<p>In this study, the structural dynamics of emergency response networks during two major natural disasters in China are explored: earthquakes and floods. Using exponential random graph models (ERGMs), we find that flood response networks are more cohesive due to their predictability, whereas earthquake response networks prioritize rapid, direct inter-organizational ties for swift mobilization. The shift from the response phase to the recovery phase reveals a move toward open, collaborative relationships, highlighting the adaptability of disaster management networks. Additionally, network robustness is critical for maintaining efficiency during disruptions. These findings offer practical insights for tailoring emergency response strategies to disaster-specific needs and fostering adaptive, resilient collaboration frameworks. By understanding how different types of disasters necessitate distinct collaborative structures, emergency managers can develop robust strategies that leverage the strengths of specific network configurations to enhance overall disaster response effectiveness. Ultimately, our research contributes to both theoretical understanding and practical applications in emergency management, emphasizing the importance of adaptive network strategies for improving resilience and operational outcomes during crises.</p>

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Structural dynamics of emergency networks: comparative analysis of earthquake and flood disasters

  • Rui Cheng,
  • Zebin Zhao

摘要

In this study, the structural dynamics of emergency response networks during two major natural disasters in China are explored: earthquakes and floods. Using exponential random graph models (ERGMs), we find that flood response networks are more cohesive due to their predictability, whereas earthquake response networks prioritize rapid, direct inter-organizational ties for swift mobilization. The shift from the response phase to the recovery phase reveals a move toward open, collaborative relationships, highlighting the adaptability of disaster management networks. Additionally, network robustness is critical for maintaining efficiency during disruptions. These findings offer practical insights for tailoring emergency response strategies to disaster-specific needs and fostering adaptive, resilient collaboration frameworks. By understanding how different types of disasters necessitate distinct collaborative structures, emergency managers can develop robust strategies that leverage the strengths of specific network configurations to enhance overall disaster response effectiveness. Ultimately, our research contributes to both theoretical understanding and practical applications in emergency management, emphasizing the importance of adaptive network strategies for improving resilience and operational outcomes during crises.