Enhancing the Community Resilience with a Network Structuring Model

Abstract

Community resilience is a key index for describing the response of human habitat system against hazards. Enhancing the community resilience to flood disaster requires indicator identification and measurement system establishment, especially for flooding risk management. In this study, an advanced index framework for measuring community resilience to flood disaster is proposed integrating fuzzy Delphi method (FDM) and interpretative structural model (ISM). Based on the definition of community resilience, the indicators are classified into six dimensions, including environmental factors, social factors, economic factors, psychological factors, institutional factors, and information and communication factors. A simplified community resilience evaluation index system is established by using FDM, and the hierarchical network structure of the community resilience to flood disasters is confirmed, in which the direct influence indicators and the root influence indicators are analyzed. The proposed framework in this study contributes to the interdisciplinary understanding of community resilience to flooding disasters and building a more resilience community; it is also expected to be extended for risk reduction in other natural hazards.