks and agent-basedmodeling, analyzing their strengths and limitations. While complex network models are suited for macro-level analyses, agent-based models focus on micro-level dynamic behavior simulations;
4. The application of interdisciplinary methods in supply chain resilience research remains at an early stage. Future research can focus on the following directions [88; 89; 90]:
* Enhanced Representation of Individual Firm Behavior: as the complexity of supply chain networks increases, accurately depicting firm-level behaviors will become a critical research direction;
* Dynamic Analysis of Information Networks: The role of information networks in supply chains extends beyond information transmission. They also serve as critical enablers for decision-making and collaboration;
* Task-Oriented Model Design: in dynamic and highly uncertain environments, task-driven supply chain modeling, particularly for managing emergencies and ensuring the fulfillment of urgent demands, will be a key area of focus. This study offers new perspectives and methods for researching supply chain resilience, providing theoretical support and guidance for supply chain management practices. By adopting network modeling approaches it not only aims to help researchers design more resilient and sustainable supply chain networks capable of thriving in complex and uncertain environments but also highlights the multiplier effect of supply chain resilience. This research underscores how strengthening supply chain resilience can have far-reaching benefits, enhancing not only the operational stability of individual firms but also contributing to the economic stability and growth of nations.