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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Goonetilleke, Ashantha | - |
| dc.date.accessioned | 2026-03-02T07:07:46Z | - |
| dc.date.available | 2026-03-02T07:07:46Z | - |
| dc.date.issued | 2021-01 | - |
| dc.identifier.uri | https://www.sciencedirect.com/science/article/abs/pii/S221242092031459X | - |
| dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/20757 | - |
| dc.description.abstract | The key challenge in social resilience assessment is to translate abstract and complex concepts to enable its measurement. Existing measures of social resilience indicators are problematic as these do not necessarily account for the multi-faceted and dynamic nature of the indicators. Therefore, innovative and reliable measurement approaches are required to improve the incorporation of social resilience measures in disaster management policy and practice. The adoption of a surrogate approach, which has received limited attention in a disaster management context, can help to overcome the conceptual challenges inherent in measuring such indicators by capturing key facets of the target indicator and facilitate robust social resilience measurement. This manuscript presents a set of potential surrogates for social resilience indicators identified in an exploratory research investigation. The data was collected using a case study approach utilising interviews with disaster practitioners and policy makers. The data analysis revealed six potential surrogates for each social resilience indicator. The identified potential surrogates provide a reliable measure of social resilience in policy and practice to devise appropriate strategies for enhancing social resilience by regularly monitoring and updating the resilience status using locally available administrative data. The potential surrogates identified to measure social resilience indicators can also be replicated with proper contextualisation in different geographic and hazard exposure settings. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Civil engineering | en_US |
| dc.subject | Social resilience measurement | en_US |
| dc.subject | Surrogate indicators | en_US |
| dc.subject | Disaster management policy | en_US |
| dc.subject | Resilience assessment methodology | en_US |
| dc.title | Assessing social resilience in disaster management | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Department of Civil Engineering | |
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