Dynamically examining emergency response network resilience: A case study of a typical earthquake in China

• Published in: Safety science 2025-04, Vol.184, p.106766, Article 106766
• Main Authors: Sun, Fei, Zhou, Jiawen, Hu, Shiyu, Zhang, Ruoyi, Xing, Huige
• Format: Article
• Language: English
• Subjects: Disaster response; Organizational network resilience; Resilience characteristics; Resilience engineering; Social network analysis; Time dynamics
• ISSN: 0925-7535
• DOI: 10.1016/j.ssci.2024.106766

•Establishing a dynamic analysis framework for ERN resilience from multi-dimensions.•ERN resilience is forward-adaptive, and evolution aligns with the resilience curve.•ERN resilience is notably correlated with organizational attributes and behaviors.•The characteristics and enhancing strategies are discussed from four resilience dimensions.•Helping to improve multi-subject governance building for earthquake disasters. The combination of multi-subject collaboration and organizational resilience strategies has recently become a significant research topic in disaster emergency response. Dynamically identifying emergency response network (ERN) resilience characteristics is essential for understanding multi-organizational collaboration and enhancing organizational response capabilities and efficiency. This study, from an integrated perspective of inherent resilience and adaptive resilience, proposed a dynamic analysis framework for ERN resilience. First, based on key resilience characteristics—adaptability, robustness, resourcefulness, and rapidity—an ERN resilience evaluation framework was constructed. The study then selected the 2022 Luding earthquake as a case study, dividing it into four periods and using social network analysis metrics to dynamically measure ERN resilience and its inherent organizational impact. The results showed that 1) earthquake ERN resilience exhibited dynamic adaptability and forward adaptability; 2) ERN resilience was significantly associated with organizational attributes and behaviors; and 3) ERN robustness was influenced by network cohesion and organizational distribution. Finally, recommendations were made to enhance disaster ERN resilience by optimizing organizational structure and responsibility allocation, improving emergency planning, and managing materials. This research provides a novel dynamic analytical framework for building disaster resilience and offers valuable insights into multi-stakeholder disaster governance for earthquake disaster resilience worldwide.