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A synthesis of disaster resilience measurement methods and indices

Journal

INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
Volume 31, Issue -, Pages 844-855

Publisher

ELSEVIER
DOI: 10.1016/j.ijdrr.2018.07.015

Keywords

Disaster resilience measurement; Synthesis analysis; Resilience indices; Validation; Adaptation strategies

Funding

  1. Dynamics of Coupled Natural Human Systems (CNH) Program from the U.S. National Science Foundation [121211]
  2. NOAA-Louisiana Sea Grant [R/S-05-PD]
  3. Direct For Social, Behav & Economic Scie
  4. Division Of Behavioral and Cognitive Sci [1212112] Funding Source: National Science Foundation

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Disaster resilience has become an important societal goal which captures the attention of academics and decision makers from various disciplines and sectors. Developing tools or metrics for measuring and monitoring progress of resilience is a critical component that requires extensive research to achieve better understanding. However, different fields have different emphases and the knowledge gained from the various studies are scattered and fragmented. To provide an integration of the literature and reflect on the current state of resilience measurement, we conducted a synthesis analysis through a systematic review of 174 scholarly articles on disaster resilience measurement from 2005 to 2017. Using a review table designed for this study and content analysis, we extracted key information from each article on resilience definition, type of measurement method, resilience indicators used, and proposed adaptation strategies. Results indicate that 39.7% of the articles used qualitative methods for resilience measurement and 39.1% of the articles used quantitative methods. However, only 10.3% of all the 174 articles conducted empirical validation of their proposed resilience indices. The three most frequently suggested adaptation strategies were empowering local governments and leaders, raising community awareness, and enhancing community infrastructure and communication. These findings suggest that future research need to incorporate validation and inferential ability into resilience measurement. Extending from static resilience measurement to dynamic system modeling and bridging the disconnection between resilience scientific research and practical actions are also pressing needs.

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