Measuring community disaster resilience using Q-methods: a physical resilience perspective Article Swipe
Hisham Tariq
,
Chaminda Pathirage
,
Terrence Fernando
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1108/bepam-03-2020-0053
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1108/bepam-03-2020-0053
Purpose Decision-makers, practitioners and community members have a need to assess the disaster resilience of their communities and to understand their own capacities in disaster situations. There is a lack of consensus among researchers as to what resilience means and how it can be measured. This paper proposes a novel technique to achieve consensus among stakeholders on definitions, objectives and indicators for measuring a key dimension of community disaster resilience (CDR), physical infrastructure (PI). Design/methodology/approach This study uses a five-step approach utilizing Q-methods to contextualize a resilience index for PI. Interviews, focus groups and Q-sorting workshops were conducted to develop a tool that ranked measures according to stakeholder preference. A total of 84 participants took part in the workshops across four countries (United Kingdom, Malaysia, Pakistan and Sri Lanka). Findings The initial set of 317 measures was reduced to 128 and divided into the three community capacities of anticipatory, absorptive and restorative. The physical infrastructure capacity assessment tool (PI-CAT) was then finalized to have 38 indicators that were also ranked in order of importance by the participants. Practical implications The PI-CAT can be useful for local governments and communities to measure their own resilience. The tool allows stakeholders to be confident that the metrics being used are ones that are relevant, important and meet their requirements. Originality/value The Q-method approach helps stakeholders to develop and use a community capacity assessment tool that is appropriate for their context. The PI-CAT can be used to identify effective investments that will enhance CDR.
Related Topics
Concepts
Resilience (materials science)
Context (archaeology)
Stakeholder
Community resilience
Originality
Perspective (graphical)
Process management
Computer science
Psychology
Business
Political science
Geography
Public relations
Social psychology
Operating system
Creativity
Physics
Artificial intelligence
Redundancy (engineering)
Archaeology
Thermodynamics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1108/bepam-03-2020-0053
- OA Status
- green
- Cited By
- 9
- References
- 57
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3128509805
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3128509805Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1108/bepam-03-2020-0053Digital Object Identifier
- Title
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Measuring community disaster resilience using Q-methods: a physical resilience perspectiveWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-02-01Full publication date if available
- Authors
-
Hisham Tariq, Chaminda Pathirage, Terrence FernandoList of authors in order
- Landing page
-
https://doi.org/10.1108/bepam-03-2020-0053Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://hdl.handle.net/2436/623866Direct OA link when available
- Concepts
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Resilience (materials science), Context (archaeology), Stakeholder, Community resilience, Originality, Perspective (graphical), Process management, Computer science, Psychology, Business, Political science, Geography, Public relations, Social psychology, Operating system, Creativity, Physics, Artificial intelligence, Redundancy (engineering), Archaeology, ThermodynamicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2, 2022: 3, 2021: 2Per-year citation counts (last 5 years)
- References (count)
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57Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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