An enhanced dynamic-network-based framework for quantifying and enhancing the resilience of disaster response networks to old communities under rainstorm waterlogging

Abstract

Developing effective disaster response networks (DRNs) is crucial for mitigating the impacts of rainstorm waterlogging in old communities. Aiming at providing implementable strategies for enhancing DRN resilience, this paper developed an enhanced dynamic network analysis (DNA)-based framework for DRNs utilizing the DNA and CRITIC-VIKOR method. This framework conceptualizes community disaster response as a three-stage ‘agent-information-resource-task’ (A-I-R-T) dynamic network, facilitating a comprehensive understanding of interactions among stakeholders, disaster information, emergency resources, and response tasks. Subsequently, a hybrid evaluation model combining CRITIC and VIKOR methods was established to quantify DRN resilience by assessing deviations from ideal response scenarios. Validated through a case study of the Y community in Xuzhou city of China, the findings reveal significant variations in stakeholder communication effectiveness across different stages of disaster response, with resilience peaking during the function recovery stage at 0.292. This study not only contributes to the body of knowledge in disaster management and resilience theory but also provides actionable strategies for enhancing DRN resilience, thereby contributing to more resilient urban environments.