dc.contributor.author |
Dharmadasa, KHK |
|
dc.contributor.author |
Kulatunga, U |
|
dc.contributor.author |
Thayaparan, M |
|
dc.contributor.author |
Keraminiyage, KP |
|
dc.contributor.editor |
Sandanayake, YG |
|
dc.contributor.editor |
Waidyasekara, KGAS |
|
dc.contributor.editor |
Ranadewa, KATO |
|
dc.contributor.editor |
Chandanie, H |
|
dc.date.accessioned |
2024-09-02T08:52:46Z |
|
dc.date.available |
2024-09-02T08:52:46Z |
|
dc.date.issued |
2024 |
|
dc.identifier.citation |
Dharmadasa, K.H.K., Kulatunga, U., Thayaparan, M., & Keraminiyage, K.P. (2024). Assessment of community disaster resilience in Sri Lanka: methodological approach in developing an index. In Y.G. Sandanayake, K.G.A.S. Waidyasekara, K.A.T.O. Ranadewa, & H. Chandanie (Eds.), World Construction Symposium – 2024 : 12th World Construction Symposium (pp. 227-239). Department of Building Economics, University of Moratuwa. https://doi.org/10.31705/WCS.2024.18 |
|
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/22781 |
|
dc.description.abstract |
Disasters threaten communities, causing immense damage to life, property, and overall well-being. In recent years, the frequency and impact of disasters have increased, highlighting the urgent need for enhancing Community Disaster Resilience (CDR). CDR refers to a community's ability to effectively anticipate, respond to, and recover from disasters. This research presents the proposed methodology to develop an index to measure community resilience to disasters in Sri Lanka. Based on the previous studies on resilience, a Systematic Literature Review (SLR) was conducted to identify all possible proxy indicators of CDR across economic, social, institutional, physical, environmental, and human health dimensions. The primary data collection and analysis will be conducted using a systematic approach called Q-methodology. As the SLR results generated too many items in the first instance, a pilot study will be undertaken to reduce the number and to identify the most relevant indicators (Q-set) for measuring CDR in Sri Lanka. This Q-set data will be ranked based on how much each expert in the field of disaster management, who will be selected through the snowball technique, would agree with each identified indicator (Q-sort). Then, Q-sort data is subjected to factor analysis to determine the inter-correlation between the results of Q-sorting. The qualitative data gathered during Q-sorting is expected to be analysed using thematic analysis. Finally, the index will be constructed by deriving the weightage of each indicator based on the Q-sorting results. This paper provides an extensive illustration of the above methodology. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Department of Building Economics |
en_US |
dc.subject |
Community Disaster Resilience (CDR) |
en_US |
dc.subject |
Methodology |
en_US |
dc.subject |
Index |
en_US |
dc.subject |
Indicators |
en_US |
dc.title |
Assessment of community disaster resilience in Sri Lanka: methodological approach in developing an index |
en_US |
dc.type |
Conference-Full-text |
en_US |
dc.identifier.faculty |
Architecture |
en_US |
dc.identifier.department |
Department of Building Economics |
en_US |
dc.identifier.year |
2024 |
en_US |
dc.identifier.conference |
World Construction Symposium - 2024 |
en_US |
dc.identifier.place |
Colombo |
en_US |
dc.identifier.pgnos |
pp. 227-239. |
en_US |
dc.identifier.proceeding |
12th World Construction Symposium - 2024 |
en_US |
dc.identifier.email |
hasangakeshan5@gmail.com |
en_US |
dc.identifier.email |
ukulatunga@uom.lk |
en_US |
dc.identifier.email |
mthayaparan@uom.lk |
en_US |
dc.identifier.email |
k.p.keraminiyage@salford.ac.uk |
en_US |
dc.identifier.doi |
https://doi.org/10.31705/WCS.2024.18 |
en_US |