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SURROGATE APPROACH TO ASSESS
SOCIAL RESILIENCE IN DISASTER
MANAGEMENT
Abdul Majeed Aslam Saja
Submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy
School of Built Environment
Science and Engineering Faculty
Queensland University of Technology
2020
Surrogate Approach to Assess Social Resilience in Disaster Management i
Keywords
Community Resilience; Disaster Resilience; Disaster Management; Disaster Risk
Reduction; Resilience Assessment; Resilience Measurement; Social Resilience;
Surrogate; Surrogate Framework.
Surrogate Approach to Assess Social Resilience in Disaster Management ii
Abstract
The resilience concept has been studied and applied across many disciplines such
as ecology, psychology, and engineering, in the past decades. While the adoption of
the resilience concept in disaster risk management goes back many years, it gained
wider attention among disaster management stakeholders with the adoption of the
Sendai Framework for Disaster Risk Reduction in 2015. Yet, there is no consensus
among different stakeholders as to how it can be measured effectively within the
practical limits of time and human or financial resources.
The importance of social resilience characteristics such as the role of social
support and networks has been highlighted in managing past disasters. New definitions
have evolved, which increasingly recognise the importance of both, social systems and
processes in the preparedness for a disaster. Understanding social resilience can assist
in the formulation of effective disaster management policies to help communities
better prepare for, respond to, and recover from disasters. However, the measurement
of social resilience indicators is not always practical or effective, due to conceptual
and methodological constraints. For example, existing measures of social resilience
indicators do not account for the multi-faceted and dynamic nature of indicators. Some
resilience frameworks also utilise direct measures of resilience, which is resource and
time intensive, and difficult to replicate over time. Hence, new approaches are needed
to measure resilience which optimises resources and within a shorter period of time,
while ensuring the adequacy and reliability of the resilience measurement.
The use of the surrogate approach can help to overcome these limitations by
identifying key facets of resilience indicators. Surrogates are used when a target
indicator is too complex and/or not feasible to measure directly. A surrogate is a
measure to effectively represent a target indicator that is intended to be measured,
based on a well-established relationship between the target indicator and the surrogate.
Further, a sound methodological approach to guide the use of surrogates has not been
investigated to-date in a disaster context, which makes this study innovative and
theoretically significant. To address this research gap, a surrogate development
framework was produced from the review of existent surrogate approach literature in
environmental science to assess social resilience in a disaster context. The surrogate
Surrogate Approach to Assess Social Resilience in Disaster Management iii
development framework was developed in three steps across three interrelated phases
as part of a mixed methods research strategy.
In the first step, five key social resilience indicators, which are very dynamic and
complex for direct measurement, were selected from the ‘5S’ social resilience
framework based on surrogate decision criteria identified in this study. The ‘5S’ is an
adaptive and inclusive framework that was developed in this study based on a critical
review of existing social resilience frameworks, by structuring social resilience in
terms of key dimensions, characteristics, and indicators to guide in selecting social
resilience indicators for surrogate approach. In the second step, key themes of the five
selected social resilience indicators were explored through a case study approach,
utilising interviews. Six potential surrogates were identified for each social resilience
indicator, their surrogacy relationship was established, and surrogate measurement
protocols were proposed. In the third and final step, the potential surrogates were
evaluated against five surrogate evaluation criteria by a wide range of disaster
management experts through an online survey. The survey results were then analysed
using a Multi-Criteria Decision Making technique to rank potential surrogates. By
synthesising the findings from the online survey, first ranked surrogates for social
resilience indicators were selected as priority surrogates for assessing social resilience
indicators.
The findings from this research make an important contribution to advance
resilience assessment in disaster management by applying an innovative approach to
conceptualise, identify, and select surrogates to assess social resilience indicators. The
integrated (revised) surrogate development framework tested in this research through
a robust multi-phase mixed method sequential research strategy sets a new way
forward for resilience assessment in disaster management research. Further, first
ranked surrogates and their measurement protocols for operationalisation, devised
from the research findings have wide practical applicability, largely in any urban
context. They will also guide policy makers and practitioners, particularly at the local
and sub-national levels, to overcome the existing challenges in resilience assessment
in a disaster context. Future research is needed to apply the integrated surrogate
development framework in different contexts, and operationalise the first ranked
surrogates using the proposed measurement protocols to further advance the social
resilience assessment research using surrogate approach.
Surrogate Approach to Assess Social Resilience in Disaster Management iv
Table of Contents
Keywords .................................................................................................................................. i
Abstract .................................................................................................................................... ii
List of Figures ......................................................................................................................... vi
List of Tables ........................................................................................................................ viii
List of Appendices .................................................................................................................. ix
Glossary of Terms .....................................................................................................................x
List of Abbreviations .............................................................................................................. xi
Statement of Original Authorship .......................................................................................... xii
Acknowledgements ............................................................................................................... xiii
List of publications ............................................................................................................... xiv
Chapter 1: Introduction ............................................................................................ 1
Background .....................................................................................................................1
Social resilience to disasters ...........................................................................................3
The potential use of surrogate approach in social resilience assessment ........................4
Research problem ...........................................................................................................5
Research Question, Aim, Objectives and Outputs ..........................................................6
Research significance and contributions.........................................................................7
Research scope ...............................................................................................................8
Thesis outline ..................................................................................................................9
Chapter 2: Literature Review ................................................................................. 12
Social resilience definitions in disaster management ...................................................13
A critical review of social resilience assessment frameworks in disaster
management ..................................................................................................................16
A ‘5S’ inclusive and adaptive social resilience framework in disaster management ...28
Summary and Implications ...........................................................................................32
Chapter 3: Surrogate approach to assess social resilience to disasters ............... 34
An overview of surrogate approach ..............................................................................35
A surrogate development framework for assessing social resilience to disasters.........47
Summary .......................................................................................................................61
Chapter 4: Research Method .................................................................................. 62
Philosophical position of research ................................................................................64
Research methods and strategies ..................................................................................67
Social resilience indicators selected for developing surrogates ....................................74
Research Ethical considerations ...................................................................................79
Surrogate Approach to Assess Social Resilience in Disaster Management v
Phase I – Qualitative case study research for identifying potential surrogates
(Interviews) ...................................................................................................................81
Phase II – Quantitative survey to evaluate and rank potential surrogates (Online
survey) ..........................................................................................................................97
Summary .....................................................................................................................114
Chapter 5: Interview analysis-Identification of potential surrogates ............... 115
Surrogate measures to assess social mobility and access to transport in a disaster
context (Indicator #1) .................................................................................................117
Surrogate measures to assess social trust in a disaster context (Indicator #2) ............133
Surrogate measures to assess learnings from the past disasters as social competence
(Indicator #3) ..............................................................................................................151
Surrogate measures to assess involvement of people with specific needs as social
equity in a disaster context (Indicator #4) ..................................................................168
Surrogate measures to assess cultural/behavioural norms as social beliefs in a disaster
context (Indicator #5) .................................................................................................185
Summary of potential surrogates and selection of set of surrogates for evaluation in
phase II .......................................................................................................................203
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 206
6.1. PROMETHEE Ranking and analysis of potential surrogates with equal criteria
weights ........................................................................................................................208
Calculation of surrogate evaluation criteria weight ....................................................220
Overall PROMETHEE ranking with weighted criteria ..............................................220
First ranked social resilience surrogate in disaster management ................................225
Summary of findings from the survey research ..........................................................227
Chapter 7: Synthesis of key findings .................................................................... 228
Key findings in relation to research objective one (RO1) ..........................................229
Key findings in relation to research objective two (RO2) ..........................................232
Key findings in relation to research objective three (RO3) ........................................240
Revisions to the conceptual surrogate development framework ................................247
Chapter 8: Conclusions and recommendations for future research ................. 252
Achievement of research objectives one to three .......................................................252
Addressing the key research question and aim ...........................................................255
Study contributions to knowledge and practice ..........................................................256
Study limitations .........................................................................................................258
Key recommendations for future research ..................................................................259
Bibliography ........................................................................................................... 260
Appendices .............................................................................................................. 277
Surrogate Approach to Assess Social Resilience in Disaster Management vi
List of Figures
Figure 1.1. Total reported economic losses per year, with major events highlighted 1998-2017 1
Figure 1.2. Thesis structure with key sections 11
Figure 2.1. Chapter 2 and key sections in the thesis structure 12
Figure 2.2. PRISMA Flow diagram used for selection of social resilience frameworks 17
Figure 2.3. Summary of the literature review highlighting knowledge gaps in social resilience 26
Figure 2.4. Three layer structure of the ‘5S’ social resilience framework 28
Figure 2.5. An inclusive and adaptive ’5S’model social resilience framework 29
Figure 3.1. Chapter 3 and key sections in the thesis structure 34
Figure 3.2. Graphical representation of surrogate approach models 37
Figure 3.3. Conceptual analogous surrogate model 38
Figure 3.4. Adaptive Surrogacy Framework 40
Figure 3.5. Vulnerability indicator development framework 42
Figure 3.6. Surrogate development framework to assess social resilience in a disaster context 48
Figure 3.7. Surrogate approach decision flowchart (Key step A) 50
Figure 3.8. A framework to identify potential surrogates (Key step B) 51
Figure 3.9. Steps to select optimum surrogates (Key step C) 56
Figure 3.10. Surrogate evaluation criteria pentagon 58
Figure 4.1. Chapter 4 and key sections in the thesis structure 65
Figure 4.2. Sequential design integrating qualitative and quantitative research methodologies 69
Figure 4.3. Overall research framework with key steps and processes 72
Figure 4.4. Expanded research framework in three phases 73
Figure 4.5. Extract from the overall research process for the literature review and research design 74
Figure 4.6. Extract from the overall research process for phase I 81
Figure 4.7. Case study locations in the Sri Lanka map 86
Figure 4.8. Administrative and authority governance structures in Sri Lanka 87
Figure 4.9. Sample selection process diagram 89
Figure 4.10. Sequential exploratory design (qualitative to quantitative) 93
Figure 4.11. Levels of interpretation in thematic analysis 94
Figure 4.12. Flow chart depicting the step by step process of case study data analysis 95
Figure 4.13. Sample Leximancer concept/theme maps from interview data 96
Figure 4.14. Cross-case synthesis diagram 97
Figure 4.15. Extract of overall research process for phase II 97
Figure 4.16. Survey design elements 99
Figure 4.17. Nine stages of MCDA process 104
Figure 4.18. Preference functions used in PROMETHEE 108
Figure 4.19. Multi-expert multi-criteria group decision support system flowchart 109
Figure 4.20. Sample PROMETHEE inputs, ranking, and GAIA plot 111
Figure 5.1. Chapter 5 and key sections in the thesis structure 116
Figure 5.2. Leximancer concept/theme maps from interview data of case study #1 117
Surrogate Approach to Assess Social Resilience in Disaster Management vii
Figure 5.3. Leximancer concept/theme maps from interview data of case study #2 121
Figure 5.4. Leximancer concept/theme maps from interview data of case study #3 124
Figure 5.5. Leximancer concept/theme maps from interview data of case study #4 126
Figure 5.6. Summary of synthesis for first social resilience indicator – social mobility 132
Figure 5.7. Leximancer concept/theme maps from interview data of case study #1 134
Figure 5.8. Leximancer concept/theme maps from interview data of case study #2 137
Figure 5.9. Leximancer concept/theme maps from interview data of case study #3 140
Figure 5.10. Leximancer concept/theme maps from interview data of case study #4 143
Figure 5.11. Summary of synthesis for first social resilience indicator – social trust 150
Figure 5.12. Leximancer concept/theme maps from interview data of case study #1 151
Figure 5.13. Leximancer concept/theme maps from interview data of case study #2 155
Figure 5.14. Leximancer concept/theme maps from interview data of case study #3 157
Figure 5.15. Leximancer concept/theme maps from interview data of case study #4 160
Figure 5.16. Summary of synthesis for first social resilience indicator – social competency 167
Figure 5.17. Leximancer concept/theme maps from interview data of case study #1 169
Figure 5.18. Leximancer concept/theme maps from interview data of case study #2 172
Figure 5.19. Leximancer concept/theme maps from interview data of case study #3 175
Figure 5.20. Leximancer concept/theme maps from interview data of case study #4 178
Figure 5.21. Summary of synthesis for first social resilience indicator – social equity 184
Figure 5.22. Leximancer concept/theme maps from interview data of case study #1 186
Figure 5.23. Leximancer concept/theme maps from interview data of case study #2 189
Figure 5.24. Leximancer concept/theme maps from interview data of case study #3 191
Figure 5.25. Leximancer concept/theme maps from interview data of case study #4 194
Figure 5.26. Summary of synthesis for first social resilience indicator – social beliefs 201
Figure 6.1. Chapter 6 and key sections in the thesis structure 207
Figure 6.2. GAIA representation of surrogates to measure indicator#1 210
Figure 6.3. GAIA representation of surrogates to measure indicator#2 213
Figure 6.4. GAIA representation of surrogates to measure indicator#3 215
Figure 6.5. GAIA representation of surrogates to measure indicator#4 217
Figure 6.6. GAIA representation of surrogates to measure indicator#5 219
Figure 6.7. Comparison of net flow values (ranking) of surrogates for indicator #1 222
Figure 6.8. Comparison of net flow values (ranking) of surrogates for indicator #2 223
Figure 6.9. Comparison of net flow values (ranking) of surrogates for indicator #3 223
Figure 6.10. Comparison of net flow values (ranking) of surrogates for indicator #4 224
Figure 6.11. Comparison of net flow values (ranking) of surrogates for indicator #5 224
Figure 6.12. First ranked surrogates for priority assessment of social resilience indicators 226
Figure 7.1. Chapter 7 and key sections in the thesis structure 228
Figure 7.2. Key step A and related outcomes to achieve RO1 229
Figure 7.3. Key step B and related outcomes to achieve RO2 232
Figure 7.4. Key step C and related outcomes to achieve RO3 241
Figure 7.5. An integrated (revised) surrogate development framework for resilience assessment 248
Figure 8.1. Overall schematic showing achievement of research objectives in each key step 253
Surrogate Approach to Assess Social Resilience in Disaster Management viii
List of Tables
Table 2.1. Social resilience definitions in the disaster management literature 14
Table 2.2. Social resilience frameworks evaluated in this review 19
Table 2.3. Comparison of methods to assess resilience 24
Table 3.1. Some examples of surrogate approach in other disciplines 36
Table 3.2. Comparison of key steps in indicator development frameworks 44
Table 4.1. Alternative combinations of knowledge claims, strategies of inquiry, and methods 66
Table 4.2. Three designs of mixed method research 68
Table 4.3. Details of social resilience indicators selected for developing surrogates 77
Table 4.4. Samples selected for interviews in all study locations 90
Table 4.5. Interview participant profiles 90
Table 4.6. Samples selected for interviews in one study location (DS division) 91
Table 4.7. Key characteristics and profile of survey respondents 101
Table 4.8. Five points scale continuum for each criteria 102
Table 4.9. Fundamental scale of absolute numbers and the scale used in the survey 103
Table 4.10. Comparison of Multi-Criteria Decision Analysis (MCDA) methods 106
Table 5.1. Surrogates (higher-order themes) mapping for indicator #1 . 128
Table 5.2. Surrogates (higher-order themes) mapping for indicator #2 146
Table 5.3. Surrogates (higher-order themes) mapping for indicator #3 163
Table 5.4. Surrogates (higher-order themes) mapping for indicator #4 180
Table 5.5. Surrogates (higher-order themes) mapping for indicator #5 198
Table 5.6. Cross-case tabulation for potential surrogates 203
Table 5.7. Potential surrogates selected for evaluation in online survey 205
Table 6.1. Overall PROMETHEE rankings for five social resilience indicators 208
Table 6.2. Criteria weight obtained from survey responses using AHP 220
Table 6.3. Overall PROMETHEE rankings with weighted criteria 221
Surrogate Approach to Assess Social Resilience in Disaster Management ix
List of Appendices
Appendix A Existing social resilience measures identified in social
resilience frameworks analysed in this study
Appendix B QUT Human Research Ethics Committee Approval
Appendix C Letter of recruitment for interview participants
Appendix D Participant interview consent form
Appendix E Participant information sheet for interviews
Appendix F Interview guide
Appendix G Participant recruitment email for the survey
Appendix H Participant information for the survey
Appendix I Survey questionnaire in key survey
Appendix J Abstracts of published and under review manuscripts
Surrogate Approach to Assess Social Resilience in Disaster Management x
Glossary of Terms
Disaster
“Serious disruption of the functioning of a community or a society
at any scale due to hazardous events interacting with conditions of
exposure, vulnerability and capacity, leading to one or more of the
following: human, material, economic and environmental losses
and impacts” (UN, 2016, p. 13).
Disaster
Resilience
“The ability of a community exposed to hazards to resist, absorb,
accommodate to and recover from the effects of a hazard in a timely
and efficient manner, including through the preservation and
restoration of its essential basic structures and functions”
(UNISDR, 2009, p. 24).
DS division
DS stands for ‘Divisional Secretariat’ division. Several DS
divisions make a district, which is the sub-national level
administration of the state.
GN division
GN stands for ‘Grama Niladhari’ division. The smallest
administrative geography in the Sri Lanka state administrative
system.
Higher-
order theme
A set of closely related themes combined to create a more useful
theme for further description of the context.
Leximancer
Leximancer is a data mining tool to analyse the content of textual
transcripts, which can display concepts and themes frequently
occurring in the transcripts (Leximancer, 2017).
Resilience
“The measure of a system’s or part of a system’s capacity to absorb
and recover from the occurrence of a hazardous event”
(Timmerman, 1981, p. 21).
Social
Resilience
The ability of social entities and social mechanisms to effectively
anticipate, mitigate and cope with disasters and implement
recovery activities that minimize social disruptions and reduce the
impact of future disasters (Bruneau et al., 2003; Kwok et al., 2016;
Rockström, 2003).
Surrogate
A surrogate is defined as an indicator effectively representing
another indicator that is intended to be measured (Miguntanna et
al., 2010; Rodrigues & Brooks, 2007)
Urban
“A smallest administrative division which has a minimum
population of 750 persons, a population density greater than 500
persons per square kilometre, firewood dependence of less than 95
% households, and well-water dependence of less than 95%
households” (Weeraratne, 2016, p. 4).
Surrogate Approach to Assess Social Resilience in Disaster Management xi
List of Abbreviations
AHP Analytic Hierarchy Process
CAT Capacities Coping, Adaptive, and Transformative Capacities
CBO Community Based Organisation
CR Consistency Ratio
CRED Centre for Research on the Epidemiology of Disasters
DMC Disaster Management Centre
DRR Disaster Risk Reduction
DS Divisional Secretariat (Divisional Administrative Division)
GAIA Geometrical Analysis for Interactive decision Aid
GDSS Group Decision Support System
GN Grama Niladari (Village Administrative Division in Sri Lanka
HREC Human Research Ethics Committee
KM Kalmunai (A DS division in Sri Lanka)
KMM Kalmunai Muslim (A DS divisional office in Sri Lanka)
KMT Kalmunai Tamil (A DS divisional office in Sri Lanka)
MCDA/MCDM Multi-Criteria Decision Analysis/Making
NGO Non-Government Organisation
OREI Office of Research Ethics and Integrity
PROMETHEE Preference Ranking Organization METHod for Enrichment
Evaluation
PwSN People with Specific Needs
RO Research Objective
RQ Research Question
SFDRR Sendai Framework for Disaster Risk Reduction
SM Sainthamaruthu (A DS division in Sri Lanka)
UNISDR United Nation – International Strategy for Disaster Reduction
Surrogate Approach to Assess Social Resilience in Disaster Management xii
Statement of Original Authorship
The work contained in this thesis has not been previously submitted to meet
requirements for an award at this or any other higher education institution. To the best
of my knowledge and belief, the thesis contains no material previously published or
written by another person except where due reference is made.
Signature:
Date: 16.03.2020
QUT Verified Signature
Surrogate Approach to Assess Social Resilience in Disaster Management xiii
Acknowledgements
First and most of all, I wish to express my heartfelt appreciation to my principal
supervisor, Dr. Melissa Teo, and associate supervisor, Prof. Ashantha Goonetilleke,
for their continuous guidance and insights throughout the period of my PhD studies.
Without their support, my PhD journey and thesis would not have been possible. My
sincere thanks are also extended to Prof. K.W.G. Rekha Nianthi and Dr. Jagath
Gunathilake from University of Peradeniya, and Dr. A.M. Ziyath from Zedz
Consultants for their thoughtful insights and comments on the manuscripts produced
in this study.
I am very grateful to Queensland University of Technology (QUT) and
University Grants Commission (UGC) of Sri Lanka for providing the necessary
financial support during the period of this study. I also take this opportunity to
acknowledge the time and productive discussions by all disaster management experts
who participated in the interviews and survey, which were carried out as part of this
study.
My sincere thanks also go to my academic colleagues at the South Eastern
University of Sri Lanka and my research colleagues at QUT for sharing their optimism
during the struggles of this study.
Thanks to Dr Christina Houen of Perfect Words Editing for editing this thesis
according to the guidelines of the University and the Institute of Professional Editors
(IPEd).
Last, but not the least, I owe an enormous debt of gratitude to my family
members, particularly to my parents, my wife, and my three beloved children, and our
friends, for their love and joy during the difficult times of this study.
I dedicate my PhD thesis to my parents, Majeed and Hanoon, my wife,
Sherfin, and my three beloved children, Nadtha, Nuzayh and Ulfa.
Surrogate Approach to Assess Social Resilience in Disaster Management xiv
List of publications
This research yielded a number of journal papers that were published. An abstract of
each paper in the published or submitted format is provided in Appendix J.
Journal papers published:
(1) Saja, A.M.A., Goonetilleke, A., Teo, M., & Ziyath, A. M. (2019). A critical review
of social resilience assessment frameworks in disaster management. International
Journal of Disaster Risk Reduction, 101096.
Journal Impact Factor – 2.568 (2018) SJR – Q1 (2018)
Citations – 9 [Google scholar] in March 2020
(2) Saja, A.M.A., Teo, M., Goonetilleke, A., & Ziyath, A. M. (2018). An inclusive and
adaptive framework for measuring social resilience to disasters. International
journal of disaster risk reduction, 28, 862-873.
Journal Impact Factor – 2.568 (2018) SJR – Q1 (2018)
Citations – 24 [Google scholar] in March 2020
(3) Saja, A. M. A., Teo, M., Goonetilleke, A., Ziyath, A. M., & Nianthi, K. W. G. R.
(2020). Surrogate Measures to Assess Mobility of People as a Resilience Indicator
in Disaster Management: An Exploratory Study in Southeastern Sri Lanka.
International Journal of Disaster Risk Science. doi:10.1007/s13753-020-00251-4
Journal Impact Factor – 2.162 (2018) SJR – Q1 (2018)
(4) Saja, A.M.A., Teo, M., Goonetilleke, A., Ziyath, A. and Gunatilake, J. (2020),
"Selection of surrogates to assess social resilience in disaster management using
multi-criteria decision analysis", International Journal of Disaster Resilience in the
Built Environment, Vol. ahead-of-print No. ahead-of-print.
https://doi.org/10.1108/IJDRBE-07-2019-0045.
Journal Cite Score – 1.130 (2018) SJR – Q1 (2018)
Chapter 1: Introduction 1
Chapter 1: Introduction
This chapter outlines the background (Section 1.1), social resilience to disasters
(Section 1.2), potential use of surrogate approach in social resilience assessment
(Section 1.3), and research problem (Section 1.4). Section 1.5 details research
question, aim, objectives, and outputs. Section 1.6 details the research significance and
contribution and Section 1.7 describes the research scope. Finally, Section 1.7 includes
an outline of this thesis, which is explained using a thesis structure as shown in Figure
1.2.
BACKGROUND
Over the past decades, disasters have continued to devastate many communities.
Significant investments in critical infrastructures and livelihoods have been
increasingly destroyed by disasters. During the last 20 years, over 1.3 million people
have died, 4.4 billion people were injured, or became homeless and needed emergency
assistance due to natural disasters (CRED, 2018). In 2018 alone, there were 281
disaster events recorded globally, with 10,733 deaths, and over 60 million people
affected (CRED, 2019a). The average annual total reported economic losses due to
Figure 1.1. Total reported economic losses per year, with major events
highlighted 1998-2017 (Source: (CRED, 2018), p. 13)
Chapter 1: Introduction 2
disasters worldwide was 50-100 billion US$ (CRED, 2018), as shown in Figure 1.1.
During 1998-2017, major disasters such as storms killed around 233,000 people and
earthquakes killed more than 747,234 people, highlighting the severity of the disaster
impact, globally (CRED, 2018). Asian countries are the most disaster-affected regions
in the world. For example, in 2018 alone, Asian countries accounted for 45% of
disaster events, 80% of the total number of persons killed, and 76% of the persons
affected, around the world (CRED, 2019b).
Communities who have experienced a major disaster are irrevocably changed in
a number of significant ways, including changes to community demographic structure,
resulting in different forms of resilience to the next disaster. The concept of ‘Build
Back Better’ was coined after the 2004 Indian Ocean Tsunami as a strategy “to
improve living and environmental conditions including through integrating disaster
risk reduction into development measures”, aimed at building more resilient nations
and communities to future disasters (UNISDR, 2015a, p. 8). In line with the strategy
of ‘Build Back Better', new thinking in community resilience concepts, such as
‘bouncing forward from disasters’ has become imperative for effective disaster risk
reduction (Manyena, 2016, p. 41). Two global frameworks, the Sendai Framework for
Disaster Risk Reduction and the 2030 Sustainable Development Goals, adopted in
2015 by United Nations, advocate for greater emphasis in investing in building
resilience and effective risk governance.
In the last decade, a number of frameworks and tools have been proposed for
assessing the resilience of communities to disasters. They have varied in their
approach, emphasis, and scope in determining key indicators to measure resilience
characteristics (Cutter, 2016). While a comprehensive measurement of resilience is
needed, it requires wide-ranging indicators, and their use is often resource and time
intensive (Ziyath et al., 2013). Hence, a practical and robust approach is needed to
measure resilience of communities (Kulig et al., 2013), one that can be adapted and
utilized in different contexts (Sharifi, 2016), to support future resilience building
initiatives.
The resilience of communities is a multi-faceted concept and its characteristics
can be categorized into five key domains: social, economic, environmental,
institutional, and infrastructure (Sharifi, 2016). Within a larger framework for
resilience of communities to disasters, social dimensional resilience characteristics are
Chapter 1: Introduction 3
described as ‘social resilience’. Social resilience is viewed as a key component in
resilience by many researchers (Kwok et al., 2016), due to the enormous impact of
disasters on people and societies. Social resilience is described as the “ability” or
“capacity” of people, social units (such as communities, social organizations), and
social systems (ranging from families to wider society) to cope, withstand and recover
from a disaster (Bruneau et al., 2003; Maguire & Hagan, 2007).
The importance of social resilience characteristics, such as the role of social
networks in responding to and recovering effectively from disasters, has been proven
in many disaster situations (Aldrich & Meyer, 2015). However, collecting data to
assess social resilience has been challenging in practice due to the very dynamic nature
of social systems and mechanisms. For example, social resilience indicators such as
social trust and community inclusiveness are challenging to assess directly and
accurately in the field (Kwok et al., 2016). Further, the key challenge in using direct
measures is about time and resource constraints for data collection, and replicability
of the method in order to regularly update the resilience status. In contrast, many
existing frameworks have used publicly available census data. The key drawback in
using census data is the limitation of their timeliness and poor ability to adequately
depict the resilience status of a target community. These limitations require innovative
approaches to resolve the difficulty of assessing social resilience indicators.
SOCIAL RESILIENCE TO DISASTERS
Disasters are defined by the United Nations as a
“serious disruption of the functioning of a community or a society at any scale
due to hazardous events interacting with conditions of exposure, vulnerability
and capacity, leading to one or more of the following: human, material,
economic and environmental losses and impacts.” (UN, 2016, p. 13)
Rapid urbanization and poor development planning have increased community
exposure to disasters, generating new risks or exacerbating existing ones, and have
resulted in a sharp increase in disaster related losses (UNISDR, 2015b). A key reason
why existing hazards often evolve into disasters is the failure of communities to
manage risk effectively (Birnbaum et al., 2016). A global emphasis on building
resilience to disasters among communities has been increasing as a result of large
number of devastating disaster events in the last two decades (Cox & Hamlen, 2015).
Chapter 1: Introduction 4
Communities need to proactively mitigate risks and build resilience to reduce
damage caused by disasters, and to recover more rapidly from disasters (Birnbaum et
al., 2016). The resilience capabilities of communities, however, and their speed and
extent of recovery from disasters, often differ significantly (Burton, 2015). Levels of
social resilience are often dependent on a number of complex local and context-
specific factors, such as socio-economic status, extent of external support and aid
provision, and past experience of disasters. The complexity of the social resilience
phenomena necessitates that policy makers, practitioners and researchers understand
the unique characteristics of resilient communities to help them better prepare for and
recover from disasters.
In this study, social resilience is defined as the ability of social entities and social
processes to effectively anticipate, mitigate, and cope with disasters, and implement
recovery activities that minimize social disruptions and reduce the impact of future
disasters (Bruneau et al., 2003; Kwok et al., 2016; Rockström, 2003). This definition
is adapted to consider the abilities of both social entities and social processes, along
the different phases of a disaster, i.e. ex-ante, disturbance, and ex-post. Resilience in
general, and more specifically, social resilience in a disaster context, may involve a
transformation to another state of social systems, rather than conservation of the
functionalities of existing social systems (Alexander, 2013): i.e., the system does not
necessarily need to return to its pre-disaster state. Hence, social resilience needs to be
conceptualised as a proactive ability of social entities and mechanisms, as opposed to
defining it only as the reactive capability of responding to a crisis (Matyas & Pelling,
2015), because the impact of disasters can be largely mitigated by enhancing resilience
before disasters occur (Birnbaum et al., 2016).
THE POTENTIAL USE OF SURROGATE APPROACH IN SOCIAL
RESILIENCE ASSESSMENT
The complexity and dynamic nature of social systems and processes often
challenge the assessment of their resilience in a disaster context. An innovative
application of a surrogate approach can help to overcome challenges in assessing
resilience in disaster management. This has been tested in other disciplines such as
environmental science and clinical medicine to address similar challenges in the
assessment of complex concepts. A surrogate is defined as an alternative measure to
determine the target indicator (Miguntanna et al., 2010; Rodrigues & Brooks, 2007).
Chapter 1: Introduction 5
The adoption of the surrogate approach in disaster management can capture key facets
of a resilience indicator to be measured, so that the challenges in measuring complex
and abstract resilience indicators can be addressed.
The surrogate approach has not been investigated in disaster management
literature to-date. Surrogates are useful for several reasons. For example, the time
required to measure the target system can be much shorter with a surrogate, whilst
surrogates are easier to measure than the target system, and the sample size or the
extent of the measurement entity becomes much less for a surrogate than for the target
system (Baker, 2005). In the surrogate approach, a methodical step is applied to
conceptualise, identify, and evaluate potential surrogates in order to finally select the
most robust set of surrogates for application.
The surrogate approach can be applied to assess target indicators that are often
difficult, or not feasible through direct measures in resilience assessment. Once the
surrogate is selected for a particular context through a rigorous and methodological
process of identification and evaluation, the selected surrogates can be used to monitor
and update the resilience status regularly. The application of selected surrogates at the
community and sub-national levels will play a vital role in devising the priority
resilience building activities.
RESEARCH PROBLEM
The concept of resilience has gained more prominence in disaster management
in recent years, due to ever increasing losses and damage caused to communities by
disasters. However, the complex and dynamic nature of social resilience characteristics
due to varied conceptualisation approaches in different contexts has further
complicated the assessment of social resilience to disasters (Burton, 2015). The key
challenge in social resilience is to translate abstract and complex concepts to enable
an adequate assessment that can inform effective resilience investment decisions.
Consequently, the need for a resource- and time- effective approach to assessing social
resilience to disasters has been advocated by many researchers.
Existing social resilience assessments have used direct measures, such as
household surveys and/or data obtained from census information sources available in
public databases (Saja et al., 2019). For example, direct methods such as household
questionnaire surveys have been used to measure indicators such as levels of risk
Chapter 1: Introduction 6
awareness and preparedness, past disaster experience, and trust in authorities (Tapsell,
2007). However, effective use of direct measures for social resilience assessments is
minimal (Beccari, 2016); the feasibility and replicability of such methods are
questionable due to time and resource limitations to meet the need for continuous
updating and monitoring of resilience (Ziyath et al., 2013).
Indirect measures are helpful when it is complex or not feasible to measure the
intended indicator directly (Becker et al., 2015). However, the existing social
resilience frameworks typically omit more dynamic and process oriented, but
important, resilience indicators for adequate measure of resilience. The selection of
variables from census reports has an important limitation that the required objective
variables may not be available or translatable to the indicator being measured. This is
also problematic in many countries, where census is not undertaken frequently. Hence,
there is an urgent need to conceptualise an innovative approach to enable effective
assessment of social resilience that can objectively capture key facets of indicators to
be assessed and can be easily and regularly updated. This remains a research gap that
needs to be addressed. The surrogate approach can help to address the challenges in
identifying key facets of process-oriented social resilience indicators which are
difficult to measure. Hence, this research proposes to test the surrogate approach by
developing a framework for conceptualising, identifying, and evaluating key facets of
social resilience indicators, which can act as potential surrogates to measure the target
indicator.
RESEARCH QUESTION, AIM, OBJECTIVES AND OUTPUTS
The key research question (RQ) generated from the literature review is:
How can key social resilience indicators in a disaster context
be measured using surrogate approach?
Research Aim: To investigate the above key RQ, the main aim of this research was
to develop an approach for conceptualising, identifying, and evaluating surrogates to
assess social resilience indicators in a disaster context.
Three research objectives (RO) were developed to allow detailed investigation of the
key research question. The corresponding research objectives and respective outputs
are provided below.
Chapter 1: Introduction 7
Research Objective 1 (RO 1): To identify key social resilience indicators that
require surrogate approach by developing an inclusive and adaptive social
resilience framework in a disaster context
Output 1: An inclusive and adaptive social resilience framework and surrogate
decision criteria to identify social resilience indicators to apply surrogate approach
Research Objective 2 (RO 2): To identify potential surrogates to measure key
social resilience indicators in disaster management
Output 2: A framework to guide the identification of potential surrogates to measure
social resilience in disaster management
Research Objective 3 (RO 3): To evaluate and select optimum surrogates for
application by ranking the potential surrogates against surrogate evaluation
criteria
Output 3: A framework to evaluate and rank potential surrogates to select the optimum
surrogate(s) for application
RESEARCH SIGNIFICANCE AND CONTRIBUTIONS
The introduction of a surrogate approach in disaster management research is
particularly significant; it will meet the challenge of devising a method for adequate
assessment of social resilience that can help to formulate resilience building programs
and policies by local disaster management stakeholders. Building resilient
communities is crucial to preparing, mitigating and recovering from potential
disruptions caused by disasters (Cox & Hamlen, 2015). Effective disaster preparedness
and risk reduction strategies can be planned and implemented by assessing existing
social resilience conditions at the local level. However, an adequate assessment of
social resilience has remained a challenge, due to several practical and methodological
difficulties. Hence, developing surrogates and translating them to real world
application to assess resilience indicators will help in effective resilience investment
decision making (Lindenmayer et al., 2015b).
The integrated surrogate development framework proposed in this research will
facilitate the robust assessment of social resilience indicators that are not feasible to
assess through existing direct methods and census-based measures. The use of the
surrogate approach as a novel method tested in this research is a key contribution to
Chapter 1: Introduction 8
the resilience assessment theory in disaster management, which has not been
developed to-date in the disaster management sector.
The surrogate model and a method to operationalise the set of robust surrogates
identified from the outcomes of this research will assist policy makers and practitioners
to assess social resilience at local and sub-national levels. An adequate assessment of
dynamic and process oriented social resilience indicators in a disaster context has been
an important knowledge gap in disaster management. This research has contributed to
addressing this challenge by using a surrogate approach. This approach will also guide
future research for assessing other dynamic and process oriented resilience indicators
in disaster management that were found to be very difficult to assess through
conventional methods.
RESEARCH SCOPE
This study focuses on developing a new approach to assess social resilience indicators
using surrogates in disaster management. The scope of this research study is as
follows.
(1) Urban context: Data collection to identify potential surrogates in the first phase of
this research was done in an urban context, using Sri Lanka as a case study. The focus
was on urban context to make the findings widely applicable, as 54% of the world
population reportedly live in urban areas, and 16% live in large cities around the world
(WorldBank, 2014). The study findings and outcomes are generic and can be
applicable in any urban context with proper contextualisation of socio-economic and
disaster characteristics.
(2) Expert consultation: This study employed sequential exploratory mixed method
research design, which used both, qualitative and quantitative data collection methods.
The initial consultation with experts through interviews in the case study (Phase I –
qualitative research) was done with disaster management practitioners working at the
local and sub-national levels in Sri Lanka. Experts at the national and international
level were reached through an online survey (Phase II – quantitative research) for
evaluating the potential surrogates. This method facilitated to reach a wide audience
of practitioners, policy makers, and researchers working in disaster management in
different countries, which helped to increase the validity of the findings.
Chapter 1: Introduction 9
THESIS OUTLINE
This thesis consists of eight key chapters, and a graphical representation
depicting the key content covered in each chapter is shown in Figure 1.2:
Chapter 1 – ‘Introduction’ explains briefly the background tor this thesis, social
resilience to disasters, the potential use of surrogate approach in social resilience
assessment, the research problem, research question, research aim, objectives and
outputs, research signification and contribution, and finally the scope of this study.
Chapter 2 – ‘Literature Review’ is structured into four sections based on the
critical review of literature relevant to this research study. These sections include:
social resilience definitions in disaster management (Section 2.1), a critical review of
social resilience assessment frameworks in disaster management (Section 2.2), a ‘5S’
inclusive and adaptive social resilience framework in disaster management (Section
2.3), and finally, a summary and implications for this research (Section 2.4).
Chapter 3 – ‘Surrogate approach to assess social resilience to disasters’ has three
sections. Section 3.1 provides an overview of the surrogate approach, Section 3.2
details the framework developed to identify and assess the use of social resilience
surrogates in the disaster context, and finally there is a summary of the chapter (Section
3.3).
Chapter 4 - ‘Research method’ is divided into eight sections. This chapter aims
to provide an overall summary of the research methods applied in this research. Section
4.1 gives an overview of philosophical assumptions of the research, Section 4.2
provides an overall research method, and Section 4.3 details the selection of social
resilience indicators for developing a surrogate approach. Section 4.4 details ethical
research considerations. Section 4.5 details the qualitative method applied in phase I
to identify surrogates, and Section 4.6 details the quantitative method applied in phase
II to evaluate and select surrogates; the final Section 4.7 provides a summary.
The next two chapters (Chapter 5 and Chapter 6) report the findings of this study
in two phases, respectively. Chapter 5 discusses the main findings of phase I interviews
across four case studies for five social resilience indicators – social mobility, social
trust, social competence, social equity, and social beliefs which are covered
respectively in Sections 5.1 to 5.5. The final Section 5.6 reports the overall findings
Chapter 1: Introduction 10
from phase I that include a cross-case synthesis of potential surrogates and selection
of surrogates for evaluation in phase II of this study.
Chapter 6 details the findings from phase II of this study and has five sections.
Section 6.1 presents the evaluation and ranking of potential surrogates using equal
criteria weights. Section 6.2 presents the calculation of criteria weights from the survey
data, while Section 6.3 presents the PROMETHEE ranking obtained with experts’
consolidated criteria weights. Section 6.4 presents the list of first ranked surrogates
selected based on the ranking of potential surrogates obtained in the online survey.
Finally, Section 6.5 provides a summary of phase II findings.
Chapter 7 – ‘Synthesis of key findings’ is divided into four sections, which
synthesises the key findings in Chapters 4, 5 and 6. Section 7.1 synthesises the findings
in relation to RO1, Section 7.2 synthesises the findings in relation to RO2, and Section
7.3 synthesises the findings in relation to RO3. Section 7.4 presents an integrated
(revised) surrogate development framework for future application in disaster
management by revising the conceptual surrogate development framework tested in
this study.
The final chapter (Chapter 8), ‘Conclusions and recommendations for future
research’, has five sections. These include: Section 8.1 - Achievement of three study
objectives’, Section 8.2 – Addressing the key research question, Section 8.3 – Study
contributions to knowledge and practice, Section 8.4 – Study limitations, and Section
8.5 – Key recommendations for future research.
Chapter 1: Introduction 11
Figure 1.2. Thesis structure with key sections
Chapter 2: Literature Review 12
Chapter 2: Literature Review
This chapter consists of four sections of the literature review, including a
summary section (Section 2.4) at the end, as shown in Figure 2.1. The first three key
sections (Sections 2.1 to 2.3) discuss the following topics in social resilience literature:
- Section 2.1 focuses on social resilience definitions in disaster management.
- Section 2.2 provides a critical review and identifies key knowledge gaps of social
resilience assessment frameworks developed in a disaster context.
- In Section 2.3, an inclusive and adaptive ‘5S’ social resilience framework in
disaster management is presented.
- Finally, the summary and implications of the literature review are provided (in
Section 2.4); the contents of Chapter 2 are summarised highlighting key problems
and knowledge gaps in social resilience assessment in a disaster context; from this
a key research question studied in this research is formulated.
Figure 2.1. Chapter 2 and key sections in the thesis structure
Chapter 2: Literature Review 13
SOCIAL RESILIENCE DEFINITIONS IN DISASTER MANAGEMENT
This section details the different ways that social resilience is defined in disaster
management literature, and the definition adapted in this study.
Resilience means the ability of an object or entity to return to its original shape
after an adverse event. The concept of resilience has been studied and applied across
many diverse disciplines, including ecology, biology, social-ecological systems, social
science, and psychology (Ainuddin & Routray, 2012; McMillen et al., 2016; Norris et
al., 2008; Quinlan et al., 2015). For example, the ‘bounce-back’ analogy from
engineering resilience, the ‘resistance’ concept in social vulnerability, and the
‘robustness’ concept in social-ecological systems theory, have contributed to diverse
interpretations of resilience in the current literature (Matyas & Pelling, 2015).
Specifically, social resilience has been broadly studied in natural resource
management, social change and development, and disaster management (Keck &
Sakdapolrak, 2013).
Due to the complexity of defining resilience, new thinking in resilience
recognises the complex relationships between the built, natural, and social
environments and their influences on the understanding of resilience to disasters
(Norris et al., 2008). Quinlan et al. (2015) suggested, however, that “while multiple
conceptions of resilience can be problematic in terms of common indicators and
comparable metrics, they can also extend the concept to a broader spectrum of contexts
and drive exploration for better approaches to implementation” (p. 679).
The use of the resilience concept has developed in the ecological sciences since
the 1970s. Although the history of resilience concept can be traced back many decades,
the term ‘resilience’ was brought to prominence in ecology by C.S. Holling,
(Alexander, 2013). Holling (1973) defined it as a measure of the ability of an
ecological system to sustain disturbances and still persist. In one of the first definitions
of resilience in a disaster context (Klein et al., 2003), Timmerman (1981) suggests that
resilience is “the measure of a system’s or part of a system’s capacity to absorb and
recover from the occurrence of a hazardous event” (p. 21).
The study by Adger (2000) on ecosystems is widely acknowledged as the first
study to define social resilience (Keck & Sakdapolrak, 2013). In the context of socio-
ecological systems, in this case a mangrove conversion, Adger (2000) defined social
Chapter 2: Literature Review 14
resilience as “the ability of communities to withstand external shocks to their social
infrastructure” (p. 361). Adger (2000) further highlighted the need to consider
contextual social attributes in defining social resilience because of varying differences
in community institutions and resource priorities.
Social resilience in a disaster context is defined in many different ways, as shown
in Table 2.1: a) abilities of social entities or largely social systems that include families,
the wider community, social groups, organisations, resources, and structures (Khalili
et al., 2015; Maguire & Hagan, 2007); b) abilities of social mechanisms such as
understanding and managing emerging risks as well as self-organisation and
transformation capacities (Kimhi & Shamai, 2004; Shaw et al., 2014); c) abilities of
both, social entities and mechanisms (both outcome and process oriented features)
(Kwok et al., 2016); and d) community’s coping, adaptive, and transformative
capacities to withstand and recover from disasters (Parsons et al., 2016). Additionally,
the diversity and dynamics of the context, in which the concept of resilience is
operationalised, brings more complexity to the definition (Alexander, 2013).
Table 2.1. Social resilience definitions in the disaster management literature
Type of
definitions
Disaster
context Social resilience definition Ref.
a)Ability of
social entities
All
disasters
“The capacity of social groups and
communities to recover from, or respond
positively to, crises.”
“The capacity of a social entity (e.g., a
group or community) to bounce back or
respond positively to adversity.”
(Maguire
& Hagan,
2007, p.
17)
Community
seismic
resilience
“Ability of social units (e.g., organisations,
communities) to mitigate hazards, contain
the effects of disasters when they occur, and
carry out recovery activities in ways that
minimise social disruption and mitigate the
effects of future earthquakes.”
(Bruneau
et al.,
2003)
(p.4)
All
disasters
“Internal ability of the social system to
counteract events described as the failure of
expectation toward its environment during
disasters, crises and emergencies.”
(Lorenz,
2013)
(p.12)
All
disasters
“The ability of a community to withstand
external social shock toward enhancing
social capacity to resist disaster losses
during disaster and regenerate after
disaster.”
(Khalili et
al., 2015,
p. 249)
Chapter 2: Literature Review 15
Type of
definitions
Disaster
context Social resilience definition Ref.
Socio-
Ecological
Systems
“Ability of groups or communities to cope
with external stresses and disturbances as a
result of social, political and environmental
change.”
(Adger,
2000, p.
347)
All
disasters
“The capacity of a social system (e.g., an
organisation, city, or society) to proactively
adapt to and recover from disturbances that
are perceived within the system to fall
outside the range of normal and expected
disturbances.”
(Boin et
al., 2010,
p. 9)
b) Ability of
social
mechanisms/
processes
Drought
Mitigation
“Social coping mechanisms that are used to
cope with extreme unmanageable shocks.”
(Rockströ
m, 2003,
p. 871)
Coastal
flooding
“Social resilience = risk perception X self-
perception X accepting change X self-
organisation.”
(Shaw et
al., 2014)
(p. 202)
All
disasters
Individuals’ sense of the ability of their
own community to deal successfully with
the emerging threat.
(Kimhi &
Shamai,
2004)
(p. 442)
c) Ability of
social entities
& mechanisms
All
disasters
“The ability of a community's social
environment to effectively anticipate, cope
with, and recover from disasters, which
depends on the presence and robustness of
other community features, resources, and
processes”
(Kwok et
al., 2016)
(p. 205)
d) Coping,
adaptive, and
transformative
capacities
All
disasters
“The capacity of communities to prepare
for absorb and recover from natural hazard
events, and the capacities of communities to
learn, adapt and transform towards
resilience”
(Parsons
et al.,
2016)
(p. 3)
In this study, social resilience is defined as the ability of social entities and
processes to effectively anticipate, mitigate, and cope with disasters, and implement
recovery activities that minimise social disruptions and reduce the impact of future
disasters (Bruneau et al., 2003; Kwok et al., 2016; Rockström, 2003). This definition
is adapted to consider the abilities of both social entities and social processes, along
the different phases of a disaster, i.e. ex-ante, disturbance, and ex-post.
Chapter 2: Literature Review 16
A CRITICAL REVIEW OF SOCIAL RESILIENCE ASSESSMENT
FRAMEWORKS IN DISASTER MANAGEMENT
A systematic literature review was conducted to critically analyse current social
resilience assessment frameworks in the disaster context. The key findings and
knowledge gaps are presented in this section.
2.2.1 Social resilience assessment frameworks in disaster context
Many social resilience assessment frameworks have been developed in a disaster
context as a result of different ways of defining and conceptualising social resilience
(Aldunce et al., 2015; Cutter, 2016; Djalante & Thomalla, 2011; Norris et al., 2008).
The understanding of different concepts used to frame social resilience in a disaster
context is critical to further advancing these frameworks to comprehensively measure
social resilience characteristics. Table 2.2 summarises 31 social resilience frameworks
that were identified through a comprehensive literature search and critically analysed.
A systematic literature review was conducted to critically analyse current social
resilience frameworks in disaster context. In selecting literature for inclusion in the
review, social resilience frameworks developed within the last decade (2005-2015) in
the disaster management sector were identified. The period between 2005 and 2015
coincided with the period of the implementation of the Hyogo Framework for Action
(HFA) which was the global guiding framework for disaster risk reduction efforts since
2005. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses –
PRISMA (Moher D, 2009) method was used to select social resilience frameworks for
a detailed review as shown in Figure 2.2. PRISMA is an established method for
guiding systematic review of academic literature, and is based on four steps:
Identification, Screening, Eligibility, and Inclusion.
Key steps of the PRISMA method is explained below:
Step 1 - Identification stage: The keywords, “Social” OR “Community” AND
“Resilience” were used in the search to identify all potential peer-reviewed research
articles on social resilience. The initial literature search was done using the Scopus
database, which is a comprehensive research database for peer-reviewed literature, for
the period between 2005 and 2015 in Title, Abstract, and Keywords (Scopus, 2017).
This resulted in the identification of 12,121 research articles.
Chapter 2: Literature Review 17
Step 2 - Screening stage: In this stage, search limiters on relevant disaster related
disciplines, such as social science, environmental science, and multidisciplinary
studies were used. Journals that are not relevant to disaster research and in languages
other than English were excluded. Consequently, 1,194 relevant research articles were
selected.
Step 3 – Eligibility check: In this step, the titles of the selected 1,194 research
articles were screened to narrow down the search for the most relevant articles on
social resilience to disasters. The title and abstracts of articles that do not relate to
social/community resilience in any natural disaster context were excluded. Finally, 172
research articles were selected for detailed review of abstracts.
Step 4 – Inclusion step: Based on the review of the abstracts of the 172 articles,
16 social resilience frameworks were selected. Using the snowball technique, 15
Figure 2.2. PRISMA Flow diagram used for selection of social resilience frameworks
for analysis
Chapter 2: Literature Review 18
additional articles were included. Accordingly, a total of 31 different social resilience
frameworks were selected for detailed analysis.
In Table 2.2, the 31 frameworks are categorised by the researcher (year), hazard
focus, and country of development (geographic coverage) along with the method
adopted for developing the framework. Only social resilience characteristics were
included from the multi-dimensional disaster resilience frameworks. However, other
resilience characteristics that are closely related to social resilience, such as social-
culture and human capital, were also considered in the evaluation.
The 31 social resilience frameworks can be categorised into two main
approaches: distinctive single dimensional frameworks, and those embedded within
multi-dimensional community resilience frameworks. While the embedded social
resilience framework is part of a broader multi-dimensional framework, a distinctive
framework is a stand-alone social resilience framework.
Distinctive single dimensional frameworks: These frameworks consider only
one dimension of community resilience - social resilience or economic resilience
characteristics. They cover single-dimensional resilience characteristics in more detail.
For example, Kwok et al. (2016) identified 66 unique social resilience characteristics
and finally proposed 18 key social resilience characteristics. In another study, Khalili
et al. (2015) identified 18 social resilience characteristics. Both frameworks have
captured some similar characteristics/indicators, such as leadership and social trust.
Chapter 2: Literature Review 19
Table 2.2. Social resilience frameworks evaluated in this review
(1) Distinctive social resilience frameworks
# Framework Country Hazard Method adapted Ref.
1 Social Resilience for New Zealand New Zealand Multi hazard Workshop (Expert Opinion from Researchers,
Practitioners, and policy makers)
(Kwok et al., 2016)
2 Social-Ecological Flood Resilience Index Southern Cape of South
Africa
Flood Secondary data from public databases (Census
data)
(Kotzee & Reyers, 2016)
3 Temporal Social Resilience Framework Australia Flood Literature review Case study in 2 locations (Khalili et al., 2015)
4 Social System Resilience Not specific Multi hazard Literature review (Lorenz, 2013)
5 Social Resilience Framework Australia Common to all
disasters
Literature review (Maguire & Hagan, 2007)
(2) Social resilience frameworks embedded within the multi-dimensional community resilience frameworks
# Framework Country Hazard Method adapted Ref.
6 Australian Natural Disaster Resilience
Framework Index (ANDRI)
Australia Multi hazard Literature review (Parsons et al., 2016)
7 Community Disaster Resilience
Index (CDRI)
Korea Multi hazard Index development with secondary data (Yoon et al., 2016)
8 Community Disaster Resilience Framework
for Iran
Iran Multi hazard Expert opinion through Focus Group Discussions (Ostadtaghizadeh et al.,
2016)
9 Community Resilience Score Card Australia Multi hazard Score card approach (Arbon et al., 2016)
10 Social Resilience Index (SRI) (Component
Community Resilience Index)
Pakistan Flood Questionnaire and secondary data (Qasim et al., 2016a)
11 Resilience Assessment
in Slums
Kenya Slums Multi hazard Workshop and case study approach (Woolf et al., 2016)
12 Conjoint Community Resiliency
Assessment Measure (CCRAM)
Israel-Gaza borders Security threats Web-based survey (Longitudinal study) (Leykin et al., 2016)
13
Community Resilience to Disasters in Saudi
Arabia
(CRDSA)
Saudi Arabia Multi hazard Delphi based expert opinion/AHP (Alshehri et al., 2015a)
14 Composite Community Resilience Index Baluchistan, Pakistan Earthquake Literature review, Composite index (Ainuddin et al., 2015)
Chapter 2: Literature Review 20
15 Disaster Resilience Indicators Mississippi Gulf Coast
in the United States
Hurricane Case study, secondary data for index
development
(Burton, 2015)
16 Rural Resilience Index (RRI) USA Multi hazard Literature review, Pilot study (Cox & Hamlen, 2015)
17 Baseline Resilience Indicators for Communities (BRIC)
US Counties Multi hazard Public and freely accessible data sources, and created dimensional scores
(Cutter et al., 2014), (Cutter et al., 2010)
18 Climate Disaster Resilience Index (CDRI) Chennai, India Multi hazard Literature review, CDRI scores (Joerin et al., 2014)
19 Social Dimension Score (Resilience Score) Indonesia Multi hazard In-depth Interviews, Focus Group Discussions (Kusumastuti et al., 2014)
20 Baseline Resilience Indicators
for Communities (BRIC)
Sarasota County,
Florida, USA
Multi hazard Interviews, plan review, focus group, and spatial
analysis
(Frazier et al., 2013)
21 Community Resilience Framework Los Angeles, USA Health focus Online survey (Chandra et al., 2013)
22 Communities Advancing Resilience Toolkit
(CART)
USA Multi hazard A toolkit consists of assessment and data
collection tools
(Pfefferbaum et al., 2013)
23 Disaster Resilience Index Japan Coastal hazards Analytic Hierarchy Process (AHP) (Orencio & Fujii, 2013)
24 Communities Advancing Resilience Toolkit
(CART)
USA Multi hazard Web-based survey using expanded version of the
CART
(Norris et al., 2008),
(Sherrieb et al., 2012)
25 Community Disaster Resilience Indicators
(CDRI)
US Gulf Coast Region Multi hazard Results from implementing a project (Peacock et al., 2010)
26 Community Resilience
Index (CRI)
Mississippi counties Multi hazard Index creation (Archival and population data) (Sherrieb et al., 2010)
27 Coastal Community Resilience Index
(CCRI)
USA Multi hazard Community Self-Assessment Tool (Index) (Sempier et al., 2010)
28 PEOPLES Resilience Framework USA Multi hazard Literature Review (Renschler et al., 2010)
29 Disaster Resilience of Place (DROP) USA Multi hazard Conceptual model based on literature review (Cutter et al., 2008)
30 Building resilience in rural communities
toolkit
Australia Multi hazard Research/community consultation (Hegney et al., 2008)
31 Capital based Community Disaster
Resilience
USA Multi hazard Index development with secondary data (Mayunga, 2007)
Chapter 2: Literature Review 21
However, there are many differences as well. For example, Khalili et al. (2015) used
social innovation and learnings from previous disasters, which were not prioritised in
the framework developed by Kwok et al. (2016). This leads to a lack of consistency in
fundamental characteristics of social resilience used in contextual frameworks.
Embedded social resilience frameworks: These frameworks view community
resilience as multi-dimensional, using variations of resilience characteristics in the
following five dimensions - social, economic, infrastructure, institutional, and
environment. More than two-thirds of the embedded social resilience frameworks have
not considered key dimensions such as community aspirations, goals and efficacy,
social institutions, social safety measures, equity and diversity/inclusiveness, local
culture/beliefs/faiths, community processes, and education.
There is a tendency to prioritise easily measurable resilience characteristics such
as social demography and social networks, and many process-related resilience
characteristics have received relatively lower priority due to difficulty in measurement.
The broader the framework with multi-dimensions, the lesser is the focus on each
dimension, and vice-versa. The scale of exclusion of important social resilience
characteristics is evident in many embedded frameworks, since it needs to include
characteristics in all dimensions. Hence, they mostly leave out key social resilience
characteristics that may require extensive assessment, which limits adequate
assessment of social resilience.
2.2.2 Social resilience characteristics and indicators
A typical social resilience framework has two layers: characteristics and
indicators. Most of the social resilience frameworks have adapted the
characteristics/indicators-based approaches to measure social resilience, because those
frameworks can be easily operationalised. In general, a set of indicators is needed to
characterise social resilience as well as for the practical application of social resilience
frameworks to different types of disasters and for varying contexts. A resilience
indicator is a description of observable or measurable information that is used to
identify the state or function of social entities (Jülich, 2017; UnitedWay, 1996).
A set of indicators will collectively measure a resilience characteristic. However,
at times, the distinction between characteristics and indicators is not rigid (Twigg,
2009). The resilience indicators can be process indicators or outcome indicators. The
outcome indicator shows how well certain activities accomplish their proposed results,
Chapter 2: Literature Review 22
and the process indicator is a measure of how well the activities are implemented
(Doorn, 2017). Both process and outcome indicators are important for measuring
social resilience, because process indicators help to understand the community and
sustainability of the community programs, whereas outcome indicators reflect the
achievements of community capacity building and empowerment (Kafle, 2012).
A lack of agreement and consistency in framing the social resilience
characteristics adds a further degree of complexity to the useful transformation and
utilisation of the concept in multiple contexts. For example, around one-third of the
frameworks only have two layers and do not identify indicators. Two-thirds of the
frameworks analysed had a third layer as indicators, with the exception of a few
frameworks that have indicators as the second layer in one social dimension. Some
frameworks have termed indicators as variables. There is also lack of clarity about
characteristics and indicators in some frameworks, and characteristics are sometimes
labelled as indicators. Therefore, a key knowledge gap in social resilience research is
a systematic structuring of a social resilience framework in logical layers, which can
guide the practitioners to operationalise it uniformly across different communities.
Future development of social resilience frameworks needs to consider key process-
oriented social resilience characteristics that are critical for adequate measurement of
social resilience, since they are largely neglected in the existing frameworks.
2.2.3 Challenges in measuring social resilience indicators
Social resilience to disasters can be measured for many different purposes. These
include: (a) measuring the relative level of resilience between two geographic
locations; (b) measuring changes in resilience status (trend) over the continuous span
of time within a single phase of the disaster; (c) measuring resilience in multiple stages
of a community at discrete time intervals, such as the changes between different
disaster phases (before, during, and after a disaster); (d) measuring hazard-specific
resilience of a community; and (e) combination of above scenarios. However,
“resilience has proven difficult to measure, and an alternative to estimating resilience
directly is to monitor characteristics of systems that are related to the resilience of the
system and are measurable” (Bennett et al., 2005, p. 946).
The key conceptual challenge in measuring resilience is that resilience is not
only an outcome, but also a process oriented phenomenon (Cox & Hamlen, 2015). The
outcome oriented resilience characteristics are static conditions with a single
Chapter 2: Literature Review 23
measurable target, whereas process oriented characteristics describe dynamic
properties of resilience (Cutter, 2016). Within most existent literature, social resilience
is perceived as a static characteristic (Cutter et al., 2008) for measurement rather than
a process related indicator (Sharifi, 2016), mainly because process indicators are not
easily measurable. For example, the number of civic organisations is an outcome
indicator to measure civic engagement in social networks. However, the existence of
many civic organizations cannot alone enhance social resilience. It is important to
understand how the type of activities undertaken by civic organisation can increase
social resilience (Cutter, 2016), which are process oriented indicators. Likewise,
adaptive capacity cannot be measured using “number of years of schooling” as an
indicator alone, because people’s adaptive capacity cannot be simply measured by how
long they attend school (Levine, 2014). Therefore, a failure to measure both, outcome
and process features of resilience results in inadequate and inaccurate assessment of
social resilience. However, it is often a challenging task to operationalise resilience
frameworks due to the multifaceted dimensions of resilience (Cutter et al., 2008) and
multiple abilities (Levine, 2014).
There are methodological challenges in measuring resilience too, which include:
the adequacy of indicators and how to measure them; and conceptual differences
further to the arbitrary definition of indicators (Levine, 2014). In practice, it has been
a challenge to collect data to inform the social resilience characteristics due to time
and resource constraints as well as the dynamic nature of characteristics that have
multiple inter-relationships, resulting in a complex network model (Ziyath et al.,
2013). These challenges are further compounded, as there is currently limited guidance
on what characteristics to measure, which indicators to use, and for what purpose and
context (Cutter, 2016). As a result, many social resilience frameworks commonly
capture easily accessible static indicators, while leaving out the dynamic and complex
key characteristics. Since it is difficult to directly measure many of the social resilience
characteristics, proxy measures are proposed/used which mostly are obtained from
secondary and census data information sources available in public databases.
Resilience frameworks that were operationalised to-date have used direct
methods such as household surveys and interviews, and/or data obtained from census
reports from public databases to assess resilience. Table 2.3 below highlights key
differences of two widely applied methods – using direct household surveys and
Chapter 2: Literature Review 24
census measures to assess resilience. The merits in direct household measures are
demerits in using census data measures, and vice-versa, as listed in Table 2.3. For
example, direct measures such as household surveys are time and resource intensive
process, while resilience measures using census data can be faster. However, both
these methods have limitations in the replication of the process to regularly update the
resilience status. This is because census data is not frequently updated and frequent
replication of direct measures are also very difficult in most contexts due to limited
resources.
Table 2.3. Comparison of methods to assess resilience
Resilience measure using
household surveys
Resilience measure
using census data
Data sources Households Census data and
statistics
Method of
accessing
data
Web/Household survey, 1-1 or focus
group interviews, consultation, self-
assessment
Census reports and data
from public databases
Merits
More realistic at the time of
measurement or for a period of time
Minimal use of
resources and faster
Data reflects the perception of social
resilience in the community
Easy to develop indices
and statistical models
Can capture process based measures
and qualitative analysis is possible
Reproduced when
census is updated
Demerits
Time consuming, finance and human
resource intensive process
Lack of accuracy
compared to surveys
due to not capturing
key social dynamics
and processes
Replication and regular updates are
difficult in resource-limited contexts
Results can be easily
reproduced, replicated,
and improved only
when the new census
becomes available
Limited set of easily measurable
indicators are chosen
Mostly capture
outcome measures
Existing indicators to capture social resilience are inadequate, since resilience
characteristics such as social capital, social dynamics and interactions are hard to
measure in practice (Cutter, 2016). One common approach in social resilience
measurement is to use publicly available and easily accessible data sets such as census
data as proxy measures to formulate indicators (Cutter, 2016). The effectiveness of
this approach is highly dependent on the accuracy of the data set, and the ability to
methodically and accurately characterise social resilience indicators within a broader
Chapter 2: Literature Review 25
framework (Levine, 2014; Ziyath et al., 2013). Therefore, another key knowledge gap
in social resilience measurement is the need for novel ways to capture key social
resilience characteristics with more conceptual clarity of their measurement.
Social resilience is also too complex to reduce it to a numeric value (Woolf et
al., 2016) and capturing dynamic social resilience characteristics using a static
measurement is not easily achievable (Schipper & Langston, 2015) for effective
decision making. Inadequate information about measurement tools and techniques and
lack of clear guidelines for measuring proposed resilience indicators in many
frameworks limit the operationalisation of the framework in different contexts
(Serfilippi & Ramnath, 2018). In the absence of robust guidelines accompanying the
set of indicators that are proposed to measure resilience, the possibility exists for the
misinterpretation of the indicator data, which may lead to inaccurate outcomes. Doorn
(2017) highlighted that the use of non-aggregated indicators can be useful for
contributing to detailed analysis of resilience than aggregated indices, for the latter are
mainly helpful in the evaluation of intervention effectiveness and drawing attention to
an issue. Resilience measurements also need to move beyond existing index based
quantifications to produce results that are oriented towards resilient development
outcomes and strategies to enhance resilience at community level (Peters et al., 2016).
Hence, new methods are needed for detailed analysis of resilience indicators that can
capture important facets of key social resilience characteristics, such as social capital,
social mechanisms, and social dynamics (Cutter, 2016), which are multi-faceted,
process oriented and abstract concepts.
2.2.4 Key knowledge gaps and recommendations for further research
The following three key knowledge gaps for future research on social resilience
in a disaster context are highlighted as shown in Figure 2.3, based on the critical
analysis of existing social resilience assessment frameworks.
Firstly, many challenges inherent in adequately measuring social resilience, as
highlighted in Section 2.2.3, necessitate a well-structured, rigorous, and adaptable
framework in the context of disaster management. Developing an integrated and
adaptable framework for consistent operationalisation remains an important research
gap in social resilience research. A comprehensive social resilience framework which
considers multiple dimensions of the social resilience concept is a pre-requisite for any
detailed assessment of resilience. However, the existing social resilience assessment
Chapter 2: Literature Review 26
frameworks have largely been developed without consensus on the key characteristics
of social resilience and how to robustly measure them. The key question which remains
unanswered is the extent to which existing frameworks can be adapted for different
contexts, since many of them have been developed within a limited context, scale and
scope. Therefore, there is a need to explore the development of a generic framework
Figure 2.3. Summary of the literature review highlighting knowledge gaps in
social resilience assessment
Chapter 2: Literature Review 27
that could guide the selection of social resilience indicators methodically to capture
multiple social resilience dimensions, and which can be adapted to different contexts.
Secondly, most social resilience frameworks have focused on outcome oriented
social resilience indicators, since they can easily produce social resilience indices.
These indices however, have limited value for interpreting the actual resilience status
of a community. In contrast, process-oriented indicators are based on dynamic
properties which are essential to comprehend social resilience adequately, have been
largely neglected. This is mainly because they are difficult to measure due to their
dynamic nature. Hence, new methods to capture key process-oriented social resilience
indicators that are critical for adequate measurement of social resilience are needed,
which is another key knowledge gap to be addressed in social resilience assessment
research. An adequate measurement of social resilience requires both, outcome and
process oriented social resilience characteristics that can capture social dynamics and
perceptions. Hence, future research needs to find innovative methods such as multi-
stakeholder engagement tools to capture the dynamic nature of social resilience.
Thirdly, conceptual frameworks should be translated into practice to help
decision-makers to operationalise social resilience measures (Abenayake et al., 2016).
Conceptual and measurement complexity and diversity have led to limited agreement
on a standard approach to operationalising the resilience concept in disaster
management (Cutter, 2016; Ostadtaghizadeh et al., 2015; Sharifi, 2016). A key
research gap still exists in relation to the assessment of the reliability and consistency
of resilience measures, when frameworks are operationalised in real-world
applications. A novel approach is needed to address the limitations in using existing
methods. Many existing social resilience frameworks developed in a disaster context
have applied selected measures from publicly available census data, since many of the
social resilience indicators require direct measures, which are time and resource
intensive. However, the use of census data from public databases to measure resilience
indicators does not depict resilience adequately or accurately since most often census
data is outdated and does not provide enough information about the dynamic nature of
resilience indicators. Further, the absence of a methodical process for identifying and
selecting the best measures from census data is limited. Hence, the use of surrogates
in lieu of actual parameters needs to be explored to address the challenges in measuring
resilience.
Chapter 2: Literature Review 28
A ‘5S’ INCLUSIVE AND ADAPTIVE SOCIAL RESILIENCE
FRAMEWORK IN DISASTER MANAGEMENT
This section reports how a ‘5S’ inclusive and adaptive social resilience
framework was developed in this study by critically analysing existent social resilience
frameworks.
A resilience framework should be able to guide the selection of appropriate
social resilience characteristics and their adequate operationalisation based on the
context of its application (Parsons et al., 2016). In this study, an inclusive framework
was developed from the critical analysis of existent frameworks to systematically
select required key indicators from different social resilience dimensions. A set of key
process-oriented social resilience indicators that are difficult or not feasible to measure
through existing methods needs to be methodically selected to apply new methods of
measurement such as the surrogate approach. In this study, the ‘5S’ framework was
used for the purpose of selecting those indicators to develop surrogates that can cover
multiple key social resilience dimensions for adequate measurement of social
resilience.
2.3.1 ‘5S’ social resilience framework structure and components
In the ‘5S’ social resilience framework, key social resilience characteristics were
clustered in sub-dimensions to create a well-structured framework based on a three-
layer structure: key dimensions, resilience characteristics, and indicators, as shown in
Figure 2.4. The social resilience framework consists of five social dimensions (denoted
as ‘5S’ framework): social structure, social capital, social
mechanisms/competence/values, social equity and diversity, and social
beliefs/culture/faith (Figure 2.5). These were based on the most commonly used
categories of social resilience as identified in the research literature. By incorporating
key characteristics and indicators in five key dimensions, a ‘5S’ framework was
developed to measure social resilience, as shown in Figure 2.5.
Social resilience to disasters
Key
dimensions
Resilience
Characteristics
Process and
Outcome
Indicators
Figure 2.4. Three-layer structure of the ‘5S’ social resilience
framework
Chapter 2: Literature Review 29
Figure 2.5. An inclusive and adaptive ’5S’ model social resilience
framework
Chapter 2: Literature Review 30
The ‘5S’ framework is flexible and can be adapted to any geographical, hazard,
or community context by shifting the priority of the characteristics and indicators
according to the context. The proposed ‘5S’ model is inclusive in the sense that a
comprehensive set of key social resilience characteristics and indicators is
incorporated within a single structure. A brief explanation of each dimension and its
composition of social resilience characteristics is provided below.
Social structure:
Social structure is defined broadly to include a wide-range of social
characteristics, including network and relationships (Nadel, 2013). However, some
specific definitions of social structure are confined to define population distribution
and composition in a geographic space. The definition of social structure as the
distribution of population that includes parameters such as gender, ethnicity,
education, and income in multiple social layers (Blau, 1977) was adopted for this
study. The attributes of social structure are important to understand and differentiate
specific population and demographic parameters such as household income and age
distribution (Renschler et al., 2010) (See Figure 2.5 for key characteristics and
indicators). There are three characteristics and nine indicators in social structure. The
characteristics include: social demography, household structure, and mobility of
people and families.
Social capital:
Social capital is a dominant, highly influential, and widely studied aspect in
determining social resilience to disasters (Aldrich & Meyer, 2014a). Initial focus of
social capital on relationships in social structures and networks by Hanifian (1916),
Bourdieu (1986), and Coleman (1990) were advanced by Putnam (1993), to features
of social organisations such as networks, norms of reciprocity, and trust, that facilitate
action and cooperation for mutual benefit (Aldrich & Meyer, 2014a; Sanyal &
Routray, 2016). Later, social capital was classified into three types: bonding, bridging,
and linking capital (Aldrich & Meyer, 2014a). It can also be categorised as structural
and cognitive social capital (Sanyal & Routray, 2016). Social capital in this study
includes: social ties within community groups, mostly associated with family
relationships; and place of attachment (bonding); networking abilities made up of
economic and other ties that are external to the community (bridging); and the
interaction between social groups and community networks with the governing
Chapter 2: Literature Review 31
authorities, state organisations, and non-state local institutions (linking) (Adger,
2003). Under the social capital dimension, there are three resilience characteristics and
nine indicators. Three characteristics are: social cohesion, social support, and social
networks (Figure 2.5).
Social mechanisms/competencies/values:
Social mechanisms include the process of developing community goals, plans,
priorities, and engagement of the community in the resilience building process. The
process oriented resilience characteristics also include community competence,
collective attitude, and shared values towards coping and adapting to disasters. Under
the social mechanism/competencies/values dimension, there are five social resilience
characteristics and 15 indicators. The resilience characteristics include: community
engagement, community goals/efficacy, community shared values and attributes,
community processes, and community competence (Figure 2.5) (Cutter et al., 2010;
Khalili et al., 2015; Paton et al., 2001).
Social equity and diversity:
Eliminating excessive burden on marginalised communities due to inequitable
distribution of critical resources, and increasing equity and social justice, are core
principles of social resilience (Plough et al., 2013). When a disaster strikes, people
who do not have access to equitable resources, such as families living below the
poverty line, may be affected significantly differently than other people within the
same community (Fothergill & Peek, 2004; Lovell & Le Masson, 2014). Social
resilience also depends on the diversity of resources, because communities that rely
on a limited range of resources often struggle to cope (Norris et al., 2008), and less
socially-diverse communities encounter greater difficulties to recover from
disturbances (Ahern, 2011). There are three characteristics and nine indicators in
social equity and diversity. The three characteristics include: fair access to basic needs
and services, community inclusiveness and equality, and diverse skill sets and
workforce (Figure 2.5).
Social beliefs/culture/faith:
Not only human resources and physical assets, but local culture and social
beliefs can play a critical role in determining social resilience to disasters (Kwok et
al., 2016). Social beliefs need to be positively capitalised in communities that are
Chapter 2: Literature Review 32
oriented with their own local culture and faith systems (Kwok et al., 2016;
Ostadtaghizadeh et al., 2016). Social resilience frameworks developed in some
communities are strongly grounded in culture and faith. For example, Ostadtaghizadeh
et al. (2016) considered culture as a separate dimension of resilience. There are two
characteristics and four indicators in social beliefs/culture/faith. The characteristics
include: local cultural beliefs/norms and religious beliefs/norms (Figure 2.5).
SUMMARY AND IMPLICATIONS
The complex nature of the resilience concept, due to varied approaches has
further complicated the measurement of social resilience to disasters. Consequently,
the necessity of a consistent approach to measure social resilience to disasters has been
advocated by many researchers. The indicator approach has been broadly used in
recent research for measuring social resilience to disasters. However, social resilience
frameworks commonly capture easily accessible indicators while leaving out complex,
but key, resilience characteristics. Most of the proposed social resilience frameworks
have largely focused on outcome features of resilience rather than process related
indicators, mainly because process indicators are not easily measurable. A failure to
measure both, outcome and process features of resilience results in inadequate and
inaccurate assessment of social resilience. Hence, there is a need for developing a
social resilience framework that can integrate key process-oriented indicators for
adequate measurement of social resilience.
Further, due to the multi-faceted nature of resilience and complex
interconnections between social resilience characteristics, there is pronounced
difficulty in carrying out an effective and feasible resilience measurement within a
reasonable timeframe to achieve comprehensiveness and greater accuracy. Moreover,
the wide-ranging disparity of social resilience characteristics in different contexts
along with spatial and temporal variations, and complex inter-relationships among
these characteristics, challenge their direct measurability through a set of
comprehensive and definitive indicators. Therefore, new approaches should also
address the challenges in directly measuring social resilience due to their added
complexity.
Many outcome-oriented indicators of social resilience are primarily measured
using publicly available census data, which is not frequently updated. Hence, the
Chapter 2: Literature Review 33
existing measures provide a limited and often not accurate assessment of social
resilience (Figure 2.3 shows the links to key knowledge gaps from the critical literature
review). A time and resource effective practical approach needs to be employed that
can use regularly updated data such as administrative data to measure social resilience.
One of the approaches to overcome these limitations is to use a surrogate approach, as
it can facilitate the identification of key facets of a resilience indicator and can use
regularly updated locally available administrative data sources to measure them.
Hence, a new method such as the surrogate approach to measure social resilience
needs to be tested to address these challenges in measuring social resilience to
disasters.
In order to methodically select key social resilience indicators from multiple
social resilience dimensions for developing a surrogate approach, an integrated
framework such as the ‘5S’ framework developed in this study can be used. The ‘5S’
framework is very generic and adaptable, and can guide the selection of key social
resilience indicators to develop a surrogate approach in any context.
Chapter 3: Surrogate approach to assess social resilience to disasters 34
Chapter 3: Surrogate approach to assess
social resilience to disasters
This chapter consists of three sections.
Section 3.1 provides an overview of the surrogate approach. This includes a brief
introduction to the surrogate approach and analogue models in different disciplines,
and an analysis of existing frameworks, to develop a surrogate framework to assess
social resilience in a disaster context.
Section 3.2 details the surrogate development framework for assessing social
resilience indicators in a disaster context in three key steps. These are aligned with
three phases in this research, which are detailed in Chapter 4 (Research methods). The
following three key steps are discussed briefly in this section: A. Selecting key
resilience indicators that require surrogate approach, B. Identifying potential
surrogates, and C. Selecting the optimum surrogates for application by evaluating and
ranking potential surrogates.
Section 3.3 summarises the surrogate approach and application in disaster
management.
Figure 3.1. Chapter 3 and key sections in the thesis structure
Chapter 3: Surrogate approach to assess social resilience to disasters 35
AN OVERVIEW OF SURROGATE APPROACH
3.1.1 Defining surrogates
The use of a surrogate approach is an innovative way forward to overcome the
challenges and limitations highlighted in measuring social resilience to disasters as
discussed in Chapter 2 (Cutter, 2016; Kulig et al., 2013; Sharifi, 2016; Ziyath et al.,
2013). Developing and translating surrogate measures to real world applications to
measure resilience will help in effective disaster planning and resource allocation.
The surrogate approach has been successfully used in multiple disciplines and
contexts, such as clinical medicine, biodiversity, and environmental studies (Barton et
al., 2015; Lindenmayer et al., 2015b; Mellin, 2011). In ecology, a surrogate is defined
as “an ecological element or process that is used to represent another aspect of an
ecological system” (Barton et al., 2015, p. 393). Lindenmayer et al. (2015b) defined it
as a “component of the system of concern that one can more easily measure or manage
than others, and that is used as an indicator of the attribute/trait/characteristic/quality
of that system” (p. 1030). Hence, the surrogate method is used as a proxy measure to
understand the environmental conditions (Lindenmayer & Likens, 2011).
Resilience surrogates are defined by Bennett et al. (2005) as proxies in assessing
resilience that can be selected from measurable attributes in a social–ecological
system. For the purpose of this study, a surrogate is considered as an indicator or set
of indicators that effectively represents another indicator that is intended to be
measured (Miguntanna et al., 2010; Rodrigues & Brooks, 2007). This method enables
easier and more cost-effective measurement than measuring the target indicator
directly.
3.1.2 The use of surrogate approach
Table 3.1 shows the application of the surrogate approach in different disciplines
such as clinical medicine, biodiversity, social-ecological systems, and water quality.
For example, due to limited resources to track the changes in ecological systems, the
application of surrogates has evolved over time as a necessary and a cost-effective
way to assess ecological processes and ecosystem responses (Lindenmayer et al.,
2015b). In the surrogate approach, understanding and selecting the most effective
surrogate(s) for the indicator of measure is very important (Rodrigues & Brooks,
2007), because it will help to understand when or under which conditions the
Chapter 3: Surrogate approach to assess social resilience to disasters 36
surrogates can be best utilised (O’Loughlin et al., 2018a). For example, in clinical
medicine, cholesterol level as a quantitative measure is used for inferring a patient’s
health status and risk of a disease (Barton et al., 2015).
Surrogates are useful for several reasons. For example, the time required to
measure the target system can be much shorter with the surrogate, which is easier to
measure than the target system, and the sample size or the extent of the measurement
entity is much lesser for surrogates than for the target system (Asher et al., 2015;
Baker, 2005). Collectively, the application of surrogates, as shown in Table 3.1, is
useful to contextualise the rationale behind the surrogate approach. The surrogate
concept can be transferred to measure social resilience in a disaster context to
overcome existing challenges of measuring social resilience assessment methods
(Levine, 2014; Saja et al., 2019), as highlighted in Chapter 2.
In the surrogate approach, the surrogacy relationship between the surrogate and
the target indicator is important. Surrogacy is defined as the extent to which a
particular set of features (surrogates) effectively represents another set of features to
be measured (target) (Rodrigues & Brooks, 2007). Further, “a surrogate should be
consistent and repeatable, in the sense that independent observers given the same
information would assess the surrogate in the same way” (Carpenter et al., 2005, p.
942). The conceptual analogues of surrogate models applied in other disciplines are
discussed in the next section.
Table 3.1. Some examples of surrogate approach in other disciplines
Area of
research Examples of surrogate approach Reference
Water quality
surrogates
Turbidity as a surrogate for water quality
parameters
Schilling et al.
(2017)
Public health
An organism, particle, or substance as a
surrogate to study the fate of a pathogen in a
specific environment to improve public health
(Sinclair et al.,
2012)
Biodiversity
conservation
planning
Conservation planning based on a set of
biodiversity features as surrogates (using
species accumulation index)
Rodrigues and
Brooks (2007)
(Lindenmayer et
al., 2015a)
Clinical
medicine
Surrogates (blood pressure) used to predict the
clinical endpoints (example stroke risk).
Biomarkers as substitute for clinical endpoints.
Aronson (2005)
(Fleming &
Powers, 2012)
Chapter 3: Surrogate approach to assess social resilience to disasters 37
Resilience for
socio-
ecological
systems
Observable features and models of socio-
ecological systems (using stakeholder
assessment, model explorations, historical
profiling, and case study comparison)
Carpenter et al.
(2005)
Resilience surrogates through development of
system models (systems are qualitative and the
relationship is quantified)
Bennett et al.
(2005)
Conceptual analogues for surrogate model in social resilience
This section explores how the surrogate approach is applied in other disciplines,
so as to conceptualise the surrogate approach to measure social resilience indicators
in a disaster context. There is evidence to suggest that existing social resilience
measurement methods have similar conceptual and methodological challenges in
ecology and clinical medicine.
For example, a systematic surrogate approach has been used in clinical medical
sciences for many decades (Barton et al., 2015). In clinical medicine, the causal
framework is built on the basic naïve, general, and composite models, with increasing
complexity of linkages, as shown in Figure 3.2. The naïve model links the effect of
the treatment (T) to the outcome (O), the treatment to the surrogate (S), and the
surrogate to the outcome. In comparison, the general model incorporates another
source of variability (U) on the surrogate and response variables. The most complex
type is the composite model that links additional covariates (denoted by X and L) and
their interrelated effects on the surrogate and response variables (Barton et al., 2015).
Similar models can be drawn for social resilience indicators and potential surrogates.
However, it is necessary to start with the basic naïve model in the social resilience
context, since the surrogate research has not been tested before to develop complex
composite models.
Figure 3.2. Graphical representation of surrogate approach models
reproduced from Barton et al. (2015, p. 394)
Chapter 3: Surrogate approach to assess social resilience to disasters 38
Barton et al. (2015) have applied the surrogate concept from clinical medicine
to ecology, and provided an ecological analogy for the surrogate model used in
medical sciences. Figure 3.3 highlights an example of conceptual analogous surrogate
models in clinical medicine, ecology, and in social resilience to disasters adapted from
Barton et al. (2015). For example, in clinical medicine, the stroke risk can be predicted
by measuring elevated blood pressure as a surrogate measure. In ecology, the desired
environmental state can be measured using lichen instead of measuring environmental
pollutants. Similarly, in the social resilience literature, social cohesion can be
measured using legal cases/complaints against neighbours or community members as
a potential surrogate instead of measuring social trust, which is an abstract and multi-
faceted social resilience indicator. The data can be accessed from regularly updated
data sources, such as administrative records available from local authorities or legal
enforcement authorities.
The use of a surrogate approach to measure social resilience can potentially
resolve the measurement issues in disaster resilience (Kulig et al., 2013). The surrogate
approach can be applied to social resilience measurement, similar to the use of the
surrogate approach to measure resilience in ecology. A robust surrogate development
framework is needed that can be used systematically to conceptualise, identify, and
evaluate surrogates in a disaster context, so as to overcome current conceptual
complexity and methodical constraint in measuring social resilience. The surrogate
Figure 3.3. Conceptual analogous surrogate model examples in clinical
medicine, ecology, and social resilience to disasters; adapted from Barton
et al. (2015) (p. 394)
Chapter 3: Surrogate approach to assess social resilience to disasters 39
thinking applied in ecology and recent evolution of surrogate frameworks that are
flexible for application in a multidisciplinary context will be used to guide this process,
as detailed in the next section.
A number of limitations were also identified in the application of surrogate
approach in other fields. For example, generalising the surrogates in different contexts
is one of the key challenges, which needs cautious interpretation of surrogate
relationship to the target (Grantham et al., 2010). However, O’Loughlin et al. (2018a)
highlighted that considerable variability and context dependency always exist in
environmental science and the application of similar surrogates in different contexts
can be overcome by adapting the framework through rigorous evaluation and
appropriate validation techniques. When a new surrogate is identified, it is necessary
to calibrate it with the existing surrogate for its robust application (Lindenmayer et al.,
2015b), which requires active learning and improvements in surrogate application
through continuous engagement of key stakeholders.
Another challenge in surrogate approach is the regular update of surrogate
information over time (Tulloch et al., 2016). Hence, the final selection of surrogate(s)
for real world application depends on the surrogate information sources that are
regularly updated, such as local administrative data. Potential surrogates can be
explored to measure sets of social resilience indicators by consulting key disaster
management stakeholders as a one-off exercise. Once the final set of surrogates has
been selected, they can be periodically updated in consultation with the relevant
agencies at the local level to capture any changes, so that resilience can be robustly
measured without repeatedly undertaking resource- and time-intensive processes.
3.1.3 Review of existing frameworks to develop a surrogate development
framework
There are a wide range of surrogate approaches proposed and used in
environmental science, such as Rodrigues and Brooks (2007), Carpenter et al. (2005),
Berkes and Seixas (2005), Bennett et al. (2005), Lindenmayer and Likens (2011), and
Lindenmayer et al. (2015b). Most of these approaches are very specific to the field of
study, as previously detailed in Table 3.1, and are very difficult to apply directly in a
disaster context. For example, Berkes and Seixas (2005) used case studies to identify
key factors influencing lagoon systems, and Bennett et al. (2005) used system models
to extract potential surrogates. These frameworks do not provide a common method
Chapter 3: Surrogate approach to assess social resilience to disasters 40
for developing a surrogate approach that can be easily adapted for other disciplines.
Two frameworks were selected for detailed review to develop a suitable surrogate
development framework to use in a disaster context.
(1) An adaptive surrogate framework by Lindenmayer et al. (2015b)
The first framework reviewed is the adaptive surrogate framework proposed for
the identification, evaluation, and application of environmental surrogates by
Lindenmayer et al. (2015b, p. 1033) (See Figure 3.4). This framework is a
comprehensive and adaptable framework compared to other surrogate frameworks,
which are mostly specific to the discipline. This framework was proposed based on
key lessons from applying varying methods of surrogate approach. It was also an
outcome of a collaborative and consultative process with many researchers who
developed surrogate approaches in environmental science (Lindenmayer et al.,
2015b).
The purpose of Lindenmayer et al. (2015b) framework is to guide methodical
identification, evaluation and selection of robust surrogates for application to measure
and monitor target ecological systems. The generic structure of the framework, which
Figure 3.4. Adaptive Surrogacy Framework
Lindenmayer et al. (2015b, p. 1033)
Chapter 3: Surrogate approach to assess social resilience to disasters 41
organises the key steps of surrogate development in a logical sequence for easy
adaptation to other disciplines, taking into account the iterative nature of surrogate
development, are the key strengths of the Lindenmayer et al. (2015b) framework
compared to other surrogate frameworks developed specific to a discipline. However,
the structuring of key steps 1 to 3 more consistently with key steps 4 and 5 can help to
adapt it easily to any context. Further, the Lindenmayer et al. (2015b) framework was
developed in the context of advancing the surrogate approach in ecology by unifying
different types of surrogate applications. Hence, this framework requires adaptation to
develop surrogates in new disciplines such as resilience measurement in disaster
management, which has not applied a surrogate approach to date.
Lindenmayer et al. (2015b) framework consists of eight key steps in developing
environmental surrogates:
1. Identify objectives: Firstly, it is important to define an objective that needs to be
addressed with respect to measuring an ecological system that is difficult to
measure directly.
2. Engage stakeholders: Identifying and engaging stakeholders in all phases of
surrogate development is important to capitalise on collective and diverse
perspectives.
3. Develop conceptual model for the target system: An important step in identifying
effective surrogates is to develop a good model of the target system with key
ecological processes.
4. Identification of surrogates: The identification of potential surrogates for the
selected ecological processes that are difficult to measure directly includes
designing a sampling strategy and key benchmarks or trigger points for
interventions.
5. Evaluation of surrogates: Evaluation of potential surrogates identified in the
previous step is critical. This includes: a) asserting the scientific validity of
surrogates; b) comparison of costs and benefits of surrogate measurement; and c)
undertaking a risk assessment.
6. Selection of surrogates: The iterative process between identification and evaluation
of surrogates will finally result in the selection of optimum surrogates that meets
the objective identified in the first step.
Chapter 3: Surrogate approach to assess social resilience to disasters 42
7. Application of surrogates: The selected surrogates need to be applied in real-world
scenarios.
8. Active learning: Active learning is a continuous process throughout all the key steps
for improving the surrogate development process.
Though all the key steps are relevant for developing surrogates in a disaster
context, some necessary adaptations in key steps need to be considered. Further, some
of the sub-steps proposed within very critical key steps such as the identification and
evaluation of surrogates (Key steps 4 and 5) need a detailed review to adapt them
appropriately in a disaster context. In order to see the relevance of these steps in a
disaster context, an indicator development framework proposed for vulnerability
assessment in disaster management was also selected for review in this study. A
comparison of the logical sequence and relevance of both frameworks can provide a
good understanding to structure surrogate development framework in a disaster
context. In the next section, review of a vulnerability indicator development
framework of Birkmann (2013) used in a disaster context is explained.
(2) Vulnerability indicator development framework by Birkmann (2013)
The second framework reviewed in this study is the vulnerability indicator
development framework, which is a concept that is closer to resilience in disaster
management. In the disaster management literature, Birkmann (2013) proposed nine
steps for developing vulnerability indicators, as shown Figure 3.5.
Figure 3.5. Vulnerability indicator development framework
Birkmann (2013, p. 94)
Chapter 3: Surrogate approach to assess social resilience to disasters 43
1. Defining goals: Indicator development process needs to start with defining or
selecting the relevant goal.
2. Scoping: Once the goals are defined, it is important to clarify the scope of indicator
by identifying the context, including the target groups and boundaries of
application.
3. Choose indictor framework: This involves identification of conceptual target
system and structuring the themes for the target system.
4. Define selection criteria: Next step involves selecting a set of general criteria for
identifying good-quality indicators.
5. Identify potential indicators: This is the key step, where a set of potential indicators
to measure the target system needs to be identified.
6. Choose a final set of indicators: Based on the criteria selected in step 4, potential
indicators need to be evaluated for selecting the final set of indicators for
application.
7. Analyse indicator results: Data collection for the indicator will be done in this step
to validate the applicability of the indicator results.
8. Prepare and present report: A final report will be prepared based on the analysis
results in step 7.
9. Assess indicators performance: The final step of indicator development is to assess
the performance of the indicator selected and applied in real context to further
improve its performance in the next step.
The comparison of key steps in both frameworks helped to select the key steps
required in a surrogate development framework for assessing social resilience to
disasters.
Comparison of key steps in both frameworks for adapting them to disaster context
A comparison of key steps in both frameworks is listed in Table 3.2, which
shows little variations in most of the key steps in both frameworks, although both are
used in different contexts. Some minor differences exist; for example, use of criteria
trade-offs for environmental surrogate evaluation as an integrated process within the
proposed framework by Lindenmayer et al. (2015b), as opposed to a separate key step
Chapter 3: Surrogate approach to assess social resilience to disasters 44
– ‘selection criteria’ by Birkmann (2013) to evaluate social vulnerability indicators
(Key step 4). Further, the final three steps (step 7, 8 and 9) in the vulnerability indicator
development framework (Figure 3.5) are: analysis of indicator results; preparation of
report; and assessment of indicator performance. In the Lindenmayer et al. (2015b)
adaptive surrogacy framework, these steps are not included, but general final steps
(step 7 and 8) are included as ‘application’ and ‘active learning’.
Table 3.2. Comparison of key steps in indicator/surrogate development frameworks
Key steps in vulnerability indicator
development (Birkmann, 2013, p. 94)
Key steps in surrogate development
(Lindenmayer et al., 2015b, p. 1033)
1 Defining goals 1 Identify objectives
2 Clarifying the scope by identifying
the target group and purpose 2 Identify and engage stakeholders
3 Identifying an appropriate
conceptual framework 3
Develop a conceptual model for the
target system
4 Defining selection criteria - Trade-offs integrated with key steps
5 Identification of potential indicators 4
Identification of potential
surrogates (benchmarks and
sampling approach)
6 Evaluation and selection of each
indicator using evaluation criteria 5
Evaluation of surrogates (scientific
validity, cost effectiveness, risk
assessment)
7 Analyse indicator results 6 Selection of surrogates
8 Prepare and present report 7 Application of selected surrogates
9 Assess indicator performance 8 Active learning throughout the
process and improvement
This comparison shows that key steps for the social resilience surrogate
framework can be developed from the adaptive surrogate framework by Lindenmayer
et al. (2015b) with proper contextualisation for use in a disaster context. Therefore,
the general key steps in surrogate development in a disaster context can include:
selection of resilience indicator to develop surrogates; identification of potential
surrogates; and evaluation of surrogates to select the best performing surrogate for
application.
Chapter 3: Surrogate approach to assess social resilience to disasters 45
The method of using the criteria for evaluation of potential surrogates in a
disaster context needs to be decided, since it is used in different ways depending on
the context. Defining criteria and evaluation were taken as separate steps (key steps 4
and 6) in the framework by Birkmann (2013), whereas the criteria trade-offs are
integrated in the Lindenmayer et al. (2015b) framework, since they are not explicitly
considered in surrogate evaluation.
The key steps 4 and 5 of Lindenmayer et al. (2015b) are the most critical in
surrogate development. Hence, some of the sub-steps proposed in two key steps (Key
step 4: Identification of potential surrogates and Key step 5: Evaluation of potential
surrogates) in the adaptive surrogate framework proposed by Lindenmayer et al.
(2015b) need further consideration when adapting them, to ensure compatibility with
the most relevant components for resilience measurement in a disaster context. Each
of the sub-steps that are adapted to formulate a surrogate development framework in
a disaster context is discussed below.
Key step 4 – Identification in Lindenmayer et al. (2015b) framework (Figure 3.4):
(1) Sub-step - Benchmarks/triggers (In key step 4 of Figure 3.4): In an ecological
context, benchmarking of surrogates is required to measure the target indicator, which
depends on the understanding of the study system (Lindenmayer et al., 2015b). The
measure of resilience is either based on the existing status (inherent resilience), in a
pre-disaster phase, or how people adapted in new efforts to recover from the disaster
impacts in the post-disaster phase (adaptive resilience) (Cutter, 2016). The baseline
status of social resilience can be measured by the potential surrogates, as proposed in
this research. However, the dynamic status of the baseline, which frequently changes
its status over time due to changing complex social systems, is an enormous challenge
to determine the baseline condition and benchmarking (Brown et al., 2018). Therefore,
in the disaster context, the surrogate measures can help to monitor the progress of
resilience status (Cutter et al., 2010), instead of benchmarking social resilience to a
threshold limit, which is often challenging. Hence, the understanding of the surrogacy
relationship between the surrogates and the target indicator is proposed to be included
as a sub-step, as it allows the establishment of a good measure of a target indicator
using existing resilience conditions through the surrogate approach.
Chapter 3: Surrogate approach to assess social resilience to disasters 46
(2) Sub-step - Sampling approach (In key step 4 of Figure 3.4): The measurement of
ecological surrogates can be done by a sampling approach, since surrogates are also
mostly measured through empirical methods. However, the sampling approach at the
initial stage of identifying social resilience surrogates can be difficult without a proper
understanding of surrogate measurement protocols. Even in developing resilience
surrogates in ecology, Carpenter et al. (2005) highlighted four different methods to
identify surrogates: stakeholder assessment; model development; historical profiling;
and case study comparisons. To decide a method for identification of surrogates for
social resilience measurement in a disaster context, it is most appropriate to be flexible
when deciding on an effective measurement method, since a surrogate approach for
resilience assessment in disaster management is still at the exploration stage. Hence,
the need for a sampling approach can be decided based on the proposed surrogate
measurement protocols. Hence, inclusion of surrogate measurement protocols as
another sub-step in the identification of potential surrogates is more appropriate to
measure social resilience using a surrogate approach in a disaster context.
Key step 5 – Evaluation in Lindenmayer et al. (2015b) framework (Figure 3.4):
(3) Sub-step - Scientific validity (In key step 5 of Figure 3.4): The evaluation of
scientific validity for environmental surrogates is a process using methods such as
experiment and observation (Lindenmayer et al., 2015b). However, the validity and
applicability of social resilience surrogates in a disaster context are either driven by
expert judgement or through locally driven approaches at the community levels (Tyler
et al., 2016). The initial identification of potential surrogates in this study was
proposed to be done through locally driven approaches, such as consulting disaster
management practitioners and policy makers working at the community and sub-
national levels. Hence, an evaluation of potential surrogates is proposed to be carried
out against a set of surrogate evaluation criteria such as accuracy and communicability,
with consultation with a wide range of disaster management experts from a variety of
cohorts (such as researchers, policy makers, and practitioners) to increase their
robustness and validity for application.
(4) Sub-step - Risk assessment (In key step 5 of Figure 3.4): A risk assessment for
identified ecological surrogates may be necessary, since the negative consequences of
applying the wrong surrogate for intervention decisions will be high (Lindenmayer et
al., 2015b). In a community disaster resilience measurement context, interventions and
Chapter 3: Surrogate approach to assess social resilience to disasters 47
investment decisions are necessary for most, if not all, of the potential surrogates based
on their baseline status. However, in reality, there is a need to prioritise resilience
interventions, due to resource constraints such as human and financial. Many
researchers such as Alshehri et al. (2015b), Carone et al. (2018), and Orencio and Fujii
(2013) ranked and prioritised resilience indicators using multi-criteria decision
making tools in a disaster context. Therefore, it is more appropriate to apply similar
approaches to rank potential surrogates to prioritise resilience building interventions.
Further, the selection of surrogates (key step 6 in Lindenmayer et al. (2015b)
framework) is the end result of the surrogate evaluation process (key step 5 in
Lindenmayer et al. (2015b) framework). Therefore, it is more appropriate to include
‘selection of surrogates’ as part of the key step – ‘evaluation of surrogates’ for
resilience assessment in a disaster context.
A surrogate development framework to measure social resilience to disasters
was created by considering the necessary adaptations to the Lindenmayer et al.
(2015b) framework, as explained above, for its application in disaster management.
From this analysis, a surrogate development framework was proposed for testing, to
assess social resilience in a disaster context, which is discussed in the next section.
A SURROGATE DEVELOPMENT FRAMEWORK FOR ASSESSING
SOCIAL RESILIENCE TO DISASTERS
The proposed surrogate development framework to measure social resilience to
disasters is shown in Figure 3.6. The proposed social resilience surrogate development
framework has three components, which will form the three key steps in the surrogate
development process (see Figure 3.6):
Key step A. Selection of social resilience indicators for surrogate development
Key step B. Identification of potential surrogates for the selected key indicators
Key step C. Selection of optimum surrogates for application in a disaster context
Stakeholder engagement and continuous learning/improvement spans across all
three key steps of the framework. This is because consultation with key stakeholders
is important as a way to obtain the necessary and on-going inputs in each respective
key step (A to C). Further, it is important to continuously improve the framework from
the lessons and new learnings when they are applied in different disaster contexts. The
details of key steps (A to C) and their sub-steps are discussed in the next sections.
Chapter 3: Surrogate approach to assess social resilience to disasters 48
Figure 3.6. Surrogate development framework to assess social resilience in a disaster context
Chapter 3: Surrogate approach to assess social resilience to disasters 49
3.2.1 Selection of resilience indicators for surrogate development (Key step A)
In key step A, two sub-steps are proposed to guide the logical decision making
for surrogate approach: (a) identification of key social resilience indicators; and (b)
the decision for surrogate approach.
A.1. Identification of key social resilience indicators
There are numerous and wide-ranging social resilience indicators. For example,
Saja et al. (2018) identified 46 key social resilience indicators in five dimensions of
resilience. However, in a particular context, certain key indicators are more important
than others, and have to be prioritised, due to resource and time limitations in
measuring all the key indicators. A feasible number of key social resilience indicators
needs to be initially agreed. This can be done either through consultation with the key
stakeholders, or through a review of available information sources on social resilience
measurement before initiating the surrogate identification process. In this study, a set
of key social resilience indicators to apply a surrogate approach was identified through
a review of literature on social resilience indicators, and is detailed in Section 4.3.
A.2. Decision for surrogate approach
As shown in Figure 3.7, the key reasons guiding the choice of surrogate
approach include:
a) When the process of existing measures for assessing a target indicator through direct
measurement is time and resource intensive (in financial and human terms)
(Lindenmayer & Likens, 2011); and/or
b) When the existing indirect measures use publicly available census data, which
mostly produce index based quantitative measures that are limited with good
qualitative interpretations to provide a good enough resilience measurement
(O’Loughlin et al., 2018b).
It was found in the review of existing social resilience measures that the two
reasons explained above are mostly true for process-oriented resilience indicators.
Further, outcome-oriented resilience indicators often provide limited measures, since
they use census data, which is not frequently updated. In such situations, outcome-
oriented resilience indicators can also be measured by using surrogates with the help
of most frequently updated administrative data.
Chapter 3: Surrogate approach to assess social resilience to disasters 50
The context-specific nature of resilience means that the measurement of
resilience is bound by temporal and spatial scales (Mitchell & Harris, 2012). Hence,
the surrogates identified in a disaster context should be applicable in different
geographic contexts and in different disaster phases. Once the surrogate approach to
measure social resilience to disasters is conceptualised, the objective of surrogate
measurement can be defined by setting the boundaries/scope, such as the geographical
and disaster context, within which the identified surrogates will be applicable. Once
the decision for a surrogate approach is made, the next key step (key step B in the
surrogate development framework in Figure 3.6) is to identify potential surrogates to
measure the selected social resilience indicators.
3.2.2 Identification of potential surrogates for selected indicators (Key step B)
Key step B is focused on the identification of potential surrogates for the selected
key indicators. This is an important step in the surrogate development framework,
because identifying as many potential surrogates as possible at the initial stage will
help to select the best surrogates through evaluation. It is important to check the
relationship between the surrogate and the target indicator and assess how stronger
and sensitive this relationship is, in order to ensure the initial validity of all potential
surrogates. Key step B has the following three sub-steps (as shown in Figure 3.8) and
each of them is explained below.
Figure 3.7. Surrogate approach decision flowchart (Key step A)
Chapter 3: Surrogate approach to assess social resilience to disasters 51
Figure 3.8. A framework to identify potential surrogates for social resilience indicators in a disaster context (Key step B)
Chapter 3: Surrogate approach to assess social resilience to disasters 52
B.1. Explore all potential surrogates,
B.2. Establish the surrogacy relationship, and
B.3. Determine protocols for surrogate measurement.
B.1. Exploring all potential surrogates
There are three elements when exploring all potential surrogates:
(1) Selection of a context:
Initially, a context for exploring surrogates needs to be established. Establishing
context includes selecting a site (geographical context), which includes urban/rural, or
coastal/inland/mountain area, as measures will differ depending on geographic
settings, and type of disasters (single or multi hazard). Resilience measures are mostly
context specific, which often vary with different types of disasters and the target
group/entity (local authority level, sub-national, or national), although there are many
common indicators and surrogates that can be identified (Ostadtaghizadeh et al., 2015;
Sharifi, 2016). Detailed explanation of the selection of case study context in this
research is explained in Section 4.5.
(2) Sampling of experts in disaster management:
Experts who are local policy makers and practitioners working in disaster risk
reduction can be purposefully sampled for data collection. For example, the experts
should have a minimum of three years of experience in disaster management projects.
Many bottom-up and locally driven frameworks developed to measure indicators
highlight the need for consulting key stakeholders relevant to the study, in order to
obtain good insights into the phenomenon being explored (Reed et al., 2006). This will
assist in making the frameworks and the measures widely applicable in practice.
Detailed explanation of the sampling method is given in Section 4.5.
(3) Consult experts for data collection:
Once the context is set and the experts are selected, an appropriate data
collection method to consult experts needs to be decided. Many common expert
consultation methods in a disaster management context, such as through key informant
interviews, interest group discussions, and participatory workshops, can be done in the
selected study locations (Keating et al., 2017). In this research, one-on-one interviews
and group interviews were used in the selected case study areas, and are explained in
Section 4.5.
Chapter 3: Surrogate approach to assess social resilience to disasters 53
B.2. Establish surrogacy relationship
In the next step, once all the potential surrogates are identified, the surrogacy
relationship for each potential surrogate with the target indicator needs to be
established. There are three key elements in this sub-step B.2:
(1) How surrogate relates to target indicator (surrogacy relationship):
Surrogacy relationship is defined as the extent to which a particular set of
features (surrogates) effectively represents another set of features of the target
indicators (Rodrigues & Brooks, 2007). This relationship between target indicator and
the proposed surrogate needs to be established from discussions with the experts.
Experts can be requested to provide examples for the proposed surrogates to establish
their relationship with the target indicator. A descriptive explanation can be given by
providing the quotes from the interview transcripts or from discussion records and to
link it with the existing literature or secondary data sources such as reports.
(2) Strength of the surrogacy relationship:
The quality and effectiveness of surrogate(s) depend on the strength of the
surrogacy relationship between the target indicator and surrogates (Grayson et al.,
1996). The higher the strength of this association between the surrogate and the target
indicator, the lesser the likelihood of misinterpreting the inference of the target
indicator (Lindenmayer et al., 2015a). Due to the multifaceted and dynamic nature of
social resilience, the most suitable method to understand the surrogacy relationship is
to use open-ended questions to explain the surrogacy relationship. Some challenges in
quantifying resilience, such as a lack of good explanation, also exist in quantifying the
surrogacy relationship. Therefore, interview participants can be requested to establish
the link between each surrogate and the target indicator , so that rich qualitative data
can be collected to overcome the limitations in quantifying the surrogate relationship
(Jones & Tanner, 2017).
(3) Sensitivity of the surrogacy relationship:
Measuring social resilience indicators in a disaster context through potential
surrogates can become complex due to multifaceted linkages between multiple
surrogates. The relationship of a potential surrogate with the target indicator is
complex in nature, such as; one surrogate is connected to the target indicator or to
other surrogates, and how changes in the surrogacy relationship may impact the target
indicator (Lane et al., 2015). It may become difficult to measure the target indicator
Chapter 3: Surrogate approach to assess social resilience to disasters 54
with the proposed surrogate, if there is a complex relationship between the identified
surrogates. Therefore, the aim should be to identify a unique set of key facets of the
target indicator which can be used as surrogates, so that the inter-linkages between
surrogates are minimal and do not make their measurement complex.
B.3. Protocol for measuring surrogates
One of the key justifications for the use of a surrogate approach is to enable the
use of frequently updated data sources so as to overcome the limitations in direct
measurement or publicly available census data sources. Therefore, the protocol for
measuring potential surrogates needs to be identified. Hence, the protocol to guide the
measurement of surrogates involve the following three elements:
1) Type of measurement:
The new approaches to assess and monitor resilience at regular time intervals
increasingly recognise and recommend a mix of qualitative and quantitative
approaches. However, more emphasis is given to provide enough evidence with the
existing data to measure the surrogates (Schipper & Langston, 2015). Therefore,
provision of sufficient qualitative interpretations of the existing status of the surrogate
will assist in translating the surrogate measure into resilience enhancement activities
for practical implementation. This has to be decided through expert consultation and
past experience.
2) Method for accessing accurate data:
The data collection method for a surrogate approach should be easier than that
used for direct measurement of resilience, such as household surveys, since they are a
resource and time intensive process and should be from sources that are more
frequently updated than census data. Therefore, the method of accessing available data
can include: primary data collection methods using a sampling approach from the
existing projects in the selected regions, or secondary data such as the regularly
updated administrative data from local state departments and authorities; a
combination of both can be explored for measuring resilience through surrogates
(Tyler et al., 2016).
3) Reliable sources for surrogate data:
In most of the local government and administrative bodies, the most frequently
updated administrative data is available, since it used by the authorities to monitor
Chapter 3: Surrogate approach to assess social resilience to disasters 55
their project goals and progress (Tyler et al., 2016). Therefore, it is necessary to source
data from non-traditional sources (for example administrative or project data), when
the publicly available census data is outdated, which has been the case in most
developing countries.
After the completion of key step B in the surrogate development process, which
includes three sub-steps as explained above, the next step (Key step C) is to evaluate
identified potential surrogates and rank them to select the optimum set of surrogates
for application.
3.2.3 Selection of optimum surrogates for application (Key step C)
Key step C involves the selection of the optimum surrogates for application, and
is the final step in the surrogate approach (as shown in Figure 3.6). The surrogates
must be evaluated independently against a set of criteria to determine optimum
surrogates that perform well in all criteria (Lindenmayer et al., 2015b). In the next
step, the ranking of surrogates can be done using multi-criteria decision making.
Finally, a set of surrogates can be selected based on priority rankings and contextual
requirements to achieve the final objective of assessing social resilience.
In this research study, the key step C of the surrogate development framework
(Figure 3.6) was extended to include all required elements for testing, as shown in
Figure 3.9. It has three distinct sub-steps: C.1. Evaluation of potential surrogates
against key surrogate evaluation criteria; C.2. Ranking of surrogates; and C.3.
Selection of optimum surrogates for application. These are detailed below.
C.1. Evaluation of potential surrogates
When the identification of potential surrogates for the selected key social
resilience indicators is completed in key step B, these have to be evaluated against a
set of key criteria to select the surrogates that have optimum performance in all criteria.
This sub-step has three components as shown in Figure 3.9: (1) Five surrogate
evaluation criteria; (2) Selection of experts for judgement; and (3) Design of
measurement (evaluation scale). A brief explanation of the above three components is
provided below. A detailed explanation of the research method for this sub-step is
detailed in Section 4.6.
Chapter 3: Surrogate approach to assess social resilience to disasters 56
Figure 3.9. Sub-steps to select optimum surrogates to assess social resilience indicators in a disaster context (key step C)
Chapter 3: Surrogate approach to assess social resilience to disasters 57
(1) Five surrogate evaluation criteria
The identification of all potential surrogates in key step B through a consultative
process with disaster management practitioners and policy makers will ensure their
initial validity for application in practice. In this step, the robustness of surrogates for
practical application can be judged by consulting higher level experts working in
disaster management at national and international levels. Some key criteria for
selecting good surrogates include accuracy, sensitive to the change, cost-effective,
easy to communicate, and capable of being updated regularly (Birkmann, 2006;
Custance & Hillier, 1998). Each surrogate should be assessed against each criterion
independently. The five selected surrogate evaluation criteria are discussed below in
detail.
Development of surrogates need to be guided by a set of key qualifying criteria
for the selection of rigorous surrogates to measure social resilience effectively. Five
key evaluation criteria were established from the set of surrogate selection trade-offs
proposed by Lindenmayer et al. (2015b), in evaluating the environmental surrogates
and standard indicator development criteria used in the vulnerability assessment
context by (Birkmann, 2013). The key criteria in trade-offs proposed by Lindenmayer
et al. (2015b) include: accuracy, communicability, cost-effectiveness, and time
sensitivity. These are similar to the criteria used in a disaster vulnerability assessment
context. For example, good surrogates should be able to easily measure the target
indicator, be sensitive to different time periods, easily understandable to users, and
cost-effective for collecting data (Maclaren, 1996). Hence, the following five key
criteria to evaluate surrogates in measuring the target social resilience indicators were
established by drawing from the surrogate and disaster management literature as
highlighted above (Figure 3.10- Surrogate evaluation criteria pentagon).
1. Accuracy of the surrogate: The link between the indicator and the target is an
important criterion for making a decision on effective indicators (Mitchell, 2013).
Further, the precision of a measurement implies the level of credibility of the indicator.
A surrogate is credible when it has high accuracy in predicting the target indicator,
and it should be able to provide appropriate information on the target indicator
intended to be measured.
Chapter 3: Surrogate approach to assess social resilience to disasters 58
Hence, the level of accuracy between the surrogate and the target resilience indicator
is an important criterion in selecting best surrogates. Experts can determine accuracy
by understanding the perceived strength of the surrogate with the target indicator.
2. Cost-effectiveness of the surrogate: The cost of measuring an indicator is typically
related to time, personnel, and logistics costs associated with data collection,
processing, and analysis (FAO, 2008). These costs may vary significantly based on
the target indicator of measure and data collection method. Often, the use of low-cost
indicators may imply difficult trade-offs in terms of their accuracy and credibility,
which needs to be considered in selecting indicators. Calculating the cost of collecting
any given indicator is relatively straightforward, but the benefits associated with that
additional piece of information may be difficult to define and quantify (FAO, 2008).
Hence, each surrogate needs to be examined for cost-effectiveness, and they can be
based on readily available data or be available at a reasonable cost through a brief
consultative process with key stakeholders.
3. Time sensitivity: It is necessary to clearly identify temporal variations of resilience
surrogates in a disaster context. An effective indicator should be able to measure the
progress or trend in different time periods (Mitchell, 2013) and be responsive to
change. In a disaster context, a surrogate should be able to respond in all three key
phases (preparedness, response, and recovery), so that the resilience characteristic is
consistently detectable, without losing its robustness. Surrogates should be capable of
being updated at regular time intervals (Donnelly et al., 2007), particularly in the
preparedness phase so that they can be monitored periodically. Time sensitivity of the
selected surrogate is therefore another criterion for surrogate evaluation.
Figure 3.10. Surrogate evaluation criteria pentagon
Chapter 3: Surrogate approach to assess social resilience to disasters 59
4. Measurement complexity: Availability of data and accessibility of the data are
important factors to consider when selecting any indicator (EC, 2015). Availability of
accessible data so that they become easily applicable in practice is often emphasized
by practitioners (Birkmann, 2006). When a surrogate is selected, it is important to
understand what data is available to measure the surrogate indicator and can be easily
obtained to predict the target resilience indicator. It is important to find the right
balance between the accuracy of data and the limited availability of data (Birkmann,
2006).
5. Communicability: Any indicator should be able to communicate the required data
to a wide range of stakeholders (practitioners, policy makers, and researchers) engaged
in measuring social resilience. An indicator should be simple to communicate while
being scientifically sound and valid (Mega and Pedersen, 1998). The task of any
indicator is also to relay complex information in an accurate and understandable
manner so that decision makers can make informed decisions (Donnelly et al., 2007).
(2) Selection of experts for judgment:
A number of experts who have experience in disaster management projects and
research can be approached to evaluate the potential surrogates against the five
surrogate evaluation criteria. To increase the validity of evaluation results, a wide
range of experts from different cohorts of the disaster management sector, such as
practitioners, policy makers, and researchers, can be invited to provide their
judgement.
(3) Design of measurement:
The measurement to evaluate potential surrogates is a five-point Likert scale that
will denote the degree of agreement from very high to very low. For each of the social
resilience indicators, experts will be requested to provide their judgement on the Likert
scale as to how they think each surrogate will perform against each of the five criteria.
The ordinal qualitative scale used for rating can be converted for quantitative analysis
in multi-criteria decision making to rank the potential surrogates.
C.2. Ranking of potential surrogates
The ranking of potential surrogates is determined by a multi-criteria decision making
process. This sub-step consists of three elements and is discussed below. A detailed
explanation of each element with its research method is provided in Section 4.6.
Chapter 3: Surrogate approach to assess social resilience to disasters 60
(1) Criteria weighting:
Based on the importance of each criterion (Figure 3.10), different weights can
be applied to each of the five surrogate evaluation criteria. If the evaluator thinks that
all five criteria are equally important, an equal weight can be applied. The experts can
also be asked to rate the importance of criteria through pair-wise comparisons. The
consolidated pair-wise comparisons of experts can be analysed using multi-criteria
decision analysis techniques, such as the Analytical Hierarchical Process (AHP), to
determine the weights for the criteria.
(2) Multi-Criteria Decision Analysis (MCDM):
Once the independent evaluation is completed, a multi-criteria decision making
method can be employed to select the best surrogate indicators to measure the required
social resilience characteristic (Ziyath et al., 2013). The Multi-Criteria Decision
Making (MCDM)/Multi-Criteria Decision Analysis (MCDA) tool is designed to
evaluate several possible decisions or items against multiple, but often conflicting,
criteria that can identify the best possible decision.
(3) Ranking of potential surrogates against the criteria:
Hence, an MCDA method such as PROMETHEE (Preference ranking
organisation method for enrichment evaluation) can provide a ranking for potential
surrogates evaluated by experts. A sensitivity analysis can also be carried out with
equal weights and consolidated weight obtained from experts to understand the
influence of criteria weights in surrogate ranking. Ranking preferences of different
cohorts of experts can also be analysed to understand if there are any differences in
preferences of potential surrogates.
C.3. Selection of optimum surrogates for application
Finally, in practice, not all potential surrogates perform well when evaluated
against all the criteria. Hence, selecting the best indicators require compromises in
their performance against five surrogate evaluation key criteria: accuracy, cost-
effectiveness, time-sensitivity, measurement complexity, and communicability. The
selection of surrogates that perform optimally in all criteria can reduce the chances of
poorly performing surrogates being selected for application (Lindenmayer et al.,
2015b). This can limit the risk of errors in interpreting the target resilience indicator.
Hence, multiple surrogates can also be selected based on the final ranking against all
five evaluation criteria, for comprehensive measurement of the target indicator.
Chapter 3: Surrogate approach to assess social resilience to disasters 61
However, the priority should be given to apply the first ranked surrogates, which were
selected through a robust identification and evaluation process.
SUMMARY
The surrogate approach has been successfully tested in a number of fields such
as ecology and clinical medicine, to predict parameters that are complex for direct
measurement. Surrogates can adequately represent a target indicator that is difficult to
measure, since surrogates are described through the identification of key facets of
target indicators. A conceptual surrogate framework to measure resilience indicators
was proposed and include three key steps: A. Selecting key resilience indicators that
require surrogate approach; B. Identifying potential surrogates; and C. Selecting the
optimum surrogates for application by evaluating and ranking potential surrogates.
This framework will help to systematically select surrogates for real world application
and hence, will assist in effective resilience investment decision making.
The application of surrogate approach to measure social resilience has not been
tested in the Disaster Risk Reduction (DRR) sector to date. Measuring social resilience
indicators using a surrogate approach will address the knowledge gap in resilience
measurement in a disaster context. The framework that was developed in this research
to measure social resilience by using surrogates will provide a new method to measure
resilience indicators using a surrogate approach in other dimensions of community
resilience, such as in the economic, physical, and institutional dimensions.
Once a set of surrogates is selected for a geographical context, they can be
regularly updated to continuously inform the resilience status of the community. It will
help the disaster management policy makers and practitioners to devise appropriate
strategies for enhancing resilience by effectively measuring it by operationalising a set
of surrogates to measure social resilience to disasters. The selection of optimal
surrogates will assist in overcoming conceptual and methodical challenges of social
resilience assessment.
Chapter 4: Research Method 62
Chapter 4: Research Method
This chapter describes the research method adopted in this study to investigate
the key research question, and to achieve three research objectives as detailed in
Section 1.5: to conceptualise, identify, and evaluate surrogates to measure social
resilience indicators in a disaster context. This chapter is divided into seven sections
as shown in Figure 4.1.
The chapter starts with an explanation of the philosophical position of this
research project (Section 4.1). Section 4.2 provides an overview of the research
methods adopted to achieve the defined research objectives, including the selection of
a mixed methods approach. Section 4.3 discusses the selection of five key social
resilience indicators to develop a surrogate approach. Section 4.4 discusses the ethical
considerations of this research study.
The next two sections detail the research method for two phases of research.
Section 4.5 discusses the use of case study interviews in phase I (qualitative study) to
facilitate the exploration of potential surrogates to measure the five selected social
resilience indicators. Section 4.6 discusses the use of an online survey questionnaire
in phase II (quantitative study) to evaluate potential surrogates identified in phase I.
In each section, respective components of the surrogate framework, data collection
technique, and data analysis methods are discussed.
Finally, this chapter concluded with the summary of research methods adopted
in this study (Section 4.7).
Chapter 4: Research Method 63
Figure 4.1. Chapter 4 and key sections in thesis structure
Chapter 4: Research Method 64
PHILOSOPHICAL POSITION OF RESEARCH
A consistent and well-articulated set of epistemological, ontological, and
methodological assumptions will guide researchers to formulate an appropriate
philosophy to frame the research question, research objectives, research methods, and
the interpretation of research findings (Saunders et al., 2015). Research philosophy
defines what knowledge is generated and its nature, and the key assumptions of world
views. Research design is informed by the beliefs and assumptions that underpin
various research philosophies to explain and justify the methodological choice,
research strategy, and data collection and analysis techniques (Saunders et al., 2016).
A research study is designed based on three key philosophical fields - ontology,
epistemology, and methodology. Ontology is a set of assumptions about what exists
in the world, epistemology is a way of understanding the assumptions on what exists,
and the methodological approach is determined by a collective consideration of both
the ontological and epistemological perspectives (Henn et al., 2009).
Ontological position
Ontology refers to the concerns of what exists and the nature of being. There are
two positions of ontology – realism and nominalism (Neuman, 2014) or objectivism
and subjectivism (Saunders et al., 2019). According to Saunders et al. (2019, p. 135),
“ontologically, objectivism embraces realism, which, in its most extreme form,
considers social entities to be like physical entities of the natural world, in so far as
they exist independently of how we think of them, label them, or even of our awareness
of them”. On the other hand, subjectivism is often associated with constructionism,
that views the motivations of social actors and the context in constructing the reality
(Bryman, 2015; Saunders et al., 2019). This research is mostly guided by a
constructionist ontological position, as it builds on a social phenomenon through the
views of social actors.
Epistemological position
Epistemology is the issue of knowledge production and how we know
scientifically what we know (Neuman, 2014). There are many research philosophies
based on epistemology, and the key ones are: positivism, realism, interpretivism, and
pragmatism (Saunders et al., 2019). The following philosophies are briefly described
as follows:
Chapter 4: Research Method 65
Positivism advocates for the development of knowledge based on careful observation
and measurement of the objective reality that exists in the world (Creswell & Creswell,
2017);
Realism asserts that reality can be understood through the use of appropriate methods,
and scientific conceptualisation is a way of knowing that reality (Bell et al., 2018);
Interpretivism considers the differences between humans in their role as social actors
and objects, and seeks to understand the world of research subjects from their point of
view (Saunders et al., 2019);
Pragmatism opens the door for different world views, varying assumptions, and
multiple methods of actions, situations, and consequences rather than precursor
conditions (Creswell & Creswell, 2017). The philosophical assumptions of
pragmatists mostly align with mixed method research strategies. For example, this
approach is not confined to one philosophical system and reality, does not subscribe
to an absolute unity of world view, and aims to provide the best understanding of the
problem by looking at what and how to undertake research.
Different experts and stakeholders in disaster management can have multiple or
conflicting priorities in resilience measurement, and thus, in resilience investments
decision making. However, it is important to balance different viewpoints with the
objective of resilience measurement, as there is a need for a consistent approach and
method to measure it in any context. Therefore, a resilience measurement research
needs to balance different perspectives and viewpoints. This makes it very difficult to
label any social resilience research to particular epistemology. Yet, aligning the
research to a most appropriate epistemological position will help to build a strong
philosophical foundation to the research that makes the selection of a robust research
method.
Social resilience is a multi-faceted concept, and its measurement requires a
broad understanding of the context and key characteristics, the role of social actors,
and their perspectives. Many existing approaches to measure resilience in a disaster
context often fail to provide a broader picture of social resilience status. Many
limitations in the existing resilience measurement approaches are increasingly
apparent in recent research studies which predominantly aim to quantify resilience.
These limitations have led to the adoption of social constructivist approaches. For
Chapter 4: Research Method 66
example, by Endress (2015) as an analytical perspective to identify social processes in
their historical context, which can help to unlock the difficulties in measuring complex
and dynamic resilience characteristics, such as social resilience. Table 4.1 below from
Creswell and Creswell (2017) summarises four alternative combinations of
epistemological positions, strategies of inquiry, and research methods.
Table 4.1. Alternative combinations of knowledge claims, strategies of inquiry, and
methods (Source: Creswell and Creswell (2017) (p. 17))
Knowledge
claims
Research
approach
Strategy of inquiry Methods
Postpositivist Quantitative Experiment design Measuring attitudes,
rating, behaviours
Constructivist Qualitative Ethnography design Field observations
Emancipatory Qualitative Narrative design Open-ended
interviewing
Pragmatic Mixed methods Mixed methods
design
Closed-ended
measures, open-
ended observations
In the context of different philosophical paradigms, this research is most closely
aligned with a pragmatism epistemological viewpoint, as resilience and its
measurement (research subjects in this study) can be influenced by perspectives of the
disaster management experts and the views expressed by the key stakeholders in
disaster management, including communities. The pragmatism approach allows for
different viewpoints to generalise findings by looking at the best options available for
researchers, mostly through mixed method, as was adopted in this research. A
pragmatic approach adapts abductive reasoning that evaluates prior findings from an
inductive process to enable a workable solution, which is very common in sequential
exploration strategies in mixed method research (Morgan, 2007). The next section
provides a brief explanation of different research methods and strategies of inquiries,
and further explains mixed method as a research method selected for this study.
Chapter 4: Research Method 67
RESEARCH METHODS AND STRATEGIES
This study utilised the mixed methods approach, as it is aligned with the
pragmatism epistemological position, discussed in Section 4.1.
In general, research can be exploratory, descriptive, and explanatory, according
to the purpose of research (Neuman, 2014). There are three types of research designs:
qualitative research, quantitative research, and mixed method research. Each design
has its own merits and demerits and is selected based on the context of the research.
At a technical level, it is a matter of selecting the best-suited research design (research
methods and tools) to discover the phenomena being studied, and qualitative and
quantitative methods can be combined concurrently or sequentially in a single research
study design (Henn et al., 2009). This research adopted a mixed method exploratory
research strategy to examine complex and little understood phenomena in order to
develop primary ideas to measure social resilience through a surrogate approach.
(a) Qualitative research
Qualitative research is described as an investigation of concrete case evidences
in a particular temporal and spatial setting, starting from the expressions and activities
of people in that context (Flick, 2014). Qualitative research techniques are associated
with collecting and analysing a set of narrative information (Teddlie & Tashakkori,
2009). Some of the qualitative research strategies include: ethnography, grounded
theory, case studies, phenomenological research, and narrative research (Creswell &
Creswell, 2017).
(b) Quantitative research
Quantitative research is a deductive method for testing objective theories of
social reality by examining the relationship among variables (Bell et al., 2018;
Creswell & Creswell, 2017). Its techniques are associated with collecting and
analysing a set of numerical data (Teddlie & Tashakkori, 2009). Some of the
quantitative research strategies include: survey research and experimental research
(Creswell & Creswell, 2017).
(c) Mixed methods research
Mixed method allows the collection of a set of evidence that is richer and
stronger to allow in-depth exploration of the research phenomena under investigation
to address the research question (Yin, 2014). Mixed method bases the program of
Chapter 4: Research Method 68
inquiry on collecting diverse, complementary and affirmative types of data that
provide a better understanding of the research problem (Creswell & Creswell, 2017).
There are three common mixed method research designs based on whether the studies
take place simultaneously or sequentially. The three mixed method research designs
are:
- Sequential explanatory;
- Sequential exploratory; and
- Concurrent triangulation.
The data collection method and role of qualitative and quantitative methods in
each mixed method design are summarised in Table 4.2. The founding research
philosophy of this study is mixed method sequential exploratory research design,
which is discussed in detail next.
Table 4.2. Three designs of mix method research (Boeije, 2009)
Designs Data collection Role of qualitative/quantitative
research
Sequential
explanatory
QUAN
qual
Quantitative data are
collected and analysed,
followed by qualitative
data. Priority is usually
unequal and given to
quantitative data
Qualitative data are used to explain
unexpected outcomes of
quantitative research. Qualitative
part is used to augment quantitative
data.
Sequential
exploratory
QUAL
quan
Qualitative data are
collected and analysed
first, followed by
quantitative data. Priority
is usually unequal and
given to the qualitative
data
The qualitative part is used to
develop theory and explore
relationships between phenomena.
Concurrent
triangulation
QUAN +
QUAL
Quantitative and
qualitative data collected
and analysed at the same
time. Priority is usually
equal and given to both
forms of data
The qualitative part is used to
confirm and cross-validate the
findings of the quantitative part.
Chapter 4: Research Method 69
4.2.1 Mixed method research - sequential exploratory strategy
In this study, sequential exploratory research strategy is adopted (Figure 4.2).
The sequential exploratory research design is chosen because the surrogates to
measure social resilience (the key phenomena of the study) need to be explored
initially (Boeije, 2009). This study aims to apply a surrogate approach to measure
social resilience indicators in a disaster context. Surrogates need to be explored
initially and then evaluated against a set of standard criteria for final selection. The
research objectives of this study guide the selection of sequential exploratory research
strategy in the mixed methods research approach, which is based on the needs of the
study to initially explore surrogates and then to evaluate it (Sharp et al., 2012). The
pragmatic perspective of research provides a greater flexibility to mix research
methods to initially explore to understand and then to interpret different viewpoints
(Greene & Hall, 2010).
This strategy involves the initial phase (Phase I), as shown in Figure 4.2, a
qualitative data collection and analysis (through interviews), followed by quantitative
data collection and analysis (through online questionnaire survey) that builds on the
results on the qualitative phase (Creswell & Creswell, 2017). Mixed method strategy
is useful because the emergent surrogate identification in the exploratory qualitative
phase can be further validated through an evaluation in the quantitative phase. This
strategy helps to generalise the results for wider contexts. It helps to explore a
phenomenon initially and to expand the qualitative findings in the next phase to
increase the validity of the selected findings in the qualitative phase (Creswell &
Creswell, 2017).
Initially, five social resilience indicators were selected to develop a surrogate
approach based on the review of literature. This helped to achieve Research Objective
1 (RO1): “To select key social resilience indicators that require surrogate approach
by developing a ‘5S’ social resilience framework in disaster management”. This is
Figure 4.2. Sequential design integrating qualitative and quantitative research
methodologies (Creswell & Clark, 2007; Flick, 2014; Hyde, 2006)
Chapter 4: Research Method 70
aligned to key step ‘A’ in the surrogate development framework shown in Figure 3.6.
The method for this step is explained in Section 4.3.
Followed by an extensive literature review, data collection using a mixed
method research approach was designed to identify, evaluate, and select surrogates in
two sequential phases. The mixed method adapted a sequential exploratory research
strategy that included a qualitative research method using interviews in phase I, and a
quantitative research method using an online survey questionnaire in phase II. The
purpose of phase I was to achieve the Research Objective 2 (RO2): “To identify
potential surrogates to measure key social resilience indicators in disaster
management”, using interviews at the community and sub-national levels. Phase I of
this research is aligned to key step ‘B’ in the surrogate development framework shown
in Figure 3.6. The detailed research method for phase I is provided in Section 4.5.
The analysis of data collected in phase I resulted in the identification of potential
surrogates for the five selected social resilience indicators. In phase II, surrogates
identified in phase I were evaluated against five key surrogate evaluation criteria to
rank potential surrogates that aimed to achieve Research Objective 3 (RO3): “To
evaluate and select optimum surrogates for application by ranking the potential
surrogates against surrogate evaluation criteria”. Phase II of this research is aligned
to key step ‘C’ in the surrogate development framework shown in Figure 3.6. The
detailed research method for phase II is explained in Section 4.6.
An overall research process with research methods for each phase of this study
is presented in Figure 4.3. It consists of key research methodological steps across each
phase and their corresponding research objective. Key steps in each phase shown in
Figure 4.3 are listed below with the expected outcomes (in italicised dot points).
1. In-depth literature review & research design phase: (to achieve RO1)
1.1. Literature review of social resilience frameworks and indicators
Identification of social resilience indicators that require surrogates
1.2. Selection of research method and design for developing surrogates
2. Phase I: Data collection (interviews) to identify surrogates: (to achieve RO2)
2.1. Field data collection (group interviews and 1-on-1 interviews)
2.2. Interview data analysis
Identification of potential surrogates to measure social resilience indicators
Chapter 4: Research Method 71
3. Phase II: Data collection (survey) to evaluate surrogates: (to achieve RO3)
3.1. Multi-expert evaluation of surrogates using online questionnaire survey
Evaluation of surrogates based on five surrogate evaluation criteria for
selecting robust surrogates
3.2. Multi-expert multi-criteria survey data analysis
Rank and select the final surrogate(s) based on their performance using multi-
criteria decision analysis
Figure 4.4 shows the overall research methods in each phase of this study,
aligned with research objectives and key steps in the surrogate development
framework (A to C) as shown in Figure 3.6. The surrogate development framework
component in each phase of the study is integrated into one overall research
framework.
Literature review and research design phase: Identification of five key social resilience
indicators that require surrogates for their measurement.
In Phase I: Three sub-steps in identification of surrogates are included:
- Identification of all potential surrogates using a case study research
- Establishing surrogacy relationship
- Exploring protocols for measuring potential surrogates
In Phase II: Three sub-steps in selecting surrogates identified in phase I are included:
- Multi-expert evaluation of potential surrogates against five evaluation criteria
using an online survey
- Ranking of potential surrogates using Multi-Criteria Decision Analysis
(MCDA) method
- Selection of optimum surrogates for application
The research method, data collection technique, and data analysis method for
each phase of this study are discussed in detail in the following sections (Sections 4.3,
4.5 and 4.6). Section 4.4 provides a brief summary of ethical considerations of this
research in both phases.
Chapter 4: Research Method 72
RO2 RO3
To identify potential surrogates to
measure key social resilience
indicators in disaster management
To evaluate and select optimum
surrogates for application by
ranking the potential surrogates
against surrogate evaluation
criteria
To select key social resilience indicators
that require surrogate approach by
developing an inclusive and adaptive
social resilience framework in disaster
management
RO1
Figure 4.3. Overall research process with key steps in three phased research
Chapter 4: Research Method 73
Figure 4.4. Expanded research framework with sub-steps for testing surrogate approach (In phases aligned with ROs)
Chapter 4: Research Method 74
SOCIAL RESILIENCE INDICATORS SELECTED FOR DEVELOPING
SURROGATES
At the initial stage of this research (literature review and research design), a
detail review of social resilience assessment frameworks was undertaken to identify
social resilience indicators that need surrogates due to the complexity of measuring
them directly. This process resulted in a ‘5S’ model social resilience framework and
five indicators were selected to develop a surrogate approach, which was to achieve
RO1 as shown in Figure 4.5.
In this study, a ‘5S’ inclusive and adaptive social resilience framework was
developed from the critical analysis of existing social resilience frameworks, as shown
in Figure 2.5. The proposed framework can guide the selection of appropriate social
resilience indicators and their adequate operationalisation based on the context of its
application. This framework was used to select a set of key social resilience indicators
to develop a surrogate approach.
Although the majority of the indicators among the 46 indicators require a
surrogate approach, five key indicators were selected (one indicator for each social
resilience sub-dimension) for developing surrogates in this research. The five
following social resilience indicators were selected for developing a surrogate
approach as a testbed:
To select key social
resilience indicators
that require
surrogate approach
by developing an
inclusive and
adaptive social
resilience framework
in disaster
management
RO1
Figure 4.5. Extract from the overall research process for the literature
review and research design phase (RO1)
Chapter 4: Research Method 75
1. Access to transport facility in a disaster situation to measure social mobility;
2. Social trust during disasters and recovery to measure social cohesion;
3. Learning from past disaster experience to measure social competence;
4. Involvement and equity for people with specific needs in different phases of
disasters to measure social equity; and
5. Existing cultural and behavioural norms in relation to disaster risks and
managing disasters to measure social beliefs.
These were selected based on the following three general criteria for deciding the
surrogate approach:
1. Process resilience indicators that are not very static (dynamic, frequently change
over time); or,
2. Complex to conceptualise and cannot be easily measured quantitatively (e.g. social
trust, community competence); and,
3. When resilience is measured using indirect methods, existing frameworks mainly
use data from publicly available census data sources, which is often not able to
accurately and adequately measure the target indicator.
In this study, a fourth criteria was also included to ensure the wide applicability of the
findings, namely, indicators that are relevant to multiple disasters and different
geographical and socio-economic contexts. Finally, one indicator was selected for each
of the five social resilience dimensions in the ‘5S’ social resilience model developed
by Saja et al. (2018).
Table 4.3 shows the detailed descriptions and justification of five key indicators
that were selected for developing surrogates. As previously stated in Chapters 1 and 2,
direct measurement of the above key resilience indicators often requires detailed
household surveys, which are costly and time consuming. These indicators are
geographically very dynamic, varying greatly from household to household and among
social groups. They also change frequently with time. For example, regular and
detailed community surveys are required to identify multiple transport facilities
available and required for disaster evacuation. This information needs to capture
unique household requirements needed to evacuate people with special needs, such as
disabled, elderly, children, and people who require special assistance. Therefore, a set
Chapter 4: Research Method 76
of surrogates that can be mainly measured through regularly updated administrative
data is needed to overcome existing limitations in resilience measurement, instead of
outdated and less frequently updated census data. In most of the developing countries,
census data is not often updated. The local authorities and administrative state
departments, however, update their administrative data regularly. Hence, new
approaches are needed to find ways to identify key facets of social resilience indicators
that are difficult to measure. The key facets of these indicators can be potential
surrogates for which the data can be obtained from the regularly updated data sources.
A list of existing measures for the five selected indicators in the 31 social
resilience frameworks analysed in this study is provided in Appendix A. Most of the
existing measures have used census statistics data that are available from the public
databases. They are not adequate to provide a good measure of social resilience as
discussed in Chapter 2 (literature review). Further, there were no relevant measures
found for some of the key social resilience indicators in the 31 social resilience
frameworks analysed in this study, such as equity for people with specific needs and
cultural/behavioural norms.
Chapter 4: Research Method 77
Table 4.3. Details of social resilience indicators selected for developing surrogates
# Indicat
or
Characteristic Link to social resilience to
disasters
Justification for selection of the indicator to measure social
resilience
References
1
Access
to
transpor
t facility
in a
disaster
situation
Social mobility
during disasters
for effective
evacuation and
disaster
response
Ability of greater mobility of
people individually and of
families collectively can
enhance social resilience to
disasters and improve response
effectiveness at the time of
disasters, particularly during
evacuation.
There are many ways disaster evacuation can happen,
including using private vehicles or mass transport systems or
there may be a need for access to emergency transport
facilities. Access to transport is mostly attributed to vehicle
ownership. Disaster evacuation researchers also found that,
evacuation behaviour is interconnected to many factors such
as socio-economic status, race, ethnicity, and local language
ability. Availability or access to special needs transport is
another crucial element with regard to mobility of people in a
disaster context.
Adger et al.
(2005),
Burton (2015),
Kotzee and
Reyers (2016),
Peacock et al.
(2010), Tierney
(2009).
Frailing and
Harper (2017)
2
Social
trust
during
disasters
and
recovery
Social cohesion
that help
improve
response and
quicker recovery
Social cohesion is positively
interrelated to social resilience,
although the strength of this
association varies. Social
cohesion and cohesion among
social entities proved to be an
important factor in effective
coping and response to any
disaster.
Social trust is an integral part of social cohesion. Trust
among the community members during a disaster is very
important, because it positively facilitates coordination and
cooperation for effective disaster response and provide access
to resources. Trust by the community in local authorities is
also another key factor to consider in measuring social
cohesion. A positive strong correlation exists between the
level of trust and engagement of community members by
emergency management authorities on risk communication
and actions.
Leykin et al.
(2016), Aldrich and Meyer (2014b),
Ainuddin and
Routray (2012),
Paton (2007),
Lorenz (2013),
Townshend et al.
(2015)
Chapter 4: Research Method 78
3
Learnin
g from
the past
disaster
experien
ce
Social
competence in
managing
disasters
Communities exposed to
disasters should have a good
knowledge about their risks and
have the capacity to acquire
reliable and precise information
of risk assessment to solve
emerging problems.
Past experience and learning from the past helps the process
of understanding future emerging risks. Past experience and
exposure to a disaster helps to enhance social resilience,
which increase the competency of the community to prepare
for, and to face the next disaster. Greater importance is given
in many social resilience frameworks to community
competence as one of the primary sets of adaptive capacities
to build social resilience. Coping style influences social
resilience and problem-focused coping style is helpful for
effective disaster response and recovery.
Norris et al.
(2008), Leykin et
al. (2016),
Miller et al.
(1999)
4
Involve
ment
and
equity
for
people
with
specific
needs
Community
inclusiveness
and social
equity in
disaster
preparedness
initiatives
Equitable gender and social
relations can contribute to
enhance social resilience.
Inclusion of people with special
needs in the process and
provision of equal opportunities
in disaster planning and
recovery are important to
enhance social resilience.
Exclusion of the most vulnerable and less resilient segment
of the population has been highlighted as the most pressing
issue in disaster response and recovery programs, due to
difficulty of access as well as purposeful negligence. Ethnic
minority, race, caste, cultural disparity, and any other forms
of marginalisation based on socio-economic status of the
population will contribute to lowering social resilience,
predominantly in resource allocation and provision of equal
access to needs and services.
Cutter et al.
(2003),
Enarson (1998),
Kotzee and
Reyers (2016),
Begum (2008)
5
Existing
cultural
and
behavio
ural
norms
Local cultural
norms and
social belief
systems dealing
with disaster
risk
Cultural beliefs exert a certain
level of influence on the
interpretation of disaster risks by
a community. Resilient building
initiatives must be undertaken
with greater cultural sensitivity
to help increasing capacities,
and so as not to lower existing
resilience.
Not only human resources and physical assets, but local
culture and social beliefs can play an essential role in
determining social resilience. Social beliefs need to be
positively capitalised in communities that are oriented with
their own local culture and faith systems. Different cultural
groups within the same community may differ in their
preferences in resilient building activities and also in disaster
response actions.
Eiser et al.
(2012),
Wilkinson (2015),
Kwok et al.
(2016),
Ostadtaghizadeh
et al. (2016)
Chapter 4: Research Method 79
RESEARCH ETHICAL CONSIDERATIONS
Research ethics is concerned with the procedures that should be applied to
protect research participants and to regulate the relationship of researchers with them
(Flick, 2014). Ethics approval from QUT was obtained, since this research was
conducted with people and their data. This research was a human-centred, which was
conducted with selected disaster management experts and people with disaster
management experience. Therefore, people were invited to take part in interviews and
an online survey.
Ethical compliance for this research was submitted to the QUT Office of
Research Ethics and Integrity (OREI) for ethical clearance. The ethics application
under the category of ‘Negligible-Low risk’ was approved by the Queensland
University of Technology (QUT) Human Research Ethics Committee (HREC). The
approval UHREC Reference number is 1700000832. The approval from QUT-HREC
is provided in Appendix B.
This research was considered a negligible or low risk study, because:
o Foreseeable risk to participants was no more than "inconvenience" due to the
limited amount of time spent on interviews and completing the online survey;
o Questions to participants were general in nature and did not relate to business/
past or current project practices;
o Participants’ reaction to questions in interviews and survey was not likely to
cause any harm or distress;
o Participation in interviews and surveys was on voluntary basis and results
reported remain anonymous; and
o In the publication of research results, participants of interviews and online
surveys were de-identified.
4.4.1 Ethical considerations in interviews (Phase I)
The semi-structured questions during interviews focused on the identification of
potential surrogates in general. Hence there was no personal information collected.
Any personal information was treated as confidential and aliases such as “participant
in interview #1” were used instead of the real names of participants in all transcripts
and publications.
Chapter 4: Research Method 80
All participants were given time to read the “Information for interview
participants” sheet and were also provided with a brief explanation about the research,
its benefits and purposes prior to starting interviews. Interviewees were reminded that
their participation in the interviews is strictly voluntary. If they feel discomfort, they
have the right to withdraw from the interview. Interview participants were requested
to seek permission from their organization/superior, when needed, before participating
and abide by confidentiality and privacy rules as per their organisation’s requirements.
A consent form was signed by each participant prior to starting interviews to indicate
that they agreed to participate in the interview on a voluntary basis.
For group interviews, a list of members attached to divisional disaster
management committee were obtained from the Divisional Secretary. The researcher
selected the participants for each group interview based on their experience (minimum
of three years of experience in disaster management). The selected interviewees were
directly contacted by the researcher to check their willingness to participate in the
group interview. Further, for group interviews, participants of a similar employment
level within the organisational hierarchy were formed into a group for the interviews
to minimise their discomfort or concerns at speaking on the topic in front of others
who are at a higher level than them. The researcher encountered some difficulties to
fix the time for group interviews that was convenient for all the participants who
agreed for group interviews. Hence, some participants did not turn out at the scheduled
time for group interviews. When participants who were selected for group interviews
were unable to participate in the group interview, one-on-one interview was conducted
with them at a later date that was convenient for them.
4.4.2 Ethical considerations in online survey (Phase II)
The online survey was anonymous, and personal identifiable information such
as name or contact details were not collected. All requirements in participating in the
online survey were written in the survey email invite and respondents were requested
to go to the online questionnaire link to respond, if they wished to participate. All
participants were sent “Information for survey participants” sheet as an attachment to
the email to read before they decide to respond to the survey questionnaire. The survey
targeted mid and senior level individuals who had a minimum of three years of direct
work experience in disaster management. This was ensured by the first question
Chapter 4: Research Method 81
included in the questionnaire, “Do you have a minimum of three years of direct work
experience in disaster management work”.
PHASE I – QUALITATIVE CASE STUDY RESEARCH FOR
IDENTIFYING POTENTIAL SURROGATES (INTERVIEWS)
4.5.1 Identification of potential surrogates: Case study as a strategy of inquiry
The case study research method is identified as a key strategy of inquiry to
unlock the complexities in social phenomena (Yin, 2014). A case study is an intensive
research process defined as an in-depth study of a social phenomenon within a unit of
observation; in this case, the unit of analysis is an urban division (Swanborn, 2010).
At the local level of this case study, disaster management planning and project
implementation are done in Sri Lanka division-wise.
While every country has its own definition of an ‘urban’ locality, ‘urban’ is
defined in the Sri Lankan context as “a smallest administrative division which has a
minimum population of 750 persons, a population density greater than 500 persons per
square kilometre, firewood dependence of less than 95 % households, and well-water
dependence of less than 95% households” (Weeraratne, 2016, p. 4). There is an
increasing emphasis for enhancing resilience in urban areas due to rapidly changing
disaster risk landscape (Maduz & Roth, 2017). The location of this research in urban
areas has wider applicability to other urban contexts in the world. Figure 4.6 shows the
research process in phase I, which was to achieve research objective 2 (RO2).
RO2
To identify potential
surrogates to
measure key social
resilience indicators
in disaster
management
Figure 4.6. Extract from the overall research process for Phase I (RO2)
Chapter 4: Research Method 82
A key justification for undertaking case study research is its ability to investigate
a new approach in detail. The use of a surrogate approach in a disaster context is an
innovation of this research, and requires an in-depth exploration of the surrogate
approach in real-world context (Henn et al., 2009; Yin, 2014). A case study approach
can help to maintain a pragmatic position that assumes a reality can be constructed and
its understanding can be developed through social experiences (Mills et al., 2017).
There are many strengths in case study research that enables the measure of
abstract concepts such as resilience to actual experiences and evidences (Neuman,
2014). Some of the strengths of case study research in the context of measuring social
resilience in disaster context include (Neuman, 2014):
o Conceptual validity, which helps to identify concepts/surrogates for measuring
social resilience, an abstract phenomenon;
o Extension of the surrogate approach to measure social resilience in a disaster
context;
o Ability to make social mechanisms more visible in order to deconstruct the key
facets of social resilience indicators
o Ability to capture complexity and trace processes in a social context;
o Enables the study to fine-tune measures of abstract concepts of resilience to
new experiences.
Further, the exploration of surrogates in multiple case study locations uses
multiple sources of evidence, maintains a chain of evidence, and creates a case study
database that enables cross-case synthesis (Yin, 2014). It allows diverse insights, since
data were obtained from a wide range of participants. Multiple cases allows
triangulation to reduce bias (Yin, 2014) and avoid focusing on the predominant views
within the specific study group.
Interviews as a data collection technique
Interviews with disaster management practitioners and policy makers working
at the community and sub-national levels were selected as a data collection technique
in the case study areas to allow easy identification of a set of potential surrogates to
assess selected indicators. Interviews can provide more detailed and important insights
for the research objectives being studied (Hancock & Algozzine, 2016), which is to
Chapter 4: Research Method 83
identify potential surrogates. Therefore, interviews were selected as the most
appropriate data collection tool for phase I of this research.
Interviews is one of the widely used technique for collecting qualitative data,
different qualitative interviewing strategies from diverse disciplinary perspectives
have resulted in a wide range of interview-based data collection techniques (DiCicco‐
Bloom & Crabtree, 2006). This includes face-to-face and one-on-one interviews,
telephone interviews, focus group interviews, and email internet interviews (Creswell
& Creswell, 2017). Survey interviewing, in-depth interviewing, and life story
interviews (Gubrium et al., 2012) are also used. For exploratory inductive research
objectives that focus on what and how social processes, interview techniques using a
one-on-one method are best suited (Johnson & Rowlands, 2012), because they can
delve into how surrogates are linked to the target indicator (surrogacy relationship)
and how they can be measured (measurement protocols). In this research, face-to-face
groups and one-on-one interviews were used for initial exploration of potential
surrogates, since this method can uncover deeper information from the knowledge and
experience of the respondents (Johnson & Rowlands, 2012).
Group interviews: Some researchers have characterised ‘group interviews’ with
limited interaction among participants as focus groups, and some others view a focus
group as a ‘group discussion’ which gives more importance to interaction between
participants than to the group interviews (Alasuutari, 2008; Bryman, 2015). A focus
group is also a type of group interview, but primarily seeks to generate qualitative data,
from the interaction between group members (Davis, 2016). In this research, group
interviews are defined as interviews with more than two participants, where the
interviewer listens to participants’ opinions individually, without any interaction with
other members in the group (Davies, 2010; De Ruyter, 1996). In group interviews,
participants are able to connect to their own experience and can build on what has been
already described by other participants. The interviewer as a moderator can encourage
each participant to offer new ideas (Axinn & Pearce, 2006) and limit the responses
when it is being repeated. Further, a group setting encourages each participant in the
group to diffuse diverse ideas influenced by other group members (Patton, 2002),
whereas in individual interviews, the same ideas can be repeated by every interviewee
and may not contribute new information. However, group interviews have some
drawbacks compared to one-on-one interviews, such as domination by some members
Chapter 4: Research Method 84
in the group. These limitations were overcome in this study by providing every
member of the group an opportunity to answer every question; this was set as a ground
rule before the interviews commenced.
Individual interviews (one-on-one/in-person): In order to gather information-rich
samples that are geographically and institutionally widespread, one-on-one interviews
were undertaken in addition to the group interviews, since it was often difficult to get
participants together in one place to undertake a group interview. Individual interviews
followed the same process and structure (semi-structured questionnaire format) of the
group interviews. However, during individual interviews, each respondent had more
time than in group interviews to explore potential surrogates for each social resilience
indicator. A total of 39 one-on-one in-person interviews were held, including 20 at the
sub-national level (Case study #4). The remaining 19 were held in the divisional case
study locations (Case studies 1 to 3).
Both one-on-one and group interviews followed the same structure and process.
An interview guide with five semi-structured questions for each of the five resilience
indicators was used, based on three sub-steps to identify potential surrogates, as shown
in Figure 4.4. Interview questions were structured as follows (detailed interview guide
for each of the resilience indicators is provided in Appendix F).
Appendix C shows the letter of recruitment for interview participants; Appendix
D shows the participant interview consent form used in this study to obtain a signed
consent for participation in the interview; Appendix E shows the participant
information sheet provided to participants before the interview to familiarise them with
the interview processes and ethical guidelines.
Creswell and Creswell (2017) highlighted four key aspects in selecting study
locations and study participants for data collection using interviews:
1. Study setting - where the research was conducted;
2. Study actors - who participated in interviews;
3. Study events - what the participants were interviewed about;
4. Study process - to know how the work of actors evolved within the research setting.
Each aspect is discussed below.
Chapter 4: Research Method 85
Study area and location (study setting)
The Kalmunai Municipality of Ampara district in the Eastern Province of Sri
Lanka was selected as the case study area for this research. Sri Lanka is one of the
countries in Asia that is highly vulnerable to multiple hazards, such as tsunamis,
cyclones, floods, and landslides. Sri Lanka was rated among the top 10 most affected
countries in the climate risk index for 2017 by Germanwatch (Eckstein, 2018).
Kalmunai Municipality was selected because it is frequently exposed to multiple
disasters such as flooding, tsunami and cyclone (UNHABITAT, 2015; Zubair et al.,
2005) and the researcher could access a wide range of disaster management experts
working in this region.
Kalmunai municipality is the most populated local authority in the coastal area
of Ampara district and can also be characterized as ‘Urban’ area by it’s highly densely
population (JICA, 2008). In Sri Lanka, all areas administered by Municipal and Urban
councils constitute the urban sector and ‘urban’ area is a Grama Niladhari Division,
“if it has a minimum population of 750 persons, a population density greater than 500
persons per km2, firewood dependence of less than 95 % households, and well-water
dependence of less than 95% households” (Weeraratne, 2016, p. iv). The population
density per square kilometre of the Kalmunai municipality is as high as 5,000 per
square kilometre whereas the national average is 299 people per square kilometre
(GoSL, 2018; JICA, 2008). The total population within Kalmunai Municipality is more
than 110,670 and most of the people live within 1.5 km range of the area from the
seashore of Indian Ocean in the East (GoSL, 2018).
The selection of urban context is also justified, because the statistics highlight
that 54% of the world population lives in urban areas and 16% of them live in large
cities around the world (WorldBank, 2014). Hence, the findings from this research will
have a wide applicability, since the data collection for this research was done in the
urban context, compared to being undertaken in a rural context. Further, the historical
records (Jameel, 2009) show that a series of cyclones hit South-eastern coast of Sri
Lanka in 1980s and 90s. This includes severe and medium category cyclones in 1845,
1891, 1907, 1921, and 1978. Although the damage and loss data is not available for
these cyclone events, 1978 cyclone was reported to be the major cyclone in the
historical records available, and it took three months to bring back to the normalcy.
Three major floods were also reported in this area: in 1933, 1957, and 2010. The 2004
Chapter 4: Research Method 86
Tsunami was the major devastating disaster in the history of this area, which killed
more than 3,000 people and entirely wiped out half of the coastal areas of Kalmunai
Municipality, leaving thousands of families, homeless and houses severely damaged.
It took more than five years for recovery from the Tsunami damages.
Four case studies were adopted. Among these, three urban study locations within
the Kalmunai municipality (local authority) were selected for this research. The three
case study locations selected are at the lowest state administrative level, which is
termed a ‘Divisional Secretariat’. This also allows multiple sources of evidence and
convergence of data in a triangulating fashion, which helps exploratory studies in
theory development (Yin, 2014).
Figure 4.7 shows the geographical area of the three study locations (Divisional
Secretariate administrative divisions), namely:
Figure 4.7. Case study locations in Sri Lanka map
Chapter 4: Research Method 87
Case study area 1: Kalmunai Tamil (denoted as ‘KMT’),
Case study area 2: Sainthamaruthu (denoted as ‘SM’), and
Case study area 3: Kalmunai Muslim Division (denoted as ‘KMM’)
The fourth case study area was selected at the sub-national level as ‘Ampara
district and Eastern Province’, which comprises other local authorities, including three
case study locations. The fourth case study location was at a sub-national level to reach
disaster experts and professionals with a holistic and national understanding of
disasters. They also work in three case study areas while working at the sub-national
levels in the district and province, which ensured wider representation of samples. In
total, the selection of four case studies as a whole provides a good representation of a
wider geographical region from community to sub-national levels, where there is a
wealth of disaster management experience.
The structure of Sri Lanka’s administrative and devolved political power
structures and their linkages is shown in Figure 4.8. It depicts the relationship of case
study locations to the lower and sub-national levels in the central administrative
structure. It also shows the parallel devolved governance structure at local authority
and provincial levels. In this study, interview participants were sampled at two levels:
Figure 4.8. Administrative and authority governance structures
in Sri Lanka
Chapter 4: Research Method 88
sub-national and lower (community) levels of administration and authorities, since
both entities have roles in disaster management in their respective levels. The district
level comes under the central government administrative structure, and the provincial
level is part of the devolved political power structure.
Sample selection (study actors): Purposive sampling strategy for interviews
Purposeful sampling is more appropriate for qualitative research that uses an
interview method for data collection, as individuals who have experience in the central
phenomenon of the research can be reached more effectively (Creswell & Creswell,
2017). The basis for a purposive sampling strategy is justified if the random selection
fails to yield the most informative samples, and therefore samples in this study can be
chosen for their knowledge which is representative of a larger population (Alasuutari
et al., 2008). Theoretical sampling, where individuals are selected according to their
ability to contribute new insights to the research phenomenon being investigated
(Flick, 2014) was the starting point in a purposive sampling strategy for this research.
Sample selection was further intensified with the identification of samples with
different levels of experience, from administrative to community work, and with wider
variations such as senior to mid-level officers (Flick, 2014).
a) Whom to select for interviews: The sampling strategy began with information-rich
participants (Marshall & Rossman, 2014) in relation to the research phenomenon,
often referred to as ‘key informants’, who are considered to be knowledgeable about
the subject (Faifua, 2014). The sample should inform the research objective
sufficiently to gather a substantial set of information that can then be content
analysed. A list of members in both divisional and district disaster management
committees in each case study location was obtained from the relevant divisional
and district government offices (theory-based samples). The final selection of
samples was done by selecting people who are active members of divisional/district
disaster management committees and have a minimum of three years of experience
in disaster management work and/or are key decision makers in disaster
management planning. Further, the inclusion of ‘information rich samples’ was
ensured by selecting those who have more than three years of experience in disaster
management projects at the sub-national level, as shown in Figure 4.9.
Chapter 4: Research Method 89
b) How many interviews: The total selected sample size for phase I was 50, including
a minimum of ten for each study location (i.e. one DS division). According to Bion et
al. (2000), the optimum number of interviews for a research study lies somewhere
between 15 and 25 individual interviews, and for groups, the optimum number can be
between six and eight groups. Since this study combined individual and group
interviews, it was planned to reach 50 interviews. Table 4.4 provides a detailed
overview of the number of selected interview participants for each case study location,
and Tables 4.5 (a) and (b) details the summary of participant profiles, such as their
administrative positions and affiliations.
A total of three group interviews (one in each case study location) and 39 one-on-one
interviews were arranged. Dynamics of the response can be increased by including
diverse stakeholders (Flick, 2014). In this research, three to four members in each
group participated in group interviews in three DS divisional case study locations (case
studies 1 to 3). A group interview technique was used in this research with selected
government officers who work in the same office (divisional secretariat) and in the
same geographical area. Some participants may gain more confidence in a group
setting from the responses of other participants compared to one-on-one interviews
Figure 4.9. Sample selection process diagram
Chapter 4: Research Method 90
(Axinn & Pearce, 2006). Group interviews are efficient because group members
stimulate each other, interviewer-respondent relationship can be sustained, they are
less likely to stall compared to one-on-one interviews and effective when the time-
frame is limited (Fontana & Prokos, 2016).
Table 4.4. Samples selected for interviews in all study locations
Table 4.5. Interview participant profiles: (a) designation/position and (b) affiliation
As shown in Table 4.5 (a) and (b), the experts interviewed in this study are a
good mix of senior-level highly experienced government and project management staff
members. 60% of interviewees hold high level positions such as Project Director,
Project Manager, Project Officer, and Project Consultants. Mid-level/community level
Interview participant
affiliation in case study areas
Group interviews
(# of experts)
Individual
interview
Tota
l
Kalmunai T (Case study 1) 1 Group (3 experts) 7 10
Sainthamaruthu (Case study 2) 1 Group (4 experts) 6 10
Kalmunai M (Case study 3) 1 Group (4 experts) 6 10
Case study 4 includes Ampara
District and Easter Province N/A 20 20
Total interviews and
participants
3 Group interviews
(11 participants)
39
participants 50
(a) Interview participants’ designation (n=50)
Project Director 18 36%
Project Manager 5 10%
Project Officer 2 4%
President/Executive Director 3 6%
Project Consultants 5 10%
Village Administrators 12 24%
Social Service Officers 2 4%
Divisional Disaster Relief
Officers
3 6%
(b) Participants’ affiliation (n=50)
Central Government 28 56%
Local Government 2 4%
NGO (Local) 11 22%
NGO (International) 7 14%
Multilateral agencies such as UN 2 4%
Chapter 4: Research Method 91
government officers, village administrators and leaders of community organisations
were 34% and 6%, respectively. The majority of the participants were from high level
positions, since almost all the participants in case study 4 and two to three participants
in each division were senior and experienced officials. The expert sample also included
60% from the public sector, 22% from local/community-based organisations, and 18%
from international agencies.
Table 4.6 shows the affiliation of interview participants in divisional
administration and their respective positions in the divisional disaster management
committee. The sample selection for each case also ensured the inclusion of interview
participants from eight different functionalities/departments involved in disaster
related activities, such as social services, disaster relief services, village administrative
services, and planning services of a divisional administrative area, as shown in Table
4.6.
Table 4.6. Selected participants for interviews in one study location (DS division)
# Divisional Disaster
Management Committee Position Affiliation No
1 Divisional Secretary (DS) Co-Chairman Administration
service 1
2 Asst. Divisional Secretary
(ADS) Secretary
Administration
service 1
3 Assistant Director of
Planning (ADP) Convener Planning Service 1
4 Administrative Officer
(Village Divisions)
Coordinator
for village
divisions
Local Administration 1
5 Social Service Officer
(SSO) Member Local Administration 1
6 NDRS officer (National
Disaster Relief Services)
Coordinating
Assistant
Disaster Mgt. Centre/
Local Administration 1
7 Village division
administrators
Representing
village
divisions
Local Administration 3
8
Representative from the
civil society organisation
(CSO)
Member
representing
CSO
Civil Society
Organisation (CSO) 1
Total 10
Chapter 4: Research Method 92
Study events - What the participants were interviewed about
1. The interviewer provided an introductory explanation of the social resilience
indicator for which the surrogates were explored.
2. To kick-start the interview, interview participants were asked to briefly explain the
current context of the resilience indicator in the case study area (This question was
to help the participants to start thinking of key facets of the resilience indicator).
3. Next, participants were asked how the target resilience indicator was assessed. This
question was to explore potential surrogate measures to assess the target indicator.
4. From the proposed key facets of the resilience indicator (which can be a potential
surrogate to that indicator), participants were probed on what key attributes indicate
a target resilience measure for gauging the surrogacy relationship. This was to
ensure that the proposed key facet of the resilience indicator is very closely related
to the target indicator.
5. Finally, the interviewer probed how the data can be obtained to measure the
proposed potential surrogate measure to understand the measurement protocols.
Study process – How interviews were conducted
Interviews were conducted from September to November 2017. All the
interviews were conducted in Tamil except for two interviews which were done in
English. The majority of the participants were from the Eastern Province of Sri Lanka,
and their native language is Tamil, and they are not necessarily fluent in English. Each
one-on-one interview lasted approximately 45 minutes, whereas the group interviews
took up to 60 minutes. All the interviews were audio recorded, which allowed the
researcher to focus on the interview questions and helped to record all the data. On
average, 10 minutes was spent on potential surrogates for each indicator. Interview
questions were posed, followed by additional probes to break the silence, and
responses were audio-recorded for analysis (Leeuw, 2008). Semi-structured interviews
with open questions were used in this research, since these are much more flexible and
more likely to yield new ideas than structured survey-type interviews or less structured
interviews (Axinn & Pearce, 2006).
Chapter 4: Research Method 93
4.5.2 Phase I – Interview data analysis
The qualitative phase of the research using interviews, is a cyclic process
between data collection, data analysis and sampling (Boeije, 2009; Vaismoradi et al.,
2016). However, the quantitative phase, using an online survey, is linear. In
exploratory mixed method research design, connected data analysis is done to
generalise findings (Creswell & Creswell, 2017). The complete representation of a
seven-step sequential, exploratory, mixed method data collection and analysis model
is shown in Figure 4.10 (Creswell & Creswell, 2017).
The case studies were analysed individually, with interview audio recordings
transcribed, and then professionally translated from Tamil to English language. The
interview transcripts yielded large volumes of text. Hence, the content analysis of
interview data was done using the Leximancer data mining tool.
Leximancer as a textual data analysis tool
Leximancer software is a computer-based lexical analysis data mining tool, used
for content analysis of qualitative data, and can produce thematic strings. Leximancer
was used because it provides an automated data analysis based on lexical text
properties, and it is efficient in handling large sets of qualitative data without bias
(Sotiriadou et al., 2014). Further, Leximancer is not only more effective than manual
coding, but also identifies a broad range of concepts thereby increasing the consistency
and reproducibility that helps analysts to derive greater insights (Angus et al., 2013;
Penn-Edwards, 2010).
Figure 4.10. Sequential exploratory design (qualitative to quantitative)
(Creswell & Creswell, 2017)
Chapter 4: Research Method 94
Concepts in Leximancer are collections of recurrent words that travel together
throughout a text document, and a concept map is generated using a frequency of co-
occurrences of concepts (Leximancer, 2017). A set of concepts that formed a theme
was identified from the lexi concept maps in a systematic fashion across the entire data
set for each case study. The concepts were then translated into meaningful themes and
a set of correlated themes was then combined to create a higher-order theme. Each
higher-order theme was then interpreted in terms of potential surrogates that are
relevant to the intended target indicator of measure in this study. The process of
thematic synthesis of case study data is shown in Figure 4.11 (Cruzes & Dyba, 2011;
Cruzes et al., 2015). The levels of interpretation to develop surrogates followed a path
of abstraction from text to higher-order themes through the interpretation of concepts
and themes generated in Leximancer analysis.
Analysis method of interview transcripts in Leximancer
Interview data was fed into Leximancer in order to develop concepts and theme
maps. The initial content analysis of interview data for each case study generated
concepts and themes in three platforms: concept cloud view, concepts integrated into
themes map, and analyst synopsis with the descriptions of concepts and themes as
shown in Figure 4.12. A sample concept, theme, and higher-order theme map is shown
in Figure 4.13. Each node is a concept, each circle around a set of similar concepts is
a theme, which are automatically generated in Leximancer. The researcher identified
similar or closer themes to create a higher-order themes shown by solid square or
rectangular lines in Figure 4.13.
Increasing level of
abstraction
Figure 4.11. Levels of interpretation in thematic analysis
Chapter 4: Research Method 95
Themes and concepts were inter-related and their meaning was interpreted with
the help of interview data in the description of each concept. Identification of concepts
and themes by inferring the content of the interview data is similar to the identification
of patterns and typologies suggested by Flick (2014). At the end of the analysis, the
aim was to extract all potential higher-order themes that can be used as potential
surrogates to measure the five selected social resilience indicators. Thematic analysis
was conducted independently for each case study. A relevant quote selected from an
interview participants in each case study is provided below to describe the relationship
between the higher-order theme and the target indicator.
Distinct case analysis: The interview transcripts for each case study were collated into
a single document for individual analysis. Among many case study analysis
techniques, pattern matching (concepts and themes), explanation building, and cross-
case synthesis are used to analyse interview data which is the method that was also
adopted for this study (Yin, 2014). The concepts/themes map using Leximancer was
generated for each case study. From these maps, a thematic analysis was carried out
by combining the most closely related themes for each case study independently to
identify a set of meaningful higher-order themes for each case study. The higher-order
theme was considered as a potential surrogate for each case study area. Further, each
Figure 4.12. Process of case study data analysis using Leximancer
Chapter 4: Research Method 96
of the higher-order themes built from the distinct case study analysis is explained with
the interview transcript data. The key step of identifying higher-order themes was done
by combining most closely related themes generated by Leximancer. Figure 4.12
shows the process of reaching higher-order themes from the interview data for each
case study.
Cross-case synthesis: In order to build a new body of knowledge, a synthesis of the
multiple cases was necessary. This was undertaken using the case study analysis
results. Figure 4.14, adapted from Yin (2014) shows the analysis structure of multiple
case studies using cross-case synthesis to develop surrogates based on the higher-order
themes generated from the different case analyses. Finally, unique themes from the
different case analyses were cross tabulated to identify commonly occurring higher-
order themes across all case studies. The final set of unique higher-order themes was
taken as potential surrogates for each of the five selected social resilience indicators.
At the end, explanation building in multiple-case studies was carried out to interpret
the potential surrogate using the surrogacy relationship and protocols for measuring
potential surrogates from interview transcripts.
Figure 4.13. Sample Leximancer concept/theme maps from interview data
Chapter 4: Research Method 97
PHASE II – QUANTITATIVE SURVEY TO EVALUATE AND RANK
POTENTIAL SURROGATES (ONLINE SURVEY)
In a sequential exploratory mixed method research design, a quantitative
research method is employed based on the qualitative findings. In phase II, an online
survey was used to evaluate potential surrogates identified in phase I. Experts with a
Figure 4.14. Cross-case synthesis diagram adapted from (Yin, 2014)
RO3
To evaluate and select
optimum surrogates for
application by ranking the
potential surrogates against
surrogate evaluation criteria
Figure 4.15. Extract of overall research process for phase II (RO3)
Chapter 4: Research Method 98
minimum of three years of experience in disaster management were invited to provide
their insights as to how the proposed surrogates can measure the target indicator, since
the aim of phase II was to evaluate potential surrogates against five key criteria to
select optimum surrogates. The research process of phase II to achieve RO3 is shown
in Figure 4.15.
4.6.1 Phase II data collection through online survey
The research framework shown in Figure 4.4 was used to select optimum
surrogates by evaluating and ranking potential surrogates identified in phase I.
Evaluation and selection of surrogates: Survey as a strategy of inquiry
Questionnaire, interviews, and structured observations are some data collection
techniques that can be used in the survey research method (Pickard, 2013). For the
purpose of this study, which aims to obtain multiple expert opinions to select the best
variables based on a set of criteria, since the target respondents are disaster
management experts such as researchers/academics, practitioners, and policy makers,
who are working in different geographical locations, and an online survey
questionnaire was chosen as the most appropriate research method, as it can reach a
larger sample. Hence, reaching experts through an online survey data collection tool
was used for the phase II of this research.
Four key elements were highlighted by Sapsford (2006) in planning for a survey
method in research, as illustrated in Figure 4.16: Problem definition – to decide what
type of answers are required; 2. Sample selection – deciding who/what is to be counted;
3. Design of measurement – deciding what is to be measured and how; and 4. Concern
for respondents – ethical responsibility preventing harm/discomfort to the respondents
(Sapsford, 2006).
Problem definition: Survey questionnaire as a data collection technique
Online surveys are conducted by inviting potential respondents by email to
complete a questionnaire embedded in a web link and completed online (Bryman,
2015). The survey was designed in ‘Key Survey’, an online platform for surveys
provided by QUT, where this study was undertaken. An email was sent with an
introduction to the survey and inviting individuals to the URL (survey link) to
participate, if they agree to participate. The email also requested a response if the user
declined to participate in the survey (“opt out”). Two follow-up reminder emails after
Chapter 4: Research Method 99
the first publication of the survey were sent to increase the participation in the survey
(Saleh & Bista, 2017), when there was a low response rate after the first follow-up
email after four weeks’ time. The second follow-up email was sent after another two
weeks and the survey was closed eight weeks after the initial launch. The survey was
open from September to October 2018.
Purposive sampling for online survey
The online survey was also used as a purposive sampling strategy to assist in
targeting the desired sample population. The survey respondents were selected based
on their expertise and/or experience, such as people who had a minimum of three years
of experience working in disaster management, because this was the best way to elicit
the views of persons who have specific expertise and experience (Appendix I.1 for the
participant profile questions used). Three cohorts were used in the sampling
population: practitioners, policy makers, and academics/researchers, in order to elicit
their preferences for selecting the surrogates and to explore different perspectives.
There is no standard formula to calculate the required number of samples in non-
probability sampling. According to Oppenheim (2000), 100 respondents are sufficient
for most questionnaire research. However, according to Pickard (2013), 100 is rather
Figure 4.16. Survey design elements (Sapsford, 2006, p. 34)
Chapter 4: Research Method 100
high for dissertation research. Since guidance was not available in relation to the
sample population number, it was estimated to reach 200 samples with the aim to reach
a sufficient number of responses, aiming for 100. A relatively small number of experts
work in disaster management and particularly in resilience building at sub-national and
national levels in a country (approximately around 20-25 experts in each country),
which is a key limitation to reach a large number of samples.
A total of 208 experts were approached as part of the purposive sampling
approach. The list of 208 email addresses was finalised for this survey, mainly from
three sources: the directory of humanitarian organisations in Sri Lanka, email
addresses from the disaster management forum in Sri Lanka/Regions such as South
Asia, and email addresses from past regional disaster related workshops attended by
researcher.
The survey specifically targeted experts working in disaster management, such
as practitioners and policy makers from UN and NGOs, government officers working
in disaster management, and donor organisations. A list of emails was collected mainly
from the disaster management contact directory in Sri Lanka. However, many experts
who worked in disaster preparedness projects after the 2004 Tsunami in Sri Lanka
have left the country to take assignments in other countries.
Survey respondents/experts’ profile
A total of 66 experts responded to the survey. The response rate for this survey
was 32%. Among the experts who responded to the survey, 84% (n=55) have a Masters
degree qualification, and 69% (n=45) have more than five years’ experience in disaster
management. 56% of the experts were from international/local NGOs/UN agencies
and 25% were from the university/research organisations. The cluster of experts
included 52% practitioners (n=34), 23% policy makers (n=15), and 26% researchers
(n=17), making the responses inclusive and representative of all key segments in the
disaster management domain. In terms of the geographical location of the experts, 33%
were from Sri Lanka and 29% were from the South Asia region excluding Sri Lanka
(Table 4.7). Hence, the responses are largely influenced by a South Asian context, and
share similar socio-economic characteristics.
Chapter 4: Research Method 101
Table 4.7. Key characteristics and profile of survey respondents
Categories Key characteristics # of experts % of
experts
Educational
qualifications
PhD 15 24
Masters degree 40 60
Bachelors degree 7 10
Other 4 6
Experience
Less than 3 years 8 11
3-5 years 13 20
5-10 years 19 29
More than 10 years 26 40
Employment
Researchers 17 26
Practitioners 34 52
Policy makers 15 23
Affiliation
Government department 7 11
Local NGO/ Community Based
Organisation
6 10
International NGO 23 35
UN agency 7 11
Private sector/donor agency 4 6
Research organisation/institute 5 7
University 12 18
Other 2 3
Location
(country/region)
Sri Lanka 22 33
South Asia (Except Sri Lanka) 19 29
Australia/Pacific 4 7
American continent 5 7
Europe 2 4
Africa 6 8
Middle East 2 4
South East Asia 6 8
Questionnaire
There are many methods of scaling the responses to questions, and the most
appropriate method depends on the way the question is worded (Punch, 2013). The
questionnaire in this survey used the Likert scale item, which asked respondents to
identify the extent to which they agreed or disagreed with a given statement (Pickard,
2013). Likert scale is “a scaling technique that allows respondents to select a choice
that best demonstrates their level of agreement with a given statement” (Pickard, 2013,
p. 213).
In this survey, the respondents were invited to scale their responses on a Likert
scale of 1-5, in terms of the suitability of surrogates in measuring the target indicators
against the five evaluation criteria. Type of scale that is most suitable for this
questionnaire will request the degree of agreement of experts based on their evaluation
Chapter 4: Research Method 102
of each surrogate for each criterion. Each response can be structured on a five-point
scale response system, because it can produce more information, and respondents can
select their choice in a stable and straightforward way (Punch, 2013; Singh, 2007).
(See Table 4.8 below for scale of responses for each criterion). Appendix G shows the
sample email for participant recruitment, Appendix H shows the participant
information sheet sent with the email, and Appendix I.2 shows the complete set of
questions used in a key survey platform. The questionnaire consisted of three parts:
the first part had eight participants’ profile questions, the second part had 15 questions
in total (each of the three surrogates had five criteria ranking for five indicators), and
the third part had ten criteria pair-wise comparisons. It was estimated to take 20 to 25
minutes to complete the survey.
Table 4.8. Five points scale continuum for each criterion
Criteria for evaluation Five points scale along the scale continuum
1 2 3 4 5
Can measure the target
indicator accurately
Strongly
disagree
(Not
very
good)
Disagree
(Not
good)
Neither
agree or
disagree
(Neutral)
Agree
(Good)
Strongly
agree
(Very
good)
Can be transferred in
different contexts
Can be used to measure in
different phases of a disaster
Can easily communicate the
target indicator
Is cost-effective in measuring
the target indicator
Selection of scale for pair-wise comparison of criteria
A scale is required to indicate the extent to which one criterion is more important
or less important than another (Saaty, 2008), in this case, with respect to evaluating
surrogates to measure social resilience indicators in a disaster context. The nine scale
intensity proposed by Saaty (2008) was reduced to a five scale intensity of importance,
since the intermediate scales may not be needed for comparing five surrogate
evaluation criteria. The five scale is more convenient for survey respondents for
evaluating surrogates against criteria, compared to the nine scale, when the majority
of the survey respondents are not researchers. Table 4.9 below shows the scale used to
Chapter 4: Research Method 103
indicate the criteria preferences for evaluating surrogates in measuring social resilience
indicators in disaster management.
The pair-wise comparison method was executed in the following steps:
o Five surrogate evaluation criteria were formed into ten pair-wise choices in the
‘Key Survey’ platform as shown in Appendix I.3.
o The disaster management experts selected for evaluating potential surrogates
were also invited to evaluate the criteria in the same survey form; and
o Independent judgement of each expert on criteria was recorded in the key survey
platform on scale of 1–5, as explained in Table 4.9 below.
Table 4.9. Fundamental scale of absolute numbers and the scale used in the survey of
this study adapted from Saaty (2008) (p.86)
Scale in
the survey
Intensity of
Importance
in Saaty
scale
Definition Explanation
1- Equally
important 1 Equal importance
Two activities contribute
equally to the objective
2- Less
important
2 Weak or slight Experience and judgement
slightly favour one activity
over another 3 Moderate
3- Moderately
important
4 Moderate plus Experience importance and
judgement strongly favour
one activity over another 5 Strong importance
4- More
important
6 Strong plus An activity is favoured very
strongly over another; its
dominance demonstrated in
practice 7
Very strong or
demonstrated
importance
5- Extremely
important
8 Very, very strong The evidence favouring one
activity over another is of
the highest possible order of
affirmation 9
Extreme
importance
4.6.2 Phase II – Survey data analysis
In phase II of this study, multi-experts evaluated each surrogate against each
criterion on a five-point Likert scale. Inputs from experts were analysed using Multi-
Criteria Decision Analysis (MCDA) for ranking potential surrogates.
Chapter 4: Research Method 104
Survey data were analysed by aggregating all completed responses in the online
questionnaire. An initial analysis was carried out on respondent characteristics.
Respondent characteristics included the current or past role of respondents in disaster
management activities, the number of years of experience in disaster management
projects, and the affiliation of past/current portfolios such as a researcher/academic,
practitioner, or policy maker. Finally, response scales from each respondent for each
surrogate against five criteria were aggregated into variables in a multi-criteria matrix.
The values in the matrix were used for multi-expert multi-criteria decision analysis.
Multi-Expert Multi-Criteria Decision Analysis (ME-MCDA)
Cinelli et al. (2014, p. 146) defined Multi Criteria Decision Analysis (MCDA)
in assessing sustainability “as a tool to support the process of decision making by
taking into consideration multiple criteria in a flexible manner, by means of a
structured and intelligible framework.” MCDA is a good tool to make transparent
decisions in a structured manner for problems with complex information (Brinkhoff,
2011). The nine stage MCDA process shown in Figure 4.17 is briefly described below
(Hyde, 2006; Majumder, 2015):
1. Selection of disaster management experts: Experts were selected as per the
sampling criteria discussed in Section 4.6.1.
Figure 4.17. Nine stages of MCDA process adapted
from Majumder (2015)
Chapter 4: Research Method 105
2. Identification of surrogate evaluation criteria: Five key criteria were identified from
the literature review on surrogate evaluation as described in Section 3.2.3.
3. Identification of surrogates as alternatives: Alternatives are the three potential
surrogates that were identified in a case study research in phase I of this study.
4. Selection of MCDA method: Among many MCDA techniques, Preference Ranking
Organization METHods for Enrichment Evaluations (PROMETHEE) method was
selected in this study for analysis of survey data. PROMETHEE can convert Likert
scale values collected using survey questionnaires into numerical values for
analysis (Carone et al., 2018).
5. Assignment of criteria performance values: The values were five-point Likert scale
(1-5) from very good to not very good.
6. Assign weights to the surrogate evaluation criteria: Initially, equal weight was
assigned for all five criteria to obtain ranking of surrogates.
7. Ranking the potential surrogates against multi-criteria: Visual PROMETHEE was
used to rank the alternatives. Each expert ranking was compiled to Group Decision
Support System (GDSS) feature to obtain the final ranking.
8. Analyse ranking with different weights to the criteria: The criteria weights were
changed to the consolidated criteria weights obtained from Analytical Hierarchy
Process (AHP) method from the pair-wise comparisons of criteria done by the
experts in this survey. The ranking with new weights were compared with equally
weighted criteria ranking.
9. Making final decision: Potential surrogates were ranked to select the best
performing surrogates. Rankings obtained with equally weighted and expert
weighted criteria were compared.
PROMETHEE as a MCDA tool to analyse survey data
Among many multi-criteria decision analysis techniques such as Analytical
Hierarchy Process (AHP), MACBETH (Measuring Attractiveness by a Categorical
Based Evaluation. Technique), PROMETHEE-GAIA, and Technique for Order
Preference by Similarity to an Ideal Solution (TOPSIS), PROMETHEE-GAIA (GAIA
stands for Geometrical Analysis for Interactive Aid as a complementary analysis tool
in PROMETHEE) has been used by many researchers to select the best actions based
Chapter 4: Research Method 106
on multiple criteria. Verheyden and De Moor (2016) from their research on a process-
oriented social responsibility indicator for mutual funds, found that PROMETHEE
was the most appropriate methodology from the set of MCDA tools in terms of
academic and professional applications.
Table 4.10, produced by Verheyden and De Moor (2016) compares four MCDA
methods against their overall robustness, ease of implementation, transparency and
ease of understanding, and extensiveness of sensitivity analysis in the context of
qualitative indicator applications. PROMETHEE has positive aspects against many
attributes of MCDA methods. The fundamental idea of outranking methods such as
PROMETHEE is that an action is ranked higher than others, if that action performs
better than other actions in the majority of the criteria, and that action does not perform
worse in other criteria (Fernández, 2013). Carone et al. (2018) used PROMETHEE to
rank communities based on the assessment of selected social resilience indicators. In
this study, PROMETHEE was selected as the MCDA technique for the evaluation and
ranking of potential surrogates to measure social resilience indicators. PROMETHEE-
GAIA supports the comparison of alternatives between assessments at different stages
of information (dynamic re-evaluation), which is a major advantage compared to all
other MCDA techniques (Cinelli et al., 2014). The PROMETHEE method is also
useful because it can provide software supported data management and supports
comparison of scenarios for different weights for criteria and their visualisation. Visual
PROMETHEE software was used for this analysis.
Table 4.10. Comparison of Multi-Criteria Decision Analysis (MCDA) methods
(Verheyden & De Moor, 2016) (p.80)
Comparison Attribute AHP MACBE
TH
PROME
THEE
TOPS
IS
Overall robustness for application X X X
Professional application
Extensiveness of sensitivity analysis X
Academic application
Ease of implementation X X X
Transparency and ease of understanding X X X
Chapter 4: Research Method 107
PROMETHEE ranking
PROMETHEE I ranking provides a partial ordering of alternatives (in this case
potential surrogates), whereas PROMETHEE II method will give full ranking of
surrogates by calculating net flow values. In this study, PROMETHEE II ranking was
used, as it can provide a complete ranking of potential surrogates based on the net
flow. The PROMETHEE II ranking calculation procedure is as follows (Brans & De
Smet, 2016):
Step 1: Formulation of a difference matrix:
A difference matrix is produced between two data points i and i’ from the raw data
inputs. Similarly, the differences for the ith alternative with respect to other alternatives
are determined. This involves determining the differences between different pairwise
alternatives for each criterion:
𝑑𝑗 = 𝑦𝑗(𝑖) − 𝑦𝑗(𝑖′)
Where 𝑦𝑗(𝑖) and 𝑦𝑗(𝑖′) are the data points of alternatives i and i’ for criteria 𝑦𝑗
Step 2: Selection of preference function 𝑃𝑗 (𝑖, 𝑖′):
Some preferential parameters such as preference and indifference thresholds need to
be defined for each function. This is done through the selection of preference
function 𝑃𝑗 (𝑖, 𝑖′). There are six generalised preference functions available in
PROMETHEE for the user to select based on the type of criteria as shown in Figure
4.18: (1) Linear, (2) V-shape, (3) Usual, (4) U-shape, (5) Level, and (6) Gaussian. The
‘Usual’ and ‘Level’ preference functions are best suited for qualitative criteria.
For this research, the ‘Level’ function is used for the net outranking flows for each of
the experts. According to PROMETHEE guidelines (VP, 2013), the ‘Level’ preference
function is a good choice for qualitative criteria such as the 5-point scale if it is needed
to differentiate smaller deviations from larger ones. In the ‘Level’ preference function,
indifference = 0, and there is a strong preference for an action as soon as there is a
difference. If the preference is between 0 and 1, then the preference value is 0.5. For
the Group Decision Support System (GDSS), the ‘Linear’ function is used, since the
net flow is a quantitative value.
Step 3: Calculate the leaving and the entering outranking flows as given below
Leaving (positive) flow for ith alternative
Chapter 4: Research Method 108
∅+(𝑖) =1
𝑚−1 ∑ 𝜋(𝑖, 𝑖′) (𝑖 ≠ 𝑖′)𝑚
𝑖′=1
Entering (negative) flow for ith alternative
∅−(𝑖) =1
𝑚−1 ∑ 𝜋(𝑖′, 𝑖) (𝑖 ≠ 𝑖′)𝑚
𝑖′=1
The leaving flow states how much an alternative dominates the other alternatives,
while the entering flow expresses how much an alternative is dominated by the other
alternatives.
Step 4: Determine the net outranking flow:
For each alternative to rank the alternatives using PROMETHEE II (complete)
ranking, a net outranking flow is calculated as follows.
∅(𝑖) = ∅+(𝑖) − ∅−(𝑖)
Step 5: Determine the rankings:
Figure 4.18. Preference functions used in PROMETHEE (Hyde, 2006; Kilic
et al., 2015).
Legends in the graphs (P(x) is preference, x is difference, x1 is indifference
threshold, x2 is preference threshold)
Chapter 4: Research Method 109
The ranking is determined of all the considered alternatives depending on ø (i) values,
which is the net phi values. The best performing surrogate (alternative) will have the
highest ø (i) value according to PROMETHEE II (complete) ranking. In this study,
PROMEHTEE II ranking was employed using the net flow calculation as shown in
step 4.
Step 6: Group Decision Support System (GDSS):
The potential surrogates were ranked to select the best performing surrogates.
Multi-expert group decision flow chart shown in Figure 4.19 depicts the flow of inputs
from experts to the final decision-making matrix using PROMETHEE Group Decision
Support System (GDSS) algorithm (Brans & De Smet, 2016; Ishizaka & Nemery,
2013). Initially, the Likert scale evaluation value of each expert for each surrogate
against the five criteria was entered into PROMETHEE independently (the expert
Figure 4.19. Multi-expert multi-criteria group decision support system
flowchart
Chapter 4: Research Method 110
evaluation value was based on 1-5 Likert scale). By running the PROMETHEE
analysis, potential surrogates were ranked for each expert and net flow values for each
surrogate was obtained.
In the next step, GDSS algorithm was implemented in PROMETHEE to obtain
final ranks by taking each expert as a criterion and each surrogate as an alternative.
The net flow value was then entered into PROMETHEE again for each surrogate
against all 66 experts as criteria. The final ranking was obtained by performing the
multi-criteria decision analysis in PROMETHEE again from steps 1 to 5, explained
above, using the experts as criteria.
Step 7: GAIA (Geometrical Analysis for Interactive Aid) analysis:
Further to the PROMETHEE ranking, the GAIA (Geometrical Analysis for
Interactive Aid) in Visual PROMEHTEE software provides a complementary visual
analysis of the results produced in PROMETHEE. Each surrogate is represented by a
point in the GAIA plane, and its position is related to its evaluations on the set of multi-
criteria in such a way that actions with similar profiles are closer to each other. Figure
4.20 shows an example of PROMETHEE inputs for actions (actions 1 to 4) in the 1-5
Likert scale against four Decision Makers as criteria used in GDSS (DM1 to DM4),
their ranking based on net flow (Phi), and GAIA plot representation of four actions
and criteria. The GAIA plane plot helps to analyse the actions and criteria (Decision
Makers) as follows (based on the example in Figure 4.16) (Brans & De Smet, 2016):
- Similar actions are placed close to each other and vice-versa (for example, action
1 which is ranked last, is represented far from other actions in Figure 4.20)
- Vectors pointing to the same direction as the decision axis (red arrow) have
positive correlation, and the opposite direction has negative correlation (for
example DM2 has conflicting views compared to DM1, DM3, and DM4).
In this study, GAIA representation visuals were used to undertake two more
distinctive analyses based on the evaluation of potential surrogates to see: (1) how
different years of experience and experts from different cohorts aligned with the
overall PROMETHEE ranking results; (2) how their preferences varied with the
overall PROMETHEE ranking. For the first analysis in GAIA, the experts with varying
number of years of experience were clustered into four cohorts: experts with less than
three years of experience (< 3Y), three to five years of experience (3-5 Y), five to ten
Chapter 4: Research Method 111
years of experience (5-10 Y), and expert with more than 10 years of experience (10
Y). Similarly, for the second analysis in GAIA, the experts were clustered into three
cohorts based on their work affiliations: practitioners, policy makers, and researchers.
Criteria weight calculation
Analytic Hierarchy Process (AHP) is an MCDA technique with the ability to
provide a consensus based on the individual expert judgments, mostly done through
assigning weights for indicators and criteria. AHP has been used by many researchers
to determine weights for a set of indicators; for example, Alshehri et al. (2015b) used
Figure 4.20. Sample PROMETHEE inputs, ranking, and GAIA plot
Chapter 4: Research Method 112
the AHP method with disaster management experts to determine weights for different
dimensions and characteristics of community resilience to disasters. In this study, AHP
was used for determining the weight for the surrogate evaluation criteria.
Determining the criteria weight using Analytic Hierarchy Process (AHP)
In order to determine the weights for the surrogate evaluation criteria in a
participatory method, the disaster management experts who evaluated potential
surrogates were also asked to provide their preferences for pair-wise comparisons of
the five surrogate evaluation criteria. The results obtained in the key survey platform
were analysed using the latest Analytic Hierarchy Process (AHP) tool by Goepel
(2013), which is being increasingly applied in the assessment of sustainability studies
(Markelj et al., 2014; Petrini et al., 2016). The analysis of inputs obtained in the survey
to determine criteria weights was done in the following steps:
o The pairwise comparisons of each expert were recorded into a matrix developed
in Excel by Goepel (2013) to determine the weights using AHP process.
o The Consistency Ratio (CR) was calculated to establish the consistency of the
judgements provided by the experts.
o The judgements with the reasonable consistency ratio (CR < 0.2) were selected
and aggregated into a separate group decision making process in AHP.
o The final weight for the criteria was obtained and used in the PROMETHEE
multi-criteria decision making tool to evaluate the potential surrogates to measure
social resilience against these weighted criteria.
o PROMETHEE ranking was obtained for a set of potential surrogates to measure
five selected social resilience indicators with the new criteria weights and
compared with the PROMETHEE ranking obtained with equal criteria weights.
CR < 0.2 is an acceptable and permissible level of consistency (Ho et al., 2005;
Park & Youngchul Kim, 2014; Wedley, 1993), though Saaty (1990) recommends CR
< 0.1. Consistency becomes a concern due to the limited capacity of humans to keep
their judgements in pair-wise comparisons consistent with more than three criteria
when executing AHP (Asadabadi et al., 2019).
In this survey, the CR value for 14 respondents among the total of 66 survey
respondents was < 0.2. The consolidated AHP results of 14 responses showed a 71%
consensus rate of pair-wise comparisons of criteria. Since the survey in this study was
Chapter 4: Research Method 113
done only once, it was not possible to request responses again so that pair-wise
comparisons could be improved to increase consistency in their responses. Therefore,
it was decided to select the responses which had CR < 0.2 to determine the
consolidated weight for the surrogate evaluation criteria.
For example, in a Focus Group Setting, five to eight decision makers are
acceptable for AHP decision making (Udie et al., 2018). Alshehri et al. (2015b) invited
16 respondents and Udie et al. (2018) invited 19 respondents through a survey using
AHP to determine the weights for resilience dimensions in a disaster context, and to
assess vulnerability to climate change in critical infrastructure. The sample size is not
a limitation to carrying out AHP, as different studies have used very small sample
sizes, and there are many studies with smaller purposeful samples. Since this study
combined the PROMETHEE tool for ranking potential surrogates and AHP to
determine the surrogate evaluation criteria weights, the number of respondents for both
survey components were the same, 66. However, only the CR of 14 respondents was
less than 0.2, which is an acceptable level of CR determined in this study as explained
above.
Chapter 4: Research Method 114
SUMMARY
This chapter discusses a mixed method research design and sequential
exploration as a research strategy for this study. This research study was carried out in
two key phases. This chapter provided an overview of research philosophy and
methods, mixed method research strategy, data collection tools, and finally the method
of data analysis for each phase.
To achieve Research Objective 1 (RO1), five key social resilience indicators
were selected from the literature review and research design phase to apply surrogate
approach from the ‘5S’ adaptive and inclusive social resilience framework developed
in this study, based on set of surrogate decision criteria (Section 2.3). The ‘5S’ social
resilience framework consists of many indicators that are either not easily measurable
or if measured, would have used data obtained from publicly available census data,
which most often do not provide an adequate measure for process-oriented resilience
indicators.
In the qualitative phase of the research (Phase I - Interviews), to achieve
Research Objective 2 (RO2), a case study utilising interviews was adopted to explore
potential surrogates by consulting disaster management practitioners and policy
makers in the selected case study locations. The data collected from four case study
areas in the Eastern coast of Sri Lanka were analysed using Leximancer – a text data
mining tool that generates concepts and a themes map. A set of higher-order themes
were identified as key facets of the target resilience indicator, which can be used as
potential surrogates to measure each of the social resilience indicators.
In the quantitative phase of the research (Phase II - survey) to achieve Research
Objective 3 (RO3), an online survey was used to evaluate the potential surrogates
identified for the five selected social resilience indicators in phase I. A number of
disaster management experts, mainly from the practitioner, research and policy making
community, were invited to evaluate the potential surrogates against five key surrogate
evaluation criteria. The responses were then analysed using PROMETHEE – a Multi-
Criteria Decision Analysis (MCDA) method, to rank the potential surrogates based on
their overall performance against all five surrogate evaluation criteria.
Chapter 5: Interview analysis-Identification of potential surrogates 115
Chapter 5: Interview analysis-Identification
of potential surrogates
This chapter is divided into six key sections to present key findings from phase I of
this study (interviews) as shown in the chapter structure in Figure 5.1. Interviews were
utilised in Phase I of this study to identify potential surrogates to assess five selected
social resilience indicators.
Sections 5.1 to 5.5 present potential surrogates for the following five indicators:
Social mobility and access to transport in a disaster context (Indicator #1);
Social trust in a disaster context (Indicator #2);
Learnings from the past disasters as social competence (Indicator #3);
Involvement of people with specific needs as social equity (Indicator #4); and
Cultural norms/behaviours as social belief (Indicator #5).
The analysis of interview data for each indicator is structured in each section as
follows:
1. Higher-order themes for case study #1 (Kalmunai T division)
2. Higher-order themes for case study #2 (Sainthamaruthu division)
3. Higher-order themes for case study #3 (Kalmunai M division)
4. Higher-order themes for case study #4 (Sub-national level)
5. Final set of surrogates identified from cross-case synthesis: A brief discussion
about the potential surrogates, their relationship to the target indicator, and
measurement protocols to assess each indicator are provided.
6. Summary of findings
Final section 5.6 presents a summary of the overall findings and includes a final set of
six potential surrogates for each of the five social resilience indicators. This section
also provides a table of three selected potential surrogates for evaluation in the next
phase (Phase II) through an online survey.
Chapter 5: Interview analysis-Identification of potential surrogates 116
Figure 5.1. Chapter 5 and key sections in thesis structure
Chapter 5: Interview analysis-Identification of potential surrogates 117
SURROGATE MEASURES TO ASSESS SOCIAL MOBILITY AND
ACCESS TO TRANSPORT IN A DISASTER CONTEXT (INDICATOR #1)
The surrogate development framework was operationalised to identify potential
surrogates for measuring the first social resilience indicator selected in this study –
social mobility and access to transport in a disaster context. Social mobility is an aspect
of movement of people individually or collectively in a disaster situation through
available means such as transport facilities (Yamamoto et al., 2018).
5.1.1 Higher-order themes for case study #1 - Kalmunai T division (KMT)
In case study #1, 12 themes were generated and four combined themes (higher-order
themes) were identified (Figure 5.2) based on connected concept nodes in Leximancer
concept maps. These include:
1. Awareness programs and early warning drills;
2. Social support through disaster management committees;
3. Evacuation places;
4. Transport for people with specific needs.
Figure 5.2. Leximancer concept/theme maps from interview data
of case study #1
3
4
1
2
Chapter 5: Interview analysis-Identification of potential surrogates 118
(1) Awareness programs and early warning drills: Many interview respondents
highlighted that people who have higher level of awareness attend early warning
and evacuation drills annually. The awareness programs focused on people with
specific needs, who are the priority during evacuation. The contents of awareness
programs include early warning response, evacuation routes/mode and procedures.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.2): a)
frequency of awareness programs; b) early warning drills focusing on evacuating
people with specific needs; and c) information dissemination sources (such as police
and trusted sources).
“Social service department has given awareness programs for the family
members and parents of the people with specific needs. They will be
transported through vehicles such as three wheelers” (Interview #41)
“If we issue an early warning for evacuation, people have public transport
facility in the main road. There is only one village that is problematic in terms
of evacuation because it gets isolated. But we have boats available in this
location” (Interview #04)
(2) Social support through disaster management committees: This theme
mainly refers to the support from the disaster management committees for people to
access transport facilities and other mobility assistance during disaster evacuations.
The most vulnerable people seek social support from neighbours or from the
community based organisations or committees such as disaster management
committee in their area. People also request evacuation assistance from state
institutions such as from the divisional area office or other essential service
departments such as hospitals or from the police.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.2): a)
availability of emergency support services (water, first aid, public transport such as
buses); b) availability and use of emergency numbers by people in the area; and c)
availability and active DMC committees in the division.
“From the disaster committees there are arrangements to get access to vehicles.
For sick people or emergency cases, accidents, or disasters, we can access
vehicles from hospitals and police. Since there is a hospital and military forces
are available within our division, we can get vehicles. There are officers from
Chapter 5: Interview analysis-Identification of potential surrogates 119
the government departments who are also disaster committee members”
(Interview #27)
“Private vehicle owner’s data is available from us. We also have given numbers
to public transport providers. When a disaster happens, they were advised to
provide their support by providing vehicles” (Interview #28)
(3) Evacuation places: This is a stand-alone theme in this case study. The
identification of evacuation centres with adequate emergency facilities when an
early warning is issued, is a key factor for timely evacuation decision making. The
importance of awareness level among the public on where to evacuate in the event
of an early warning was also highlighted.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.2): a)
evacuation maps available in the division with evacuation centres marked; b)
number of evacuation places identified which have emergency facilities such as
toilets for people with specific needs; and c) awareness among people of the
availability of the evacuation places in their respective area.
“With the participation of the people, we have developed evacuation plans and
maps to identify safer places” (Interview #4)
“When disaster occurs, the government has decided and demarcated places of
accommodation during evacuation. Disaster Management Centre in some
evacuation centres, there are toilets and other facilities made available in the
existing evacuation places” (Interview #41)
(4) Transport for people with specific needs: Vehicles targeting people with
special needs is important for effective mobility in times of disasters. The priority
should be given to evacuating people with specific needs, and hence their transport
facilities need to be measured.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.2): a)
availability of own transport facilities for use by people with specific needs; b)
government arranged transport facilities such as emergency service vehicles; and c)
availability of vehicles with organisations for transporting people with special
needs.
Chapter 5: Interview analysis-Identification of potential surrogates 120
“Disaster management committee in each division can organise some transport
facility for the people with specific needs such as elders, children and disable
people based on the transport services and facilities available within the area.
We can’t provide transport facilities to all people and we have to give priority”
(Interview #34)
“Big vehicles are not very much available and these big vehicles cannot be used
during disasters because we don’t have wider roads to use bigger vehicles
during disaster time, because of congestion of vehicles. Push bicycles or motor
bikes are the used widely for transportation at any time and particularly during
disasters. There are some cases with people with specific needs who cannot be
transported by motor bikes” (Interview #41)
5.1.2 Higher-order themes for case study #2 – Sainthamaruthu division (SM)
In case study #2, 10 distinct themes were generated. By combining closely related
themes, four higher-order themes were identified (Figure 5.3). These included:
1. Awareness and early warning;
2. Evacuation places with facilities for people with special needs;
3. Transport facilities and vehicle owners;
4. Narrow roads.
(1) Awareness and early warning: This higher-order theme is similar to the higher-
order theme (1) in case study #1.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.3): a)
disaster preparedness awareness programs/drills conducted annually by the disaster
management committee of the area; b) how many people participate in each of the
awareness programs/drill; and c) how many people carry emergency bag during the
drill.
“Evacuation routes and maps have been displayed in many villages. This
awareness has been done through programs as to how to evacuate and where
to evacuate. This was done using pictures and they were also given
instructions” (Interview #6)
Chapter 5: Interview analysis-Identification of potential surrogates 121
“There are volunteers and youth groups in each GN division. We have provided
awareness training to them on how to evacuate people with specific needs. In
each GN there is a disaster management committee, and youth and sports clubs.
Elders, pregnant mothers, were helped by volunteers to move them to evacuation
centres” (Interview #40)
(2) Evacuation places with facilities for people with specific needs: This theme has
emphasised the importance of evacuation places with facilities for people with specific
needs. When people are aware about evacuation places that were already identified,
have emergency facilities, they are more likely to evacuate. Timely evacuation
requires access to transport facility, importantly for the people with specific needs.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.3): a)
number of evacuation places available; b) population of specific needs; and c) ratio of
evacuation places equipped with specific needs to population of specific needs.
Figure 5.3. Leximancer concept/theme maps from interview data
of case study #2
1
2
3
4
Chapter 5: Interview analysis-Identification of potential surrogates 122
“We have an evacuation centre now in our division. It is now being constructed
with facilities for special needs…… In the past we used schools and mosques as
evacuation centres. But now we can use this new evacuation centre built for the
purpose of accommodating people when disasters occur” (Interview #12)
(3) Transport facilities and vehicle owners: The vehicle ownership and their
willingness to support during disasters emerged as inter-related themes in this case
study. Access to transport facility for timely evacuation is linked to the vehicle
ownership and transports available in the area that could be accessed by the people
who do not own a vehicle.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.3): a)
type of vehicles owned by the local authorities that can be used during disasters; b)
public/common vehicle in the area; and c) mapping of emergency vehicle availability.
In case of flood, the availability of boats become important.
“Vans and bus owners are there in my area, a bus owner with five buses have
given his buses for evacuation services with free of charge as a voluntary
contribution. Similarly, tractor owners also have done the same. If we can get
the details of vehicle owners within the community to mobilise help for transport
facility during disasters” (Interview #6)
(4) Narrow roads: The theme on community infrastructure that are important for
social mobility, such as road networks and bridges connecting roads has emerged in
this case study. A vehicle needs to reach to the place of a person with specific needs
such as elders or disabled who live in the vulnerable area in order to evacuate them.
Similarly, the identification of proper evacuation routes are important, because some
roads may be narrow and larger vehicles cannot be used.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.3): a)
road conditions (narrow or wide); b) road network for effective evacuation; and c)
road features such as bridges and drainage.
“There are problems to use vehicles in massive scale due to narrow roads.…..
For example, if a person has a van, when they evacuate they will take some more
people with them. For cars and motorbike, they have to evacuate alone. Many
roads are narrow, and our bridges are very narrow that is not enough in a large
evacuation” (Interview #40)
Chapter 5: Interview analysis-Identification of potential surrogates 123
“…. we have done an evacuation and response plan in Sainthamaruthu and we
have also identified safety places for evacuation. Based on this we have made
awareness among people about evacuation routes and places. When there is a
disaster early warning, people will move towards safety centres and identified
and demarcated evacuation centres” (Interview #9)
5.1.3 Higher-order themes for case study #3 – Kalmunai M division (KMM)
In case study #3, 10 themes were generated and four combined themes were identified
as higher-order themes (Figure 5.4). These include:
1. Vehicles available in the community;
2. Evacuation roads;
3. Evacuation in mosques and schools;
4. Early warning.
(1) Vehicles available in the community: This theme highlights the existing vehicle
capacity in the geographical area or region that can be utilised during disaster
evacuation. It is important to know the location where vehicles for emergency use can
be obtained.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.4): a)
mapping of state emergency vehicle availability in the division; b) availability of
community managed vehicles; and c) private vehicle owners that can be used during
emergencies.
“We should check whether there is a local level mapping for availability of
vehicles and resources at the community level. Where the vehicles are available
and how many are available in each village. We have to check if the available
vehicles have the provisions of evacuating people with special needs” (Interview
#42)
Chapter 5: Interview analysis-Identification of potential surrogates 124
(2) Evacuation roads: Access to transport facility depends on the capacity of the
roads to cater to an evacuation during a potential disaster. This theme is related to
evacuation routes and planning. Evacuation by means of a vehicle also depends on the
road network and conditions of roads in the area.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.4): a)
evacuation route sign boards displayed on roads; b) availability of evacuation route
maps and plans with local authorities; and c) key road infrastructure availability such
as large bridges.
“We have to first talk about roads for effective evacuation. When people
evacuate, if there are any problems from the private lands that create problems
to roads, we provide compensation to those private owners and get the land for
roads to make the road network effective and smooth during disasters”.
(Interview #25)
(3) Evacuation to mosques and schools: This theme is related using public buildings
such as places of worships and schools in times of disasters. The availability of
facilities in mosques and schools for use during evacuation time is important if they
are demarcated as evacuation places.
Figure 5.4. Leximancer concept/theme maps from interview data of
case study #3
1
2
3
4
Chapter 5: Interview analysis-Identification of potential surrogates 125
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.4): a)
number of evacuation places available (Mosques/schools/public buildings/designated
buildings); b) awareness among the public of evacuation places; and c) ratio of people
evacuated and stayed in the public buildings as opposed to in houses of relatives.
“…. People went to mosques and schools, when there was a flood. The house
heads stayed back and removed belongings and safe guarded their belongings
from flood water. People with specific needs were taken by the family members
to mosques and schools” (Interview #29)
(4) Early warning: Early warning is emphasised by many interview participants in
case study #3 as an important facet for decision making for access to a transport facility
during disasters.
Four key concepts identified in this theme are (as shown in box 4 in Figure 5.4): a)
availability of early warning systems (number of early warning towers); b) public
addressing system such as loud speakers in religious places (example mosques and
temples); c) geographical coverage of early warning messages i.e. the percentage reach
to the population at risk; and d) drills conducted to test the performance of early
warning systems and messages.
“Early warning towers are built and early warning equipment are given to local
authorities. The towers were regularly tested and rehearsal programs are being
held frequently. People are trained and awareness raising programs were also
held. Evacuation boards are displayed as to how people should be evacuated”.
(Interview #32)
5.1.4 Higher-order themes for case study #4 – Sub-national level
In case study #4, nine themes were generated and four combined higher-order themes
were identified (Figure 5.5). These included:
1. Evacuation places in the area
2. Early warning systems and plan
3. Availability and access to transport facilities
4. Emergency information sources
Chapter 5: Interview analysis-Identification of potential surrogates 126
(1) Evacuation places in the area: This theme highlights the importance of
designated safe areas as part of a disaster preparedness plan to increase the resilience
of communities.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.5): a)
number of evacuation places available (religious places/schools/public buildings); b)
availability of evacuation maps with evacuation places in public (roads/public places);
and c) availability of government demarcated safer areas in evacuation plans.
“People go to near-by places, common places like a temple, school,
community hall, and temporary centres. There are places that are identified
by Disaster Management Centre and village disaster management
committees (VDMC) for people to evacuate in times of disasters” (Interview
#17)
Figure 5.5. Leximancer concept/theme maps from interview data
of case study #4
2
3
4
1
Chapter 5: Interview analysis-Identification of potential surrogates 127
(2) Early warning systems and plan: The theme on available early warning
mechanisms and proper execution plan when there is a disaster, emerged in case study
#4, which was pointed out by many interview respondents.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.5): a)
availability of early warning systems (example, Tsunami early warning towers); b)
geographical coverage of reach to the population at risk; and c) testing/drills using
early warning towers (annual Tsunami Remembrance Day drill).
“Early warning group member details should be available at the DS and village
level, which is an important indicator. The availability of contact directory of
early warning group in GN divisions and they were given identity cards is
another indicator. There is also a software system with contact details of key
people in the early warning group at the division level” (Interview #5)
(3) Availability and access to transport facilities: One of the key factors to
understand the social mobility is to know the availability and access to transport
facilities in time of disasters. It was emphasised that vehicles should be driven through
narrow roads and avoid major traffic congestions during disaster evacuation.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.5): a)
availability of public transport (buses) and other special transport systems during
disasters (boats); b) private vehicles such as tractors or ambulances from hospital or
CBOs, in cities, school vans and three-wheelers; and c) access to smaller vehicle such
as three-wheelers.
“We do resource mapping for a village. We also collect information such as how
many vehicles and where they are in the households, how many tractors, how
many carts are and where they are available. When we do village development
plan, we include these information in emergency preparedness plans”
(Interview #5)
(4) Emergency information sources: Access to information is key to improving the
mobility and access to required transport facilities during disaster warnings. The
availability of contact numbers of emergency vehicles in the community disaster
management plan can be one of the measures of access to transport facilities when
disasters occur.
Chapter 5: Interview analysis-Identification of potential surrogates 128
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.5): a)
emergency contact details and directory (available in the disaster preparedness plan
document); b) early warning groups in the village or disaster level disaster
management committees; and c) availability of early warning systems (mobile apps
and towers).
“Nowadays the information system is dependent on mobile phones.….. Disaster
Management Committee, will have an information on how to access transport or
bus. Disaster Management Centre has some information district wise and people
can call DMC and ask them for help to access transport” (Interview #13)
“We can get those information it from researches or assessments. They are
posted in the divisional offices. The numbers that are needed to contact to get a
vehicle during an emergency are sometimes available in public or posted in
administrative offices. But it is very rare to display in community. We can do a
mapping out what are the emergency vehicles available, where to get them, and
who to contact, and how to contact them to get those vehicles. This should be
displayed in common places where people often go or access to their needs to
such as library, divisional offices, and local authorities and village divisional
offices” (Interview #3)
5.1.5 Final surrogates identified from cross-case synthesis for indicator#1
Table 5.1 below summarises the mapping of higher-order themes (taken as surrogates)
which emerged from thematic analysis of interview data of four case studies.
Table 5.1. Surrogates (higher-order themes) mapping for indicator #1
Case study
locations/area
Surrogates to measure social mobility in a disaster
context
S11 S12 S13 S14 S15 S16
Case study #1
(KMT) X X X X
Case study #2
(SM) X X X X
Case study #3
(KMM) X X X X
Case study #4
(sub-national
level)
X X X X
S11: Available transport facilities (targeting people with specific needs)
Chapter 5: Interview analysis-Identification of potential surrogates 129
S12: Evacuation places and centres (including facilities for people with specific needs)
S13: Awareness programs/plans and early warning systems
S14: Evacuation routes and plans
S15: Social support systems (incl. disaster management committees and government)
S16: Emergency information dissemination and sources (including telephone numbers
to access transport)
For each of the potential surrogates, a brief description of the surrogate, its relationship
with the target indicator, and assessment protocols proposed by interview participants
from the synthesis of interview responses are summarised below.
1. Available transport facilities (targeting people with specific needs) (S11): This
surrogate was highlighted in all four case studies. Access to a transport facility during
a disaster should be planned to deal with the future disasters effectively. Timely access
to a required transport facility is necessary for effective evacuation and mobility during
and after disasters. The availability of transport facilities or timely accessibility for
transport facilities for People with Specific Needs (PwSN) was highlighted by many
interview participants in the case studies.
Further, the measurement of surrogate (S11) should include the assessment and
mapping of the ratio of vehicle ownership to population, availability of vehicles to
‘transport PwSN’ to the ‘PwSN’ ratio, and the ratio of vehicles available with
government institutions and private owners that can be used during disasters.
2. Evacuation places/centres (including facilities for people with specific needs)
(S12): This surrogate was highlighted in all four case studies. The existence of
demarcated evacuation places or purpose-built disaster evacuation centres can help the
population at risk to execute a planned evacuation during disasters. The level of
awareness among the people about the facilities at the evacuation centres will influence
the mobility of people with special needs who are the least resilient segment of the
population.
The surrogate (S12) measurement protocol can include: assessing and mapping
of evacuation places available (places of worship/schools/public buildings/designated
buildings) and its capacity, ratio of evacuation places to how many are equipped to
handle people with special needs, and the ratio between the total capacity of evacuation
places and the population at risk.
Chapter 5: Interview analysis-Identification of potential surrogates 130
3. Awareness programs/plans and early warning system (S13): This surrogate was
also highlighted in all four case studies. People at-risk should be made aware about the
mobility and accessibility to transport facilities when required during a disaster
warning or response. Awareness programs can influence the way people evacuate and
the resilience of the community to disasters by planning for effective evacuation during
disasters. The dissemination of early warning messages at the right time, to the
population at risk can help people to evacuate to safer places. Effective risk
communication result in greater mobility and allow people to prepare for timely
evacuation.
The surrogate (S13) can be measured by mapping and assessing: the existence of
early warning mechanisms such as towers, sirens, and public address systems in places
of worship and schools, annual disaster evacuation drills (ratio of people who
participated to the population at risk and number of people evacuated carrying
belongings), number of training and awareness programs related to evacuation
conducted annually in places of worship and schools, and participation trends in
training and awareness programs conducted related to evacuation.
4. Evacuation routes and plans (S14): This surrogate was highlighted in case studies
#2 and #3. The existence of evacuation routes and plans help a community to be
resilient when disasters occur, so that the community can respond to the event
effectively. Most often the evacuation plan as part of the bigger disaster management
plan identifies the requirement for transport facilities for evacuating people in the event
of a disaster. The understanding of evacuation access routes and multiple evacuation
access points will contribute to greater mobility of the community as a whole, as
highlighted by many interview participants across the four case studies.
The surrogate (S14) can be measured by mapping the key access roads including
multiple access points that are connecting to major highways, and assessing the road
conditions, road infrastructure, and evacuation signage with instructions. Further,
village or street disaster management committees and existence of evacuation plans
available with these committees can also be assessed.
5. Social support system (including from disaster management committee and
government) (S15): The social support system (support through disaster management
committees and government officials) was selected as the fifth surrogate from case
study #1. The support for accessing transport and assisting in evacuation after disaster
Chapter 5: Interview analysis-Identification of potential surrogates 131
warning from the neighbouring community and other support systems such as police
and security forces is another important factor for greater mobility. The support for
accessing transport and assisting in mobility of people to evacuate from emerging
disasters may also come from the community itself. People who are not at risk from
the emerging disaster, such as people living in less vulnerable areas within the same
community may come forward to assist people, who are living in highly vulnerable
areas.
The surrogate (S15) can be measured by assessing the resource maps available in
the village based disaster management plans, the existence of annually elected village
level disaster management committees, and the activities of disaster management
committees, helping to increase the mobility of people during disaster evacuation.
6. Emergency Information dissemination and sources (including emergency
telephone numbers of transport facilities) (S16): The emergency information sources
were selected as the sixth surrogate to measure access to transport facility from case
study #4. The dissemination of information to people at risk is an important factor for
timely access to a transport facility for evacuation during a disaster early warning.
Access to information such as emergency telephone numbers of the key organisations
involved in disaster response and recovery is needed to access required resources such
as emergency transport facility for evacuation.
The surrogate (S16) can be measured by sampling the area based social media
platforms/websites/groups, and assessing the active disaster information dissemination
services and programs, number of people who use the internet or other emergency
communication devices such as satellite phones and their usage during the disaster
warning period, and the usage of area based emergency call number services for
disaster information and requests for emergency transport facilities.
Chapter 5: Interview analysis-Identification of potential surrogates 132
5.1.6 Summary of findings for indicator #1
The study initially identified 83 concepts and 41 themes from the four case
studies for indicator #1. Similar themes were then aggregated and six higher-order
themes were identified through cross-case synthesis which can be considered as
potential surrogates to measure social mobility. The summary of the synthesis is shown
in Figure 5.6.
The following three surrogates – S11: Transport facilities available (targeting
people with specific needs), S12: Evacuation places and centres, and S13: Awareness
programs and early warning systems, have higher validity, since they were identified
across all four case studies.
Another set of relevant higher-order themes (S14: Evacuation routes and plans,
S15: Social support systems, and S16: Emergency information sources) were found in
at least one of the case studies, can also be potential surrogates to measure social
mobility in a disaster context. Hence, six potential surrogates to measure social
mobility are highly reliable and practically applicable in similar contexts, since they
were identified in consultation with practitioners and policy makers who are highly
experienced in implementing disaster management activities at the community level.
Figure 5.6. Summary of synthesis for first social resilience indicator –
social mobility and access to transport facilities
Chapter 5: Interview analysis-Identification of potential surrogates 133
SURROGATE MEASURES TO ASSESS SOCIAL TRUST IN A
DISASTER CONTEXT (INDICATOR #2)
The surrogate development framework was operationalised to identify potential
surrogates for assessing the second social resilience indicator selected in this study –
social trust in a disaster context. Social trust in a disaster context is a phenomenon
which influences the behaviour of people with other social groups and associations in
the community in disaster management activities (Thoresen et al., 2018).
5.2.1 Higher-order themes for case study #1 - Kalmunai T division (KMT)
In case study #1, nine themes were generated and four combined themes (higher-order
themes) were identified (Figure 5.7) based on connected concept nodes in the
Leximancer concept maps. These include:
1. Performance of CBOs or Effectiveness of CBO activities;
2. Public-Government officer relationship;
3. Government office/local authority support for people;
4. Effectiveness of disaster relief work.
(1) Performance of CBOs or Effectiveness of CBO activities: When discussing
social trust in disaster management work, the role of Community Based
Organisations (CBOs) such as Rural Development Society (RDS) is very much
highlighted in the context of this study area.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.7): a)
trend of people in the village participates in CBO meetings; b) how many CBOs are
active and work in relation to disaster management work; and c) percentage of CBOs
participate in disaster preparedness work such as disaster early warning testing or
drills conducted annually.
“From the Rural Development Department, we can get information. We have
at least one CBO, Rural Development Society (RDS) in each division. If RDS is
inactive, then we use Women RDS (WRDS) if it is active. If WRDS is inactive,
we go for Sports club, youth club likewise. Most often we work with RDS and
WRDS, but if they are inactive we will have to approach other CBOs. They
Chapter 5: Interview analysis-Identification of potential surrogates 134
follow up with the active CBOs. By this, we can measure the level of trust within
the community since the CBOs are within the same community” (Interview #27)
“We can measure trust based on the active and helping NGOs. The
organisations continue to be active, like SWOAD, World Vision who are
working all the time. Around, there are 65 CBOs registered. RDS, WRDS,
Sports clubs and youth clubs, and other clubs registered under departments.
Only 10-12 organisations are active. Based on their work we can measure the
trust. When disaster happen, RDS and WRDS and Civil Defence Group are the
three key CBOs in a village, who are already prepared to face disasters. They
have been elected by the people and they represent the people and they attend
to the issues when people need it. The society accepts their work since they work
for the society” (Interview #28)
Figure 5.7. Leximancer concept/theme maps from interview data of
case study #1
2
1
4
3
Chapter 5: Interview analysis-Identification of potential surrogates 135
(2) Public-Government officer relationship: This theme mainly refers to the level of
trust by the people on government systems and mechanisms which largely depends on
the relationship of government officers with the public. The first point of contact for
many people is the respective village administrator, who is a public servant employed
by the state to identify peoples’ needs at all times.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.7): a)
the level of response from the public when Divisional Secretary (DS) office requests
support or help (fund and relief collection) people affected by disasters in other areas;
b) trend in people attending meetings/campaigns convened by the government officers;
and c) response rate to the requests for community help to resolve an issue (e.g.
compensation request for disaster damage).
“Public believe government officers more. People have much hope that the
relief and recovery needs will be fulfilled. People can get clear information only
from government officers. Some organisations go to some selected places. In
those selected locations, they only select few people and provide assistance.
This creates problems and leave out many people who are in real need. 70-80%
of the people who were affected did not receive the relief support. Other
organisations do not have much information and it is with the government
officers who are in the field. We received many complains about this in the past
during this relief distribution. Then we addressed these problems. Since we
have many information, so later NGOs approached us to work in a village to
support people who were affected by Tsunami” (Interview #41)
(3) Government office/local authority support for people: The concepts emerged
in this case study have given focus on the positive efforts by government officers to
build trust. Although CBOs help people faster in disaster response, all activities are
coordinated by the government departments and local authorities. CBOs and other
organisations have to work under the government leadership, sometimes a joint
leadership by civil society and state administration, particularly in disaster
management.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.7): a)
people assisted by government from the list of people identified with needs; b) budget
allocation from the state/local authority against required finances for the projects; c)
Chapter 5: Interview analysis-Identification of potential surrogates 136
number of programs conducted/projects implemented by state/local authority from
the list of identified projects.
“For government, it has to work with circulars and it has its own capacity
limitations. Government has the responsibility to protect people from the
calamities. People think and believe that the government will somehow help
them at any point even after four months, because it is a permanent solution.
NGO solution is very short term and they will finish and go. People also know
that the government will not do things immediately” (Interview #39).
(4) Effectiveness of disaster relief work: The involvement of disaster related work
rely on the level of trust in the disaster management system. The trust largely
influences how the responsible stakeholders working in disaster management to
effectively implement their projects and coordinate with other stakeholders.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.7): a)
number Organisations actively working in disaster management; b) percentage of
assistance collected to support disaster victims outside, against the assistance within
the community (budget allocations by community based organisations); and c)
number of trained active volunteer base involved in awareness programs/information
dissemination.
“During Tsunami time, many help were done by NGOs. We guided and
facilitated NGOs through GN (Village divisions) and then DS (Divisional
administration) office. When people were staying in displacement centres, we
gathered information from people and held meetings with people and then with
NGOs to provide collected information. Complaints have come after Tsunami
disaster. Some organisations have given relief items to some segment of the
people created some suspicion. Some personal complaints have come due to
this suspicion. We guided and facilitated to solve them through DS office”
(Interview #41)
“During evacuation, disaster relief, and relief collection, people completely
collaborate. 90% of the people participate during the collection of money and
relief items for supporting disaster affected people in neighbouring villages or
other places. We do not only provide assistance to people but, also collect
money and relief support for other disaster affected people” (Interview #27).
Chapter 5: Interview analysis-Identification of potential surrogates 137
5.2.2 Higher-order themes for case study #2 – Sainthamaruthu division (SM)
In case study #2, eight distinct themes were generated. By combining closely related
themes, three higher-order themes were identified (Figure 5.8). These include:
1. Effectiveness of CBO activities/social service;
2. Level of support for awareness programs;
3. Government office (Divisional Administration Office) support for people.
(1) Effectiveness of CBO activities/social service: This theme is similar to the
theme (1) in case study #1.
Four key concepts identified in this theme are (as shown in box 1 in Figure 5.8): a)
active number of CBOs out of registered CBOs, number of projects implemented over
the past five years by active CBOs; b) membership and volunteer base of CBOs; c)
funding capacity of active CBOs; and d) reserve funding that can be utilised during
disaster time.
“CBOs, most of the time involve in relief work and community development
work. For disaster management purposes, there are local social service
organisations. There are other social service organisations too. DS office has
Rural Development Societies, Women Development Societies, Youth and Sport
Figure 5.8. Leximancer concept/theme maps from interview data
of case study #2
2
3
1
Chapter 5: Interview analysis-Identification of potential surrogates 138
Clubs, Elders society, Samurdhi Society were registered as social service
organisations. They do work with their own funding. There are district
registered organisations (NGOs). They get some funding and they also do
housing, roads, drinking water facilities, and toilet facilities” (Interview #12).
(2) Level of support for awareness programs: This theme emphasised the
importance of level of support given by the public to the awareness programs to
indicate social trust. The level of support provided by the local organisations to
implement awareness programs and the degree of public response for such awareness
programs or disaster drills show the level of trust by the public on the government
system and officers.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.8): a)
number of awareness programs conducted in the past years; b) number of people
participated in the awareness programs; and c) number of CBOs and volunteers
involved in organising the awareness programs.
“The level of trust depends on the work that the public institutions do in the
area. DS office conducts some programs such as awareness programs. We can
see how many people participate and attend those awareness programs related
to disaster management. We can measure the level of trust with the community
based organisations or societies, by measuring the contributions of people to
programs. For example, some organisations get more people when they ask for
awareness programs to come. Similarly, people will not come when some
organisations invite people to attend awareness programs” (Interview #40).
“When there is a disaster, there are some organisations who do some dedicated
work. For example, we have done a tsunami evacuation drill, a youth
parliamentarian group has done a good job. They have done a good effort on
evacuation drill, awareness, and training. Similarly, there is one society came
recently, when disasters happen, we have given a first aid training to the youth”
(Interview #16).
(3) Government office (Divisional Administration Office) support for people:
The support from government offices can measure the level of trust built with people,
as highlighted in this case study. The trust built during normal days will influence the
trust during the disaster management activities.
Chapter 5: Interview analysis-Identification of potential surrogates 139
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.8): a)
changes in number of requests/complaints to DS Office related to disaster relief or
recovery programs; b) number of people using Right to Information (RTI) services
for the past years; and c) appreciations or demonstrations/public protests/campaigns
held against the state institutions or projects in the past years.
“When disaster happens, people will approach DS office. Divisional Secretariate
(DS) will divert them to sectoral departments. If a road damaged, we will contact
Road Development Authority. If there is a problem in the lagoon, we will contact
the Municipal Council and they will do the work. They have given a call that
there is a water level increasing in lagoon and 15 houses are already under
water. I called Municipal Council and there was an excavator. The GN was in
the field with the community. When this type of work happens, people will trust
on the government system” (Interview #20).
5.2.3 Higher-order themes for case study #3 – Kalmunai M division (KMM)
In case study #3, nine themes were generated and four combined themes were
identified as higher-order themes (Figure 5.9). These include:
1. Effectiveness of community organisations;
2. Government office support for people;
3. Effectiveness of disaster relief system;
4. Complaint mechanisms available.
(1) Effectiveness of community organisations: This theme highlights the similar
theme (1) in case studies #1 and #2.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.9): a)
existence of coordination body and procedures to work in disaster management work;
b) how many petitions were made by people against the organisations; and c) number
of volunteers/human resources attached to the area organisations.
Chapter 5: Interview analysis-Identification of potential surrogates 140
“When it comes to social trust, community based organisation that have a good
preparedness and services are very less in the area. There is less organisations
that have trained human resources and good preparedness plans that can
perform well during disasters. After disasters, organisations that have grown
well from other areas and outside Kalmunai come and do the work. The existing
organisations can do some work at the minimum level, but for disaster work there
is very less if none that can do disaster work effectively. There are some
organisations like sports club. There is no trained and effective organisation to
work in disaster time” (Interview #32).
(2) Government office support for people: This theme is related to trust built by state
officials with the public in normal time that have an impact on the trust in disaster
context. Although there are limitations from state institutions to immediately act after
a disaster due to bureaucratic regulations, the state mechanism for disaster
management and coordination before and after disasters are established in each village
and division. The divisional disaster management committee presided by the divisional
secretary is the central focal point for coordinating all the disaster management efforts.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.9): a)
response rate for the request to participate in public meetings/awareness programs; b)
Figure 5.9. Leximancer concept/theme maps from interview data of case
study #3
2
4
3
1
Chapter 5: Interview analysis-Identification of potential surrogates 141
percentage of budget of the total spent/required by the government for disaster work;
and c) trend in complaints/legal cases/corruption petitions against government
officers.
“People believe that the government office will support immediately or even after
few days. For example we can see how the service by DS office on Wednesday,
how many people come to get the service in the DS office, will tell us the trust
people have on the government entities. People are aware more than us. Due to
media influence, people have more awareness and trust. People get the services
in the respective sector from the respective government counterpart” (Interview
#42).
(3) Effectiveness of disaster relief system: In this study, the concepts generated from
the interview data have focused on the trust built by the beneficiaries who received
disaster relief assistance. The level of satisfaction by beneficiaries by way of low
number of complaints lodged with respect to disaster relief system could be one of the
measures of trust.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.9): a)
duplication and gap of relief items provided to beneficiaries; b) number of
beneficiaries complaining of not receiving relief assistance; and c) trends of people
complaining lack of public services and resources in the area.
“The provisions of relief items will be same and the visibility will be different - I
mean their log are different. There is no coordination. Similar to resource
mobilisation and social cohesion, we can see how people and teams work
together in a normal situation if people work together, then during emergency,
they will work together. The work in the normal situation will reflect during
emergency. Since organisations need credit, how they work in normal situation
is important” (Interview #29)
(4) Complaint mechanisms available: The trend in complaints against an institution
could be a good measure of trust level with that institution. For example, how people
trust government institutions can be checked by the complaint trends against
government institutions.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.9): a)
trend of complains received by police or local authorities; b) public protests or publicly
Chapter 5: Interview analysis-Identification of potential surrogates 142
expressing agitation against a state entity or CBOs; and c) the use of Right to
Information/Feedback box to complain.
“There are government officers who guide these societies, for example Rural
Development Society – Rural Development officer (RDO), for youth club – Youth
Service Officer (YSO), for Sports Club – Sports Officer (SO) are there. They can
provide a feedback or observations or complain about their respective
organisations within their purview. We can get some opinion from public about
community based organisations. We can ask opinions from community leaders
and other key community members about these organisations. We can get a good
status report, if we can ask from different segments of people whose roles fall
within those respective categories. There are suggestion boxes in the DS office.
We can check suggestion box, what proposals or complaints people have made.
We can also check with audit department. Audit department gets complaints from
many sections of people” (Interview #32)
5.2.4 Higher-order themes for case study #4 –Sub-national level
In case study #4, 11 themes were generated and four combined higher-order themes
were identified (Figure 5.10). They include:
1. Trust in information and early warning dissemination;
2. Functioning of disaster relief/management system;
3. Level of services and resources;
4. Level of trust in CBOs
(1) Trust on information and early warning dissemination: One of the important
aspects of trust building is through accurate information sharing such as during early
warning dissemination. People expect local authorities and respective state institutions
responsible for disaster management to issue an effective and timely early warning
message to the public, so that the public can take the necessary steps to prepare and
evacuate to safer places in due time.
Chapter 5: Interview analysis-Identification of potential surrogates 143
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.10):
Key concepts in this theme are: a) percentage difference in people evacuated between
authorised early warning issued by authorities against false early warning (rumours);
b) percentage of people who attended annual early warning rehearsals/awareness
programs; and c) number of phone calls made to DMC hotline/emergency number for
early warning confirmation.
“The trust building should start with proper warning. Met department has a
problem with the trust level on the warning and prediction. Early warning
government structure should be established with last mile reach. There are
excuses. I expect that the information should come to me. Timely warning is the
first step of trust. The first step of trust is whether people get the warning”.
(Interview #13)
“There was a Tsunami rumour two weeks back, 40 to 50 people called me. I told
them that there is no Tsunami. People believed in the rumour. The dissemination
of the early warning is not enough to the speed that the rumour spreads.
Figure 5.10. Leximancer concept/theme maps from
interview data of case study #4
2
1
4 3
Chapter 5: Interview analysis-Identification of potential surrogates 144
………But normally the Police with Red Cross volunteers provide early warning
dissemination. There was no evidence for a Tsunami. The whole district was
affected by the rumour” (Interview #14)
(2) Functioning of disaster relief/management system: There are disaster
management committees formed in most of the villages under the Divisional Secretary
with the help of the Disaster Management Centre. However, the existence of such a
committee and a system does not alone build trust among the public. Instead they will
have to function in disaster preparedness phase and continue to prepare for disasters.
The level of trust in the committee and the system can be measured by its effectiveness
and regular functioning mechanisms.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.10): a)
annual trend in implementing Disaster Management (DM) related projects and people
support/participation; b) frequency of DM committee meetings per year and actions
implemented; and c) number of people trained in DM related programs such as first
aid.
“After 2004 Tsunami, the government and people started to talk about disaster
management. Government also started to work in disaster management. But
before that there were lots of rumours. There is a disaster management centre
hotline number - 117. We can see number of calls from public to see how people
trust disaster management activities. Like 117, at the national level we have 119.
People also see the media news….we have to say that the social trust has
increased. Sri Lanka government also has done many work at the field level. After
people face a disaster, the trust level increases. Now, the disaster management
committee and awareness programs are well established in the field level….we
don’t receive complaints directly. There are many CBOs and NGOs, but they are
not working in disaster management. Not many work is done in disaster
management currently” (Interview #26)
(3) Level of services and resources: People believe in a system based on the
satisfactory level of service and availability of resources within the system. For
example, for the public to trust the local authorities, they need to provide services to
the level of public satisfaction, and in return people will pay their taxes to the local
authorities. When there is lack of trust in the government system, people will start to
complain about the services and resources.
Chapter 5: Interview analysis-Identification of potential surrogates 145
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.10): a)
trend in the percentage of people who pay local authority tax annually; b) services such
as compensations for disaster losses promised and provided by the government; and c)
trend in problem reporting/lodging complaints to Police/DS office/Mediation board.
“The government offices are helping the people. But for local authorities, people
have to pay tax to services. One measure would be, number of people who pay
tax. If they trust they pay tax. If they ask people about common services that they
offer, for example solid waste, building approval, those things will show trust. In
the meantime the level of corruption is also high” (Interview #14)
“When there is some distribution or resource allocation, to implement a project,
there is no collaboration and coordination because it is very difficult to do. For
example to DS office and Municipal Council – how many service related petitions
have been lodged? We have formed a disaster management committee and we
need to coordinate” (Interview #11)
(4) Level of trust in CBOs: Since Community Based Organisations (CBOs) play an
important role in disaster management work and their close relationship with the
community, the level of trust determines the effectiveness in disaster preparedness and
response activities in a particular community.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.10): a)
functions of the Disaster Management Committee at the village level; b) trend in
volunteerism (capacity of volunteers and their projects); and c) ratio of participation
of members/CBOs in a regular public meetings in a division.
“Compared to the government institutions and local authorities, there is higher
level of trust with CBOs. When disaster happens, CBOs immediately do help and
relief work. People accept this and until people recover from disasters, these
CBOs continue to take care of peoples’ needs and get the complaints of people.
There is a maintenance body and leadership. There is a coordination and people
can lodge there complaints to this committee. Due to non-service of the
government, a new committee is formed. Those who need to do the work did not
do it, so the need for a new committee was realised” (Interview #11)
Chapter 5: Interview analysis-Identification of potential surrogates 146
5.2.5 Final surrogates identified through cross-case synthesis for indicator #2
Table 5.2 below summarises the mapping of higher-order themes (taken as
surrogates) which emerged from the thematic analysis of interview data from the four
case studies.
Table 5.2. Surrogates (higher-order themes) mapping for indicator#2
Case study
locations/area
Surrogates to measure social trust in disaster
management
S21 S22 S23 S24 S25 S26
Case study #1
(KMT) X X X X
Case study #2 (SM) X X X
Case study #3
(KMM) X X X
Case study #4 (sub-
national level) X X X X
S21: Effectiveness of Community Based Organisations (CBOs)/social service
S22: Level of services and resources of local authorities/state support for people
S23: Functioning and effectiveness of disaster management systems and complaint
mechanisms
S24: Trust on information sharing /early warning dissemination
S25: Level of public support for awareness and public programs
S26: Public-government officer relationship
For each of the potential surrogates, a brief description of the surrogate, its relationship
with the target indicator, and assessment protocols from the synthesis of interview
responses are summarised below.
1. Effectiveness of Community Based Organisations/social service (S21): This
surrogate was highlighted in all four case studies. Community Based Organisations
(CBOs) were highlighted as the key stakeholders in disaster management activities by
many interview participants across many case studies. Immediately after a disaster,
people have lack of trust on government mechanisms for help at least for the first three
days (72 hours). This fact was acknowledged even by the government officials,
because of rigid state procedures and bureaucracies do not allow the village level state
departments and officers to make decisions. They have to depend on the top for
decisions that will get delayed and people start to criticise the government although
Chapter 5: Interview analysis-Identification of potential surrogates 147
they know this fact. However, people have more trust in CBOs that fill the gap in
disaster relief and recovery assistance during the time that government is unable to act
and mobilise resources.
Further, the measurement of this surrogate (S21) should include the assessment
and mapping of active and non-active CBOs in the selected region and their past
experiences in disaster management work. The assessment should also include their
present capacity such as the number of memberships/volunteers/networks and
resources in disaster management activities including the provision for disaster
management work in their constitutions.
2. Level of services and resources of local authorities/state support for people (S22):
This surrogate was also highlighted in all four case studies. An effective system of
providing service to the public by the government institutions and local authorities is
a key component of building trust with the public. The level of public service depends
on the commitment of the government staff towards providing the required services in
a timely manner and have sufficient resources needed to deliver the public services.
The surrogate (S22) can be measured by mapping and assessing the measure of
the projects implemented by state/local authorities against the total identified number
of projects, measure of the percentage of budget spent on projects against the budget
needed/ requested, and measure of the percentage of beneficiaries supported in disaster
management projects of the total identified people who needed help during disasters.
3. Functioning and effectiveness of disaster management systems/complaint
mechanisms (S23): This surrogate was highlighted in three of the case studies, except
case study#2. The social trust is built on the effectiveness of service delivery during
disasters and people weigh the support during the difficult times that they needed help.
The functioning of a disaster relief system with all primary stakeholders within a
community is key to building trust. The more people have trust, the less complaints
and vice versa. Hence, measuring the effectiveness of the disaster relief system by
understanding the existing disaster management committee structure and commitment
can be a surrogate measure of social trust.
The surrogate (S23) measurement protocol can include: measure of active
functioning of village/community level disaster management committee (such as
frequency of meetings, participation rate of committee members, and existence of a
Chapter 5: Interview analysis-Identification of potential surrogates 148
disaster management plan) and measure the existence of complaint mechanisms
through the availability of a communication mechanism by the disaster management
committee, the availability of a complaint portal, and the trend in the number of
complaints received/demonstrations/other forms of resistance.
4. Trust on information sharing /early warning dissemination (S24): This surrogate
was only highlighted in case study #4. Information such as early warning messages
and evacuation procedures are very important for successful disaster management
work. The government entities such as Disaster Management Centre (DMC) is
responsible for issuing an early warning message to the public through an authorised
channel such as Police and DS offices. When an early warning message is issued, the
way people react depends on the trust with the early warning issuing mechanism or
dissemination authority. For example, if people evacuate from their places of living
when the disaster management centre issues a warning, it is a good indicator of trust
in the Disaster Management Centre. Similarly, the trust can be measured with other
social entities such as religious places, which also disseminate early warnings.
The surrogate (S24) can be measured by the percentage of people evacuated from
the vulnerable areas, measure the number of people self-evacuated/reached
displacement centre, percentage of people who participated in an early warning
rehearsal program or awareness programs conducted annually, and number of phone
calls made by the public to disaster hotline numbers such as 117 for early warning
clarification.
5. Level of public support for awareness and public programs (S25): The level of
public support for awareness and public programs was selected as the fifth surrogate
from case study#2. Social trust can be measured by the level of public support given,
when the disaster related awareness programs or other public programs are organised
in a community. The presence of number of community members invited is an
indication of the level of trust on the benefits of the program. The changes in number
of attendance annually can also be measured to see how the level of trust changes over
time. In addition to public participation, the measure can also include the involvement
of volunteers and community based organisations/social service organisation members
in organising such awareness programs/events to indicate the level of trust among the
public.
Chapter 5: Interview analysis-Identification of potential surrogates 149
The surrogate (S25) can be measured by the number of awareness programs
conducted in the past five years, the trend in the number of people participating in
awareness programs, and the number of CBOs and volunteers involved in organising
such awareness programs.
6. Public-government officer relationship (S26): The public-government officer
relationship was highlighted as a key facet of social trust in case study#1. The way the
state officers responsible for the public service carries out their daily routine is critical
to build trust with the public. Their duty is done through the departmental work and
the trust is built on the effectiveness of their work. The relationship and the trust built
during normal working time will reflect in the trust during disaster work. Hence,
public-government officer relationship can be one of the surrogates to measure social
trust in a disaster context.
The surrogate (S26) can be measured by identifying the meetings or campaigns
convened by each of the government officers, calculating the percentage of attendance
of the public in such campaigns and meetings, the response rate/trend in support for
relief or fund collection campaigns by people in the area, and the trend in
complaints/legal cases reported against the government officers.
Chapter 5: Interview analysis-Identification of potential surrogates 150
5.2.6 Summary of findings for indicator #2
The study initially identified 91 concepts and 37 themes from four case studies
for indicator #2. Similar themes were then aggregated and six higher-order themes
were identified through cross-case synthesis which can be considered as potential
surrogates to measure social trust. The summary of the synthesis is shown in Figure
5.11.
The following three surrogates – S21: Effectiveness of Community Based
Organisations’ activities/social service, S22: Level of services and resources of local
authorities/State support for people, and S23: Functioning and effectiveness of disaster
management systems and complaint mechanisms, have higher validity, since these
were identified in at least three of the four case studies.
Another set of relevant higher-order themes (S24: Trust on information sharing
/early warning dissemination; S25: Level of public support for awareness and public
programs; S26: Public-government officer relationship) were found in at least one of
the case studies, can also be potential surrogates to measure social trust in a disaster
context. Hence, six potential surrogates to measure social trust are highly reliable and
practically applicable in similar contexts, since these were identified in consultation
with practitioners and policy makers who are highly experienced in implementing
disaster management activities at the community level.
Figure 5.11. Summary of synthesis for second social resilience indicator –
social trust
Chapter 5: Interview analysis-Identification of potential surrogates 151
SURROGATE MEASURES TO ASSESS LEARNINGS FROM THE
PAST DISASTERS AS SOCIAL COMPETENCE (INDICATOR #3)
The surrogate development framework was operationalised to identify potential
surrogates for assessing the third social resilience indicator selected in this study –
learnings from the past disasters as social competence. Social competence gained
through past disaster experiences is about how communities utilise their positive and
negative learnings to improve preparedness and recovery activities for future disaster
events (Hoffmann & Muttarak, 2017).
5.3.1 Higher-order themes for case study #1 - Kalmunai T division (KMT)
In case study #1, 10 themes were generated and four combined themes (higher-order
themes) were identified (Figure 5.12) based on connected concept nodes in the
Leximancer concept maps. These were:
1. Evacuation drills
2. Reaction to early warning
3. Disaster awareness/knowledge level
4. New construction methods (e.g. Houses)
Figure 5.12. Leximancer concept/theme maps from interview data
of case study #1
1
2
3
4
Chapter 5: Interview analysis-Identification of potential surrogates 152
(1) Evacuation drills: An increase in participation in annual evacuation drills by the
population most vulnerable to disasters may indicate lessons learnt from the past
disasters. Disaster evacuation drills and exercises are carried out regularly – for
example in the case of Tsunami which is done annually.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.12): a)
participation of people (percentage increase after the disaster) in disaster drills; b)
number of people who carried disaster grab bag during the disaster drill; and c) the
level of support by CBOs and other stakeholders to conduct drills.’
“Disaster drills are conducted by the Disaster Management Centre. The
participation of people in these disaster drills has increased over time. People
show interest in learning new knowledge and experiences from the past about
Tsunami and other disasters. Disaster drills are conducted for the people
continuously. It was made clear to people during disaster drills and awareness
programs that how they should evacuate, what are the procedures for
evacuation, and what kind of relief support they will receive after a disaster”.
(Interview #41)
“In the past people ran and evacuated with a bag that contains important
documents and money. We have done a mock drill. People know now and they
were made more awareness. We have done the drills in all the coastal areas”
(Interview #28)
(2) Reaction to early warning: The changes in reaction to early warning before and
after a disaster could be a measure of learnings from the past disasters. Before a disaster
experience, people may not have any knowledge about the disasters, for example, the
tsunami in 2004 in Sri Lanka. After the 2004 tsunami, people react to early warnings
issued by the local authorities differently. The difference in reaction is due to lessons
from the past experience.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.12): a)
changes in issuing proper early warning messages to the population vulnerable to
disaster risks; b) changes in evacuation of people for evacuation early warning
messages; and c) participation of people in awareness programs held to provide new
knowledge about early warnings.
Chapter 5: Interview analysis-Identification of potential surrogates 153
“People have good awareness now about early warning. When an early
warning message is issued, people become alert. We have done many
awareness programs and tsunami mock drills. We have two Tsunami early
warning towers in this region. People will not accept the early warning
messages from other people. They will only accept early warning messages
from religious places such as temples and mosques and from the DS (Divisional
Government Administration) office. However, sometimes, even when there was
a tsunami rumour, people moved immediately away from the disaster prone
coastal areas” (Interview #28)
(3) Disaster awareness/knowledge level: People learn from every disaster, a lesson
that helps them to prepare for future disasters. The efforts taken after a disaster to
raise level of awareness can indicate the learnings from the past disaster experience.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.12): a)
changes in participation in disaster awareness events by the public; b) involvement of
community based organisations in organising awareness events/interest shown; and
c) changes in disaster risk reduction activities before and after disaster.
“We have done awareness programs about disaster management. When we ask
people what will you do when disasters happen, people say that they are
prepared with the disaster grab bag. People tell us even before we do
awareness programs. They have clinic card, people will take medical cards and
other important documents and they have kept them in disaster bags they
already prepared. They also know which way to evacuate and what the routes
they should do evacuation are” (Interview #28)
(4) New construction methods (e.g. Houses): An example was highlighted for not
taking actions from the past flooding experience in this case study area. Problems
were identified with drainage and it was the primary cause of flooding. However, no
learnings from the past seem to be accounted to prevent flooding by solving the
drainage problems. This shows the lack of willingness to take the past experience into
account to address the emerging disaster related challenges.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.12): a)
changes in new housing constructions (incorporating DRR measures); b) public
Chapter 5: Interview analysis-Identification of potential surrogates 154
infrastructure DRR integration projects such as drainage systems; and c) no
development in the identified risk areas.
“When concrete roads are constructed or people construct houses, they have
to lay pipes from their houses to the drainage canals. During the time of
construction, they should have kept a pipeline to send the water out of their
house to the drainage. People wait until the flood water gets into their houses
and later they will damage the roads to send the water out. This should have
been done before. If people have an awareness and proper knowledge on how
to divert and send the water out of their houses when they construct houses,
they would have placed water carrying pipes properly” (Interview #4)
5.3.2 Higher-order themes for case study #2 – Sainthamaruthu division (SM)
In case study #2, eight distinct themes were generated. By combining closely related
themes, three higher-order themes were identified (Figure 5.13). They include:
1. Degree of government disaster preparedness work;
2. Disaster awareness/knowledge level;
3. Reaction to disaster early warning.
(1) Degree of government disaster preparedness work: Many government
institutions involve in disaster management work. New initiatives and projects are
initiated by government institutions before and after disasters. The changes in the
initiatives can provide a measure of learnings from the past disasters.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.13): a)
the changes in disaster preparedness projects before and after disasters; b) new
modifications in the government disaster preparedness plans after disasters; and c)
changes in government regulations/circulars/policies to mitigate and prevent disasters
damages.
“A twitter communication system is developed. In this twitter group government
officers are there. So they are included. People did not take risk reduction
measures to prepare for disasters in constructing their buildings and to reduce
the impact the losses. Government institutions have built new buildings taking
into account the disaster risks. People have no knowledge about the disaster
Chapter 5: Interview analysis-Identification of potential surrogates 155
resilient housing construction. Even government institutions also lack this
knowledge. Even the masons who construct buildings are also not
knowledgeable” (Interview #16)
“Sometimes people do not take steps on their own. People have the mentality
that they expect the government institutions to do everything. People do not do
projects themselves very much, but depend on government or other projects
externally initiated. At the government level, have a very good preparedness.
We have a good preparedness plan. So, people are prepared because
government is well prepared to face future disasters” (Interview #20)
(2) Disaster awareness/knowledge level: People learn from every disaster a lesson
that helps them to prepare for future disasters and the efforts taken after a disaster to
raise the level of awareness can indicate the learnings from past disasters.
Four key concepts identified in this theme are (as shown in box 2 in Figure 5.13): a)
self-initiations by people at the individual/household level disaster preparedness
Figure 5.13. Leximancer concept/theme maps from interview data of
case study #2
1
3
2
Chapter 5: Interview analysis-Identification of potential surrogates 156
activities; b) importance given to awareness programs such as new initiatives on
DRR; and c) increase in number of people participate; and d) participation in disaster
drills with new learnings such as preparedness kits.
“People who were affected by disasters have some experience, so we learned
lessons. We do awareness programs for children who are born after major
disasters. We have also done awareness programs for school teachers. Disaster
Management Centre in districts have video clips and practice about past
disasters. We have school awareness programs, combining public and school
children. We have also done awareness programs and discussions regularly with
the school principals. The awareness programs include the knowledge about
hazards and what precautions can be done. We have instructed people using
disaster examples happened recently” (Interview #12)
(3) Reaction to disaster early warning: Reaction to disaster early warning can help
to understand the learnings from the past disaster experiences. People learning from
the past disaster early warnings and improving their response to upcoming early
warning messages, is a key indication of learnings from the past disaster experience.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.13): a)
changes in early warning systems such as early warning tower, new disaster drills,
and early warning testing programs; b) differences in reaction to early warning
messages before and after disasters; and c) participation trends in early
warning/evacuation drills.
“The last 2004 Tsunami was not known to anyone. People went to see the sea
instead of going away. People only know that sea is coming to land. Now Disaster
Management Centre has done awareness programs for the last 13 years, now
people know what Tsunami is. People now have the knowledge, how to evacuate
when an early warning is issued. Earlier, it was told that when there is an
earthquake in Sumatra, it will take two and half hours to come to Sri Lanka. Now
we have made people aware” (Interview #40)
5.3.3 Higher-order themes for case study #3 – Kalmunai M division (KMM)
In case study #4, nine themes for case study #3 were generated and four combined
themes were identified as higher-order themes (Figure 5.14). This include:
1. Initiatives of disaster management committees or members;
Chapter 5: Interview analysis-Identification of potential surrogates 157
2. New DRR programs (e.g. changes in buildings/infrastructure designs);
3. Changes in awareness knowledge;
4. Reaction to early warning.
(1) Initiatives of disaster management committees or members: Disasters often
highlight the need for active disaster management committees and members. Disaster
management committees can help to organise not only response to disasters
effectively, but can also play a key role in Disaster Risk Reduction (DRR). The
learnings from past disasters may trigger an inactive committee to work actively after
disasters based on past learnings. When there is no such committee dedicated to focus
on DRR work, there is an opportunity to establish such a committee after a disaster.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.14): a)
new committees established after recent disasters; b) new projects implemented after
recent disasters; and c) changes in committee work plans (improvements).
“People were already instructed about the evacuation locations and routes. We
also created a committee and they convene monthly meetings and discuss
Figure 5.14. Leximancer concept/theme maps from interview data
of case study #3
4
3
1
2
Chapter 5: Interview analysis-Identification of potential surrogates 158
disaster preparedness work. The committees function when there is a disaster”
(Interview #29)
“Since people are educated, they have a good knowledge. We have disaster
preparedness committee in each GN and with WRDS and RDS and other Social
Service Organisations, we do many awareness programs. These programs were
done with the disaster management centre to raise awareness and during the
committee meetings, we do awareness raising programs once in six months”
(Interview #19)
(2) New DRR programs (e.g. changes in buildings/infrastructure designs): The
past disaster experience helps the community to take proactive initiatives to reduce
risk from future disasters. For example, when water enters into the houses during flood,
people raise the foundation of the newly built houses. After 2004 Tsunami, people
changed their house designs and build upstairs houses. Similar type of disaster risk
reduction programs can be an indicator that people learned lessons from past disasters
and apply those lessons to reduce damages from future disasters by increasing their
resilience.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.14): a)
changes in housing/infrastructure designs in the disaster prone areas; b) records of new
DRR projects implemented after recent disasters; and c) new regulations/law/circulars
to reduce the impact of disasters.
“When we discuss about Tsunami, the land use in the coastal area has changed.
Now the coastal area was declared as a buffer zone. There were many houses
and buildings and now it is not the residential area. This new regulation has
imposed restrictions on building new constructions. There will be no permission
given in these area for buildings. Schools and other public buildings were not
given permission to operate and the law is enforced to restrict constructions in
this area. The area is also not allowed for construction, where people gather at
large numbers. People are now aware and on alert. New designs were also
introduced. The foundation level has increased in the flood prone areas. The
design of building constructions has changed to reduce future disaster losses”
(Interview #42)
Chapter 5: Interview analysis-Identification of potential surrogates 159
(3) Changes in awareness knowledge: The changes in awareness campaign can be
explored to measure the improvements and level of learnings incorporated in new
disaster awareness program strategies. People may attend more enthusiastically in
awareness and training programs related to disasters based on past experience.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.14): a)
increased level of awareness programs and participation; b) increased volunteer
contribution and new stakeholders in organising awareness programs and disaster
related trainings; and c) different types of awareness programs (innovative).
“Many training programs were conducted and the knowledge has transferred to
different levels in the community. The training programs were done for many
segment of people like children, female, people with specific needs and other
different segment of population. There are many media work on DRR. We can
check them – if they produced CD or video, handbills for raising awareness”
(Interview #25)
(4) Reaction to early warning: Early warning plays a key role in disaster
management, particularly for disasters such as Tsunami. When an early warning alert
is issued to the population at-risk, the reaction of people may vary based on the past
learnings from disasters. In the village level disaster management structure, there is a
village level disaster management committee and there are sub-committees.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.14): a)
pre and post activities of early warning sub-committee under the village DM
committee; b) peoples’ reaction to disaster drills such as preparedness level in safe
guarding important documents; and c) number of people evacuated with and without
official early warning messages from local authorities.
“We can see their disaster preparedness activity. When there was an evacuation
during the tsunami rumour recently, people evacuated with important
documents. We could see them with these important documents when they
evacuate from their villages. This is an evidence from their past lessons. People
immediately went to schools and get their children, when there was an early
warning issued. People move children immediately from their houses as a
priority” (Interview #29)
Chapter 5: Interview analysis-Identification of potential surrogates 160
5.3.4 Higher-order themes for case study #4 – Sub-national level
In case study #4, seven themes were generated and four combined higher-order themes
were identified (Figure 5.15). These include:
1. Government action and community reaction to early warning;
2. Disaster evacuation/preparedness kit;
3. Disaster risk reduction work (New building structures);
4. Village level disaster management committee.
(1) Government action and community reaction to early warning: One of the key
components of disaster resilience strategy is to enhance effective early warning
generation, transmission, and dissemination to the last mile. The responsible authority
to issue early warning is mostly assigned to a state disaster management authority. The
past disaster experience highly influences not only on the government side, but also
among the community in reacting to the early warning.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.15): a)
changes in past to present investment in disaster early warning systems and awareness
Figure 5.15. Leximancer concept/theme maps from interview
data of case study #4
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2
1
4
1
Chapter 5: Interview analysis-Identification of potential surrogates 161
programs by the state; b) disaster drills and knowledge about evacuation locations; and
c) plan with early warning dissemination methods.
“When we issued a tsunami early warning even in the mid night time, people
evacuated timely. They have good preparedness. People who are geographically
and economically vulnerable, cooperate well for disaster drills. Sometimes we
expect 100 people, but around 300 people turnout during the drills. In some
areas, cooperation is very less and we think it is due to their lack of interest,
since their area was not affected much during the past tsunami. In the areas
which were affected badly, people give good cooperation” (Interview #26)
(2) Disaster evacuation/preparedness kit: Every disaster teaches different lessons to
people who are affected by those disasters and to the authorities who manage those
disasters. One of the learnings from the past to improve future resilience is to be better
prepare at the household level, to help people to recover back from the impact of
disasters quickly. Most of the interview participants were of the view that they noticed
during disaster evacuation drill, an increasing trend in people bringing a disaster
preparedness kit that is kept ready in their houses with important documents covered
in safe pockets.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.15): a)
number of households have prepared emergency kits; b) households have emergency
contact list and numbers; and c) sale of emergency preparedness kits/items by the local
shops.
“After fire incidents, how many people bought fire extinguishers? Items like first
aid kits and fire extinguishers can be checked in places that are sold. We can see
how many have been sold in the area. Laminating facility – how many people
have done laminated documents. Similarly we can check with the banks how
many people use safe lockers, after a disaster event” (Interview #10)
(3) Disaster risk reduction work (New building structures): Disaster Risk
Reduction (DRR) is the key driving theme in resilience literature. After a disaster,
DRR becomes a central talk in policy discussions and there is a tendency to forget
DRR after sometime. Therefore DRR should become a mainstreaming theme in all
development projects and budget allocations. Based on the past learnings from disaster
Chapter 5: Interview analysis-Identification of potential surrogates 162
damages, new DRR initiatives need to be taken on board to reduce future disaster
losses.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.15): a)
availability of a disaster risk map in each division; b) trend in financial investment (or
separate budget allocation in DRR projects/number of projects addresses DRR; and c)
changes in infrastructure development policy/practice.
“We can check the financial investment by the community in their village
themselves, if there is an increase, then there is an interest shown and people
take into account the past disaster experience. Even in divisional meeting, a
community based organisation talks about DRR work, then it shows that they
have learnt lessons from the past to prepare for future disasters. Changes in the
number of DRR projects can be a good measure. We can financially measure the
level of DRR investment. If there are three agro wells constructed after a disaster
by the irrigation department, then there is lessons learnt. We can also check
number of letters comes from the community to DS office asking for DRR
projects” (Interview #5)
(4) Village level disaster management committee: It is essential that the committee
manages all activities related to disasters provides a coordinated and effective
mechanism to overcome challenges. When a disaster management committee at the
village level exists before a disaster, the changes in its function can be identified to see
how the past learnings from the previous disaster were taken on board. When there is
no such committee at the village or divisional level before the disaster occurs, the
indicator could be the formation of a new committee since the village could have felt
the need for such a committee to manage future disasters.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.15): a)
the availability of disaster stakeholder list and emergency contact list; b) the
availability of core group of people trained on critical disaster management skills such
as first aid; and c) function of the existing committee and projects implemented.
“Civil security committees are formed very recently. This was formed in every
village after the war to deal with security issues and to stabilise the villages
towards security issues. But now these groups have broadened their focus beyond
security issues and included disaster issues. There is a system and organisations
Chapter 5: Interview analysis-Identification of potential surrogates 163
like us have given capacity building programs. These committees can deal with
all problems in a village, but they need to be given more capacity building. They
have to be fully equipped. After tsunami and floods, Disaster Management
Committees or units were started” (Interview #1)
5.3.5 Final surrogates identified through cross-case synthesis for indicator #3
Table 5.3 below summarises the mapping of higher-order themes (taken as
surrogates) which emerged from the thematic analysis of interview data from the four
case studies.
Table 5.3. Surrogates (higher-order themes) mapping for indicator#3
Case study
locations/area
Surrogates to measure learnings from the past
disaster experience (Emerging themes)
S31 S32 S33 S34 S35 S36
Case study #1
(KMT) X X X X
Case study #2 (SM) X X X
Case study #3
(KMM) X X X X
Case study #4 (sub-
national level) X X X X
S31: Reaction to disaster early warning
S32: Awareness and disaster knowledge level
S33: New DRR programs such as innovative construction methods
S34: Functional level of the disaster committee/members
S35: Disaster Risk Reduction (DRR) & Disaster Preparedness (DP) strategy
S36: Evacuation drills & disaster preparedness kits
For each of the potential surrogates, a brief description of the surrogate, its
relationship with the target indicator, and assessment protocols from the synthesis of
interview responses are summarised below.
1. Reaction to disaster early warning (S31): This surrogate was highlighted in all four
case studies. The key objective of any disaster preparedness activity is to save lives.
Early warning plays an important role in providing required information to people for
their necessary actions in a timely manner. An appropriate reaction to early warning
Chapter 5: Interview analysis-Identification of potential surrogates 164
messages from the public enhances their resilience to disasters. The effectiveness of
reaction to early warning increases based on the learnings from the past disaster
experience. All four case studies have highlighted the reaction to disaster early
warning as a surrogate measure to learnings from the past, since there have been often
many improvements on early warning systems and peoples’ reaction to early warning
based on the past disaster learnings.
The surrogate (S31) can be measured by identifying the early warning systems
built after a disaster, the past real early warning instances, early warning/evacuation
drills, the reaction of the public by number of people who reacted appropriately, trend
in number of confirmation calls to disaster management centre after early warning
messages, and the number of people evacuated with and without official early warning
messages from local authorities.
2. Awareness and disaster knowledge level (S32): This surrogate was also highlighted
among three case studies #1, #2, and #3. The knowledge about disaster risks and
awareness of disaster risk reduction and preparedness methods are important factors
influencing disaster resilience of a community. When the awareness level of disasters
is higher, the community is well prepared to manage future disasters. In Sri Lanka,
2004 tsunami was one of the examples that showed that Sri Lanka as a country has
very minimal awareness and knowledge about tsunami. This disaster was a turning
point for major changes and a national policy shift in disaster management. Hence, the
key factor of influence for the lessons from past disaster experience could be attributed
to awareness and disaster knowledge of past disasters and future disaster risks.
The surrogate (S32) can be measured by awareness/training/capacity building
programs conducted over the past years, public participation trend in
awareness/training/capacity building programs, and the support by community based
organisation/other stakeholder engagement in organising the awareness programs.
3. New DRR programs such as innovative construction methods (S33): New DRR
programs such as innovative construction methods was selected as the fifth surrogate
from case studies #1, #3, and #4. The learnings from past disasters help people to
improve disaster resilience strategies. There could be many initiatives to reduce the
foreseen disaster risk and prepare for them. These measures can be structural and non-
structural. While people apply some DRR actions at the household level, for example,
people raise the foundation of their houses above the past flood level, or build a room
Chapter 5: Interview analysis-Identification of potential surrogates 165
in the upper floor or reinforce the roof with stronger structures, when they construct
new houses and infrastructure. There could be many new innovative solutions
proposed for reducing the future disaster risks and preparing better for emerging
disasters. The learnings from the past disaster experience triggers people, responsible
community leaders and state officials to take necessary steps to avoid the previous
mistakes being repeated.
The surrogate (S33) can be measured by analysing the new projects implemented
after a recent disaster, the degree of integration of DRR activities mainstreamed in
those projects, percentage of new development proposals proposing DRR integration
measures, and documented learnings and past disaster experiences in the area selected
for resilience measure.
4. Functional level of the disaster committee/members (S34): This surrogate was
highlighted in two of the case studies #3 and #4. The existence of a disaster
management committee provides an importance assistance in enhancing community
competency and disaster resilience. The members in a disaster management committee
most often include key state officials and community leaders who can guide the
community towards effective disaster management activities. The actions taken by the
disaster management committee after a disaster based on learnings from the past
disaster experience could be a good measure of the competency of the community to
manage future disasters.
The surrogate (S34) measurement protocol can be undertaken by identifying if
there is a committee exists to manage disaster work, by measuring the records of the
activities implemented by the committee before and after a recent disaster, and the
measure of changes (improvements) in the committee itself after the occurrence of a
recent disaster based on the key lessons from its functions.
5. Disaster Risk Reduction & disaster preparedness strategy (S35): This surrogate
was highlighted only in case study #2. Disaster Risk Reduction and Disaster
Preparedness (DRR and DP) is the key for implementing resilience building activities
at the community level. DRR and DP strategy at the community and sub-national
levels need to be formulated based on the key learnings from the past disaster
experience. Central and local government play an important role in initiating and
implementing DRR and DP activities at the policy level and they have to ensure that
the policies are implemented that bring benefits to the communities at risk by reducing
Chapter 5: Interview analysis-Identification of potential surrogates 166
the disaster risks. The changes in policy and projects of the government DRR/DP work
will indicate the incorporation of past learnings in the current or future project and
policy initiatives.
Further, the measurement of this surrogate (S35) should include the assessment
of the disaster risk map availability, measure of DRR and DP projects implemented,
measure of the budget spent on DRR and DP projects before and after a recent disaster,
and measure of new constructions that take into account DRR integration such as
elevating foundations/constructing high rise buildings in disaster prone areas.
6. Evacuation drills & disaster preparedness kits (S36): The participation in
evacuation drills and in possession of disaster preparedness kits was highlighted as one
potential surrogate to measure learnings from past disaster experiences in case studies
#1 and #4. The evacuation follows the early warning, when the disaster risk is
imminent. The evacuation drills as part of the disaster preparedness strategy help to
train people for effective evacuation in real time. The participation of people in
evacuation drill shows the interest of people in disaster preparedness activities. People
are trained to carry disaster preparedness kits during the evacuation that will give them
a practice to do it in a real disaster situation.
The surrogate (S36) can be measured by the number of evacuation drills
conducted before and after a disaster, number of people at risk who participated in the
drills before and after disaster, number of people who carried a disaster evacuation kit
among the people evacuated, the degree of participation of community based
organisations in disaster evacuation drills, and the availability of disaster
simulation/showcase in the area selected for resilience measure.
Chapter 5: Interview analysis-Identification of potential surrogates 167
5.3.6 Summary of findings for indicator #3
The study initially identified 84 concepts and 32 themes from four case studies.
Similar themes were then aggregated and six higher-order themes were identified
through cross-case synthesis which can be considered as potential surrogates to
measure social competence. The summary of the synthesis is shown in Figure 5.16.
The following three surrogates – S31: Reaction to disaster early warning, S32:
Awareness and disaster knowledge level, and S33: New DRR programs such as
innovative construction methods have higher validity, since they were identified in at
least three of the four case studies.
Another set of relevant higher-order themes (S34: Functional level of the disaster
committee/members, S35: Disaster Risk Reduction (DRR) & Disaster Preparedness
(DP) strategy, and S36: Evacuation drills & disaster preparedness kits) were found in
at least one of the case studies, can also be potential surrogates to measure learnings
from the past disaster experience. Hence, six potential surrogates to measure learnings
from the past disaster experience are highly reliable and practically applicable in
similar contexts, since they were identified in consultation with practitioners and
policy makers who are highly experienced in implementing disaster management
activities at community level.
Figure 5.16. Summary of synthesis for third social resilience indicator –
social competence
Chapter 5: Interview analysis-Identification of potential surrogates 168
SURROGATE MEASURES TO ASSESS INVOLVEMENT OF PEOPLE
WITH SPECIFIC NEEDS AS SOCIAL EQUITY IN A DISASTER
CONTEXT (INDICATOR #4)
The surrogate development framework was operationalised to identify potential
surrogates for assessing the fourth social resilience indicator selected in this study –
involvement of people with specific needs as social equity in a disaster context. The
involvement of people with specific needs who are most vulnerable and often
marginalised refers to the level of proactive engagement and provision of equitable
opportunities in increasing their resilience to disasters (Stough & Kang, 2015).
5.4.1 Higher-order themes for case study #1 - Kalmunai T division (KMT)
In case study #1, 10 themes were generated and four combined themes (higher-order
themes) were identified (Figure 5.17) based on connected concept nodes in
Leximancer concept maps. These include:
1. Disaster facilities with access priority to PwSN;
2. Available organisations and projects for PwSN;
3. Social safety programs/funds for PwSN;
4. Availability of committees and support services.
(1) Disaster facilities with access priority to PwSN: Most of the interview
participants highlighted that the key facility that require PwSN friendly access is the
evacuation centre. However, when there is lack of access to PwSN in normal situations,
interviewees raised concerns to raise interest among state and other responsible
stakeholders for investing in giving priority for PwSN to access facilities. Further, it
was highlighted that the key facilities such as the evacuation centres need to be
identified and assessed for measuring equity for PwSN.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.17): a)
PwSN access facilities to evacuation centres and other disaster related facilities such
as community centres; b) priority services available for people with specific needs; and
c) government policy initiatives to make the disaster facilities such as schools, access
friendly for PwSN.
Chapter 5: Interview analysis-Identification of potential surrogates 169
“If there is a two story building, there is no provision for a disable person
to access that building. So there is no access and there is no thinking about
them in our society. There is no follow up monitoring and capacity building
efforts and support is not widely available” (Interview #4)
We also do some facilities such as for the person to access through wheel
chair in his house. If he uses toilet, then he or she can go to toilet and access
facilities without the support of others. We assess the needs of these people
and we do facilities such as hand rails to access toilets. We did not complete
it 100% but we do it satisfactorily” (Interview #28)
(2) Available organisations and projects for PwSN: In a community, there are many
Non-Government Organisations (NGOs) and other social service voluntary
Figure 5.17. Leximancer concept/theme maps from interview data
of case study #1
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4
1
2
Chapter 5: Interview analysis-Identification of potential surrogates 170
organisations that implement community based projects. It was highlighted that there
are a number of projects implemented specific to PwSN in the target area.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.17): a)
availability and effective functioning of PwSN organisations; b) disaster related
projects implemented specific to PwSN by the government and non-government
organisations; and c) funding allocation from organisations for PwSN projects.
“There are some organisations but not in our area helping to PwSN. But, they
only help during disasters such as World Vision, Red Cross, EHED, and SERVO.
They do not function now and they are not here. It is only the government that
supports PwSN now” (Interview #35)
“When there is a disaster, we can check the list of relief projects or work. If they
are included properly then we can at least assure that they are given equal
opportunity. Samurdi is another mechanism for poverty alleviation program.
Government has reduced the number of Samurdi beneficiary list. Government
do not check their ability to earn enough income and awareness and education
to spend their earnings for the expenditure. This is available in circular and they
are implementing. But the problem is in monitoring” (Interview #4)
(3) Social safety programs/funds for PwSN: The availability of social safety
programs and funds/resources for people with specific needs is an important indicator
to measure the inclusion/equity for people with specific needs.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.17): a)
Government programs available for social safety funds targeting PwSN; b)
Government allocation for PwSN projects (including disaster related work); and c)
Non-governmental/charity/private sector initiatives or contributions for social safety
net programs for PwSN.
“There is a special project. There are many payments and schemes in the social
service department. There is a society in Kalmunai North and Kalmunai South.
There is a disable society and we give revolving fund without interest. There are
63 people with specific needs” (Interview #39)
(4) Availability of committees and support services: The involvement and equity
for PwSN can be enhanced when specific committees and support systems are
available to address the needs of PwSN in the state and community structure.
Chapter 5: Interview analysis-Identification of potential surrogates 171
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.17): a)
the level of representation of PwSN in disaster related committees; b) stand-alone
committees for PwSN or organisations formed by PwSN; and c) available support
services such as disability aids and building accessibility.
“Generally, the treatment for PwSN in normal routine life are subjected to
special consideration in all activities and projects. They are also given special
focus during disaster time. Data is available about PwSN such as elders,
disables, and the type of problems they have. When they are accommodated
in public places during evacuation, elders, disable, children, and women are
given support. There is an assessment of what type of assistance they require,
when they are accommodated in public places” (Interview #27)
5.4.2 Higher-order themes for case study #2 – Sainthamaruthu division (SM)
In case study #2, nine distinct themes were generated from case study #2. By
combining closely related themes, four higher-order themes were identified (Figure
5.18). These include:
1. Social safety programs for people with specific needs;
2. Participation of persons with specific needs in training programs;
3. Availability of support services with access to people with disability;
4. Available committees and organisations for PwSN/representation of PwSN in
organisations or committees.
(1) Social safety programs for people with specific needs: Social safety programs
for elderly/persons with disability, plans and programs by the social service
department and availability of society or committee for persons with specific needs
are key considerations in the assistance to PwSN.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.18):
a) Government monthly/regular funding mechanisms for People with Specific Needs
(PwSN) under social safety net program; b) availability of disaster related specific
Chapter 5: Interview analysis-Identification of potential surrogates 172
support to PwSN such as insurance scheme; and c) degree of external assistance to
PwSN.
“For elders beyond 70 years, every individual is given 2,000 rupees per
month. Through the elder’s society, social service department provide
spectacles for those who have eye problems. They are also given monthly
allowance as explained earlier. Their medical expenses and other specific
expenses are mostly covered by the government. For the people who are under
poverty level, they live in shelter. When their houses are damaged, they will
be assisted with food and other relief support” (Interview #40)
(2) Participation of persons with specific needs in training programs: The degree
of awareness and knowledge about disaster preparedness among the persons with
specific needs such as people with disability, elders, people with chronic illness,
children and pregnant mothers is an important measure of resilience. Since PwSN are
Figure 5.18. Leximancer concept/theme maps from interview data of
case study #2
1
4 3
2
Chapter 5: Interview analysis-Identification of potential surrogates 173
highly vulnerable to disasters, they should be treated with special care and thus,
availability of training programs to build their capacity is important.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.18): a)
percentage of attendance by PwSN in disaster related awareness or training programs;
b) degree of participation of PwSN in disaster drills; and c) specific disaster related
trainings or awareness programs for PwSN.
“We provide them some technical training. We have information. They do not
have enough skills to compete with other people in the society. We expect some
qualifications for them to be appointed. There is a percentage of allocation of
recruitment in general recruitment procedure. There are many differently able
people who are very well skilled. They can be capacitated to develop their skills
to get jobs” (Interview #12)
“When they come to get these services in the DS office, many awareness
programs and information are passed to people over 70 years of age. When
there is known disaster before it happens, we can gather these people with
specific needs and educate them about impending disasters” (Interview #31)
(3) Availability of support services with access to people with disability: When
the accessibility of people with disability or elders are concerned, most often the first
thing the interview participants highlighted is the need for accessibility to buildings.
This may include ramps or lift services in buildings, so that people who come in wheel
chairs can easily access the services they wish to obtain.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.18): a)
availability of access facilities such as ramp, lift and hand rails in buildings; b)
provision of accessible aids for the people with specific needs; and c) support services
available for people with specific needs.
“There are grants and funding for constructing toilet facilities in their houses
and they are given supportive aids such as walking sticks and wheel chairs.
People with specific needs are also supported with grants to build houses.
There are projects under social service department such as 250,000 rupees
grant for PwSN” (Interview #40)
(4) Available committees and organisations for PwSN/representation of PwSN
in organisations or committees: The availability and effective functioning of a
Chapter 5: Interview analysis-Identification of potential surrogates 174
committee specific to PwSN or a registered organisation run by PwSN such as
“Differently-able Persons Organisation” (DPO) can enhance the resilience of PwSN
to disasters.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.18): a)
the degree of priority given to PwSN in regular government programs; b) availability
of evacuation centres with support structure for PwSN; and c) Government policy
initiatives such as circulars or regulations for equity access for PwSN.
“Elders are living with children. There are elders’ society for each GN division.
In our division, there is a registered disable organisation. We can ask from these
societies whether they have been provided needed support during the past
disasters or to prepare for future disasters” (Interview #40)
5.4.3 Higher-order themes for case study #3 – Kalmunai M division (KMM)
In case study #3, seven themes were generated and four combined themes were
identified (Figure 5.19). These include:
1. Social safety programs for the most vulnerable people (Elders/Women Headed
Households);
2. Organisational and government support for PwSN;
3. Registered groups/committees for PwSN;
4. Planning and resources for PwSN.
(1) Social safety programs for the most vulnerable people (Elders/Women
Headed Households): Most of the social safety programs focus on two key segments
of people with specific needs such as elders and women headed households (widows).
Elders and widows can be physically highly vulnerable to disasters and require
immediate and special care. Government implements social safety net programs such
as monthly payment to elders over 70 years age and similar allowance for women
headed households who are under the poverty line.
Chapter 5: Interview analysis-Identification of potential surrogates 175
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.19): a)
representation of women in local organisations; b) care for elders (social safety
programs by state); and c) social safety financing for widows.
“Every month, elders above 60 years of old, get 2,000 rupees, people with
disability get 3,000 rupees by Social Service Department. In addition to
Public Monthly Allowance (PMA), social safety allowance (called
‘Samurdhi’) is also given to women headed households/widows and for the
families under poverty line. During disaster times also, the same funding is
given” (Interview #29)
(2) Organisational and government support for PwSN: The availability of
organisational (non-state) and government projects and support targeting PwSN can
ensure equity of resource allocation for PwSN, particularly for people with disability.
This includes programs or projects and resource support through specific interventions
related to disasters.
Figure 5.19. Leximancer concept/theme maps from interview data of
case study #3
4
1
2
3
Chapter 5: Interview analysis-Identification of potential surrogates 176
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.19): a)
Organisational services available to PwSN; b) support from government for PwSN;
and c) disaster specific services and support for PwSN.
“There are many access facilities for the people. When disaster response work
was done by some organisations, they collected information about people with
specific needs. They have designed and implemented specific programs for
these people” (Interview #32)
When there is a problem we temporary toilets for them with the help of MOH
and Municipal Council through respective organisations and NGOs and also
philanthropists. Government provides social service support. Government for
person 150/- per person item. Special allocations are done through NGOs.
Additionally not much done.” (Interview #30)
(3) Registered groups/committees for PwSN: The availability of registered groups
or committees that are set up for PwSN can enhance the support systems for PwSN in
a disaster context. However, the active functioning or participation of such groups or
committees in disaster risk reduction programs need to be considered, when measuring
the involvement of PwSN for enhancing disaster resilience.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.19): a)
available forums or committees for PwSN (specific to DRR); b) meetings organised
by the registered groups or committees in DRR; and c) projects/awareness programs
implemented.
“There is a group working with people with disabilities called ‘Human Link’.
This disability group is registered in government. They talk about disable people
rights and problems” (Interview #24)
“If a person with disability needs to attend a meeting, is the meeting place has
access to them. Are the people with specific needs organised in an organisation
or committee. Do they have a specific organisation formed for them? We can
see the structure? If people with specific needs to come to meeting,” (Interview
#25)
(4) Planning and resources for PwSN: Disaster Risk Reduction (DRR) plans in each
government administrative division need to consider the needs and vulnerabilities of
PwSN. The plan is an initial indicator, but also the resource allocations for effective
Chapter 5: Interview analysis-Identification of potential surrogates 177
implementation of the plan can be considered as another measure to assess the equity
for PwSN in DRR programs.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.19): a)
availability of DRR plans targeting PwSN; b) resource allocation in general projects
for PwSN; and c) resource allocation and financing for PwSN for DRR projects.
“In the contingency plan, we have identified people who are more vulnerable to
disasters such as flood. There are around 1,500 people in such situations. Equal
access to resources is a problem. Because, we do not have enough resources.
Sometimes, it can be in Municipal Council. We can’t take decision alone. We
invite all stakeholders including community based organisations to a meeting.
When we do a project, we invite all important people for preparing the
contingency plan. When we do these meetings, we will take decisions with key
people in the community” (Interview #24)
5.4.4 Higher-order themes for case study #4 – Sub-national level
In case study #4, ten themes were generated and four combined higher-order themes
were identified (Figure 5.20). These include:
1. Accessibility in evacuation buildings;
2. Early warning information for PwSN;
3. Priority criteria for people with specific needs in projects;
4. Government/NGO support services for PwSN.
(1) Accessibility in evacuation buildings: Evacuation is the key disaster response
component and timely evacuation of people can save many lives. However, evacuation
of people with specific needs is challenging which requires specific resources. For
example, people with disability requires additional physical and human resource
support to evacuate during disasters. Similarly, when they are evacuated to a pre-
identified evacuation building demarcated by the disaster management committee,
they should be with all accessible facilities for PwSN.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.20):
ratio of evacuation building with accessibility for PwSN and without accessibility; b)
Chapter 5: Interview analysis-Identification of potential surrogates 178
regulations for construction of disabled/elders friendly buildings; and c) approval
mechanisms for construction of buildings with accessibility.
“The general circulars and rules will be same for local authority similar to
government systems. When new buildings are constructed, the access and lift
need to be ensured in the buildings. It is followed by the local authorities. We, at
the local authority will only approve the buildings that have the access for
persons with specific needs” (Interview #36)
(2) Early warning information for PwSN: Early warning is the key for effective
evacuation that will help people, particularly PwSN to prepare for timely evacuation.
Hence, the availability of multiple early warning messages that can cater to the needs
of different people such as people with disability (blind and deaf). A specialised early
Figure 5.20. Leximancer concept/theme maps from interview data of
case study #4
1
3
2
4
Chapter 5: Interview analysis-Identification of potential surrogates 179
warning messages and ability to communicate with people with specific needs can
measure the involvement/equity of PwSN in disaster context.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.20): a)
availability of diverse early warning information dissemination methods for PwSN; b)
availability of awareness programs for PwSN of specific early warning systems; and
c) availability of access to information systems for PwSN.
“If people have multiple methods available to access early warning information,
it is an important measure. Certain Disable People Organisations (DPOs) are
well functioning. Active participation of them can be a good indicator. Early
warning should also include signs that can be understood. If there is a school
with special needs children, early warning messages need to target these students
through specific early warning signs that can be understood by them”. (Interview
#10)
(3) Priority criteria in projects for people with specific needs: The availability of a
set of criteria to prioritise the assistance for PwSN in the state and non-state funded
projects and services can be a measure of involvement and equity for PwSN in a
disaster context. The priority criteria is informed or decided through a circular issued
by the social services department at the national level to the sub-national offices, which
implements the projects for PwSN. There are also methods of assessing the needs of
the population based on a set of criteria and a scoring system. The specific questions
in the assessment forms provide priority and higher scores for persons with specific
needs.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.20): a)
number of projects implemented with the criteria for PwSN and without the criteria;
b) availability of official protocol for PwSN inclusion (Circulars); and c) number of
PwSN targeted projects.
“In my project there is a criteria. In the scoring system, the first and priority
criteria are these people – PwSN. The executive committee of community based
organisations also prioritise these people. The existence of criteria to prioritise
the needs of PwSN shows that the concerns of PwSN are prioritised” (Interview
#13)
Chapter 5: Interview analysis-Identification of potential surrogates 180
(4) Government/NGO support services for PwSN: The key government support for
PwSN is the social safety net programs. It is regularly implemented by the respective
government ministries such as social service ministry that provide monthly and annual
assistance to elderly, persons with disability, women headed households, and for
people live under the poverty line.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.20): a)
resource allocation for PwSN from the government budget; b) NGOs or CBOs
available for PwSN; and c) number of government services available targeting PwSN.
“In each divisional office, there is a Social Service Officer (SSO). He has details
of people with specific needs who were supported with wheel chairs, livelihood
support and also how many organisations are working with them. There is a
regular allocation from the government, however, the government has imposed
many criteria to provide livelihood support and houses for PwSN” (Interview
#18)
5.4.5 Final surrogates identified through cross-case synthesis for indicator #4
Table 5.4 below summarises the mapping of higher-order themes (taken as
surrogates) which emerged from the thematic analysis of interview data from the four
case studies.
Table 5.4. Surrogates (higher-order themes) mapping for indicator#4
Case study
locations/area
Surrogates to measure involvement of persons with
specific needs in disaster management
S41 S42 S43 S44 S45 S46
Case study #1
(KMT) X X X X
Case study #2 (SM) X X X X
Case study #3
(KMM) X X X X
Case study #4 (sub-
national level) X X X X
S41: Social safety programs for PwSN
S42: PwSN Committees/groups or representation of PwSN in committees
S43: Organisations/projects for PwSN
S44: Participation of PwSN in training programs
S45: Disaster facilities with access/priority to PwSN
Chapter 5: Interview analysis-Identification of potential surrogates 181
S46: Planning and resources for PwSN (Organisational/government support)
For each of the potential surrogates, a brief description of the surrogate, its relationship
with the target indicator and assessment protocols from the synthesis of interview
responses are summarised below.
1. Social safety programs for Persons with Specific Needs (S41): This surrogate was
highlighted in all four case studies. Social safety programs are the key programs
available for PwSN to ensure their inclusiveness in a community. Through social
safety programs by the state, it ensures the rights of the PwSN and provide equal access
to resources to avoid discrimination for those people who need special care. In the
context of this research, some programs highlighted during the interviews include
monthly payments for elderly over 60 years age, women headed households, and
persons with disability. Social security funds established to support marginalised
families and families living under the poverty line is key to ensure equity for PwSN.
The measurement of this surrogate (S41) should include the measure of people
with specific needs in the division, the percentage of people with specific needs such
as elderly, women headed households, and disabled in disaster situations included in
social safety assistance programs, the trend in social safety program subscribers, and
identifying the disaster preparedness related needs that can be addressed through social
safety programs.
2. PwSN Committees/groups or representation of PwSN in committees (S42): This
surrogate was highlighted in three case studies (case studies #1, #2, and #3). The
involvement and equality for PwSN can be measured using the inclusion of PwSN in
committees in their own community. The level of representation of PwSN in general
committees working in the community shows that their voice is heard, they are
provided with equal opportunity and there is minimal discrimination. In some places,
separate groups are also formed specific to PwSN to ensure their collective ideas are
gathered in assessment planning, and implementation of projects.
The surrogate (S42) measurement protocol can include the measure of specific
committees available for PwSN to the PwSN population, the number of general
committees in which PwSN has adequate representation, and percentage of PwSN in
decision making positions in the divisional area.
Chapter 5: Interview analysis-Identification of potential surrogates 182
3. Organisations/projects for PwSN (S43): This surrogate was highlighted in all four
case studies. The availability of projects targeting PwSN to ensure their needs are
properly catered is a key factor in measuring the equity for PwSN. The number of
projects specifically designed for PwSN by the government and NGOs can indicate
the level of consideration given to PwSN in a specific community. In addition to the
projects, there are also organisations formed for PwSN that represent the voice of
PwSN. The number of projects implemented by PwSN organisations and by the
government or non-governmental organisations is also a good measure of the
involvement of PwSN in a community.
The surrogate (S43) can be measured by the number of projects implemented
targeting PwSN alone, the number of organisations formed specific to PwSN, and the
percentage of people targeted under the projects to the total PwSN population.
4. Participation of persons with specific needs in training programs (S44): This
surrogate was highlighted only in case study #2. The involvement of PwSN in training
programs to build their capacity is a measure of ensuring equity for people with
specific needs in a disaster situation. Some training and awareness programs to raise
their awareness on disaster risk reduction such as early warning, evacuation and
recovery can help to enhance their knowledge to effectively undertake disaster risk
management. Awareness programs or disaster drills are widely conducted regularly to
prepare people for emerging disasters. However, knowing that the most vulnerable
segment of the population in any disaster context are people with specific needs, it is
important to highlight the availability of training programs specific to PwSN and their
participation in training/awareness programs.
The surrogate (S44) can be measured by the number of training/awareness
programs organised that target or include PwSN, percentage of participation of PwSN
in the general training/awareness programs to the total PwSN population, and the
frequency of the training/awareness/disaster drill programs conducted for PwSN.
5. Disaster facilities with access/priority to Persons with Specific Needs (S45): This
surrogate was selected as the fifth surrogate from case studies #1 and #4. In a disaster
context, one of the key factors for PwSN is the accessibility of infrastructure facilities
by PwSN. The availability of access to critical infrastructure such as hospital buildings
Chapter 5: Interview analysis-Identification of potential surrogates 183
that need to be frequently accessed by people with specific needs is important to
measure equity for people with specific needs. In a disaster context, the accessibility
of evacuation centres for people with disability has been a concern. The availability of
latrines for men and women separately, for people with disability, and elder-friendly
access are some example of such disaster facilities to provide priority to PwSN.
The surrogate (S45) can be measured by the accessibility audit of critical
infrastructure such as hospitals and community buildings, accessibility audit for
evacuation centres including facilities for PwSN, and the availability of disability aids
for people with disability.
6. Planning and resources for PwSN (Organisational/government support) (S46):
This surrogate was highlighted as a key facet of the indicator – ‘involvement of persons
with specific needs in disaster management’ in case studies #3 and #4. The availability
of a plan and resources based on the plan from the government and NGOs can be a
surrogate to measure involvement/equity for PwSN. The social services departments
in each divisional area prepare an annual plan for supporting PwSN and allocate
resources accordingly to ensure the needs of PwSN are met. Social safety programs
are devised to assist the population with specific needs in order to reduce inequality.
However, they require additional resource allocation to fulfil their basic needs to live
with dignity.
The surrogate (S46) can be measured by the percentage of financial allocation per
annum from the total budget to PwSN of the division, the support from the NGOs
(percentage of contribution by NGOs to PwSN), and the allocation of resources for
PwSN at the divisional level (For example the budget and expenditure of the PwSN
organisations).
Chapter 5: Interview analysis-Identification of potential surrogates 184
5.4.6 Summary of findings for indicator #4
The study initially identified 81 concepts and 35 themes from the four case
studies for indicator #4. Similar themes were then aggregated and six higher-order
themes were identified through cross-case synthesis which can be considered as
potential surrogates to measure involvement of persons with specific needs in disaster
management. The summary of the synthesis for the fourth social resilience indicator –
involvement of PwSN as social equity is shown in Figure 5.21 below.
The following three surrogate – S41: Social safety programs for Persons with
Specific Needs, S42: PwSN committees/groups or representation of PwSN in
committees, and S43: Organisations/projects for Persons with Specific Needs, have
high validity, since they were identified in three of the four case studies.
Another set of relevant higher-order themes (S44: Participation of persons with
specific needs in training programs; S45: Disaster facilities with access/priority to
Persons with Specific Needs; and S46: Planning and resources for PwSN
(Organisational/government support)) were found in at least one of the case studies,
can also be potential surrogates to measure the equity/involvement of persons with
specific needs in a disaster context. Hence, six potential surrogates to measure the
involvement of persons with specific needs in disaster management are highly reliable
and practically applicable in similar contexts elsewhere, since they were identified in
consultation with practitioners and policy makers who are highly experienced in
implementing disaster management activities at the community level.
Figure 5.21. Summary of synthesis for the fourth social resilience indicator
– social equity
Chapter 5: Interview analysis-Identification of potential surrogates 185
SURROGATE MEASURES TO ASSESS CULTURAL/BEHAVIOURAL
NORMS AS SOCIAL BELIEFS IN A DISASTER CONTEXT
(INDICATOR #5)
The surrogate development framework was operationalised to identify potential
surrogates for measuring the fifth social resilience indicator selected in this study –
cultural and behavioural norms in disasters as social beliefs. The cultural and
behavioural norms in a disaster context refers to the influences of beliefs in the
interpretation of disaster risks (Eiser et al., 2012).
5.5.1 Higher-order themes for case study #1 - Kalmunai T division (KMT)
In case study #1, eight themes were generated and four combined themes (higher-order
themes) were identified (Figure 5.22) based on connected concept nodes in the
Leximancer concept maps. These include:
1. Involvement of religious institutions in disaster relief and response
activities;
2. Religious places as evacuation centres with facilities;
3. Government disaster management plan integrating religious institutions/
faith-based organisations;
4. Role of faith-based organisations/leaders in social trust.
(1) Involvement of religious institutions in disaster relief and response activities:
Not all religious institutions are active in disaster relief and response activities.
However, in strong faith based communities, religious institution is one of the key
decision makers. It is very prominent in disaster situations that religious organisations
themselves extend support, not only to their own population, but to the neighbouring
population or sometimes people affected by disasters in other regions as well.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.22): a)
past records of disaster relief activities of religious institutions, b) availability of
Disaster Management (DM) volunteer force/network in religious institutions, and c)
availability of DM plans/DM committees by the religious institutions/faith-based
organisations.
“When there is a disaster, no ethnic or religious bias. When there is a
disaster people from different ethnicities and religious backgrounds come to
help people. The damaged houses were repaired by the international
Chapter 5: Interview analysis-Identification of potential surrogates 186
organisations although they are Christians. During disaster time, there is no
division between ethnicity and religious backgrounds. There are religious
institutions providing relief items. For disaster relief, other ethnic people
send relief items to us. When disasters come, people come together to help
other community” (Interview #41)
(2) Religious places as evacuation centres with facilities: As religious institutions
play a key role, in many occasions people tend to seek safety in religious places when
they evacuate. People tend to take shelter in religious places. However, the facilities
available in religious places to accommodate people including the most vulnerable
population such as the people with specific needs is the key measure of social
resilience. Since some religious places may not be suitable for accommodating people
because they may lack basic facilities that could lead to more harm than good. Hence,
the measure of availability of religious places as evacuation centres with basic facilities
(Mosques, Temples, and Churches) can be a surrogate for existent religious/cultural
practices in relation to disaster management.
3
2
1
4
Figure 5.22. Leximancer concept/theme maps from interview data of
case study #1
Chapter 5: Interview analysis-Identification of potential surrogates 187
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.22): a)
percentage of religious places that have facilities for evacuation centres; b) percentage
of population that is regularly attached to religious places for their religious/social
activities; and c) percentage of people accommodated in all demarcated religious places
as evacuation centres.
“Religious places are also used as an evacuation places and people move
immediately to accommodate to these religious centres for first
accommodation and to safe guard themselves. There are Participatory Rural
Appraisal tools to understand these information. There are many tools that
could help us to understand what type of role the religious institutions can
play” (Interview #04)
(3) Government disaster management plan integrating religious institutions/
faith-based organisations: In strong faith-based communities, the religious
institutions and faith-based organisations play a key role in decision making on
community issues such as in disaster situations. In these communities, the role of
religious institutions and faith-based organisations/networks cannot be ruled out
when disaster management plans are developed by the local authorities. Hence, the
measure of role played by religious institutions and faith-based organisations is an
important factor in determining social resilience to disasters under the dimension of
social/cultural belief systems.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.22): a)
participation of faith-based organisations/religious institutions in disaster
management committee (members); b) involvement of religious institutions/faith-
based organisations in disaster management planning process; and c) participation of
faith-based organisations/religious institutions in disaster management activities by
government.
“When there is heavy rain or flood or even during droughts, there are social
and religious events organised. There are some special religious sermons
and prayers when there is a drought. People come together and it is a time
that people show a social cohesion and it is an opportunity for people to
gather for a common cause. When there is a disaster, people link it to
religious believes. For droughts, people link it to religious reasons.
Government also organise religious events to bring community together and
Chapter 5: Interview analysis-Identification of potential surrogates 188
we can see how many people participate in those prayers and religious
functions. It shows their strength of the religious beliefs in disaster related
understanding and knowledge” (Interview #27)
(4) Role of faith-based organisations/leaders in social trust: This case study
emphasised on the trust on the faith-based organisation and religious
institutions/leaders. For example, the trust on early warning messages disseminated
from the religious institutions and leaders are more likely to be believed by the
community than from other sources when the community has stronger faith
orientations.
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.22): a)
available faith-based organisations in the area; b) degree of social trust on faith-based
organisations (Degree of participation of people in religious events); and c)
participation of faith-based leaders in community issues.
“When there is a disaster early warning, temples and mosques and other
cultural centres are the first to disseminate information. Even in the night at
10 or 11 o’clock, the head of the temple informs to the public that they need
to be vigilant about an impending disaster. People believe these messages,
because it is coming from religious places. When a disaster information is
given by a normal person, people have more believe that the religious leaders
and spiritual leaders will not tell anything without confirmation. So there is a
stronger believe that people trust religious leaders and messages come from
religious institutions” (Interview #28)
5.5.2 Higher-order themes for case study #2 – Sainthamaruthu division (SM)
In case study #2, nine distinct themes were generated. By combining closely related
themes, three higher-order themes were identified (Figure 5.23). These include:
1. Faith-based organisations/activities;
2. Early warning information/support by religious institutions;
3. Culture of women in the society.
Chapter 5: Interview analysis-Identification of potential surrogates 189
(1) Faith-based organisations/activities: Faith-based organisations and their
activities have played an important role in disaster management work before and after
disasters. The motto of helping people becomes the centre of their activities. Hence,
faith based organisations comes under cultural division of the government
administration in the case study area.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.23): a)
ratio of faith based organisations to other community based organisations; b) level of
engagement of faith based organisations; and c) the work of community based
organisations in faith.
“Religious organisations will never do harm as they always try to help people.
For people, they show more interest in the religion. When there was war in this
country, people take self-defence in mosques for two reasons: one, people have
Figure 5.23. Leximancer concept/theme maps from interview data of
case study #2
1
3
2
Chapter 5: Interview analysis-Identification of potential surrogates 190
more faith in their religion and second, when people stay in religious places, it
is very safe. So people seek shelter in religious places like mosques”. (Interview
#20)
(2) Early warning information/support by religious institutions: One of the nine
themes generated from this case study interview data analysis is ‘information’ that
indicate early warning and information. The other connected key concepts to
information/early warning is mosques (i.e. religious institutions) and their support in
disseminating information and early warning related to disaster risks.
Four key concepts identified in this theme are (as shown in box 2 in Figure 5.23): a)
role of religious institutions in Disaster Risk Reduction (DRR) for early warning and
information dissemination; b) support of religious leaders/active participation in DRR
work; c) facilities available in religious places as evacuation centres for the use during
evacuation; and d) early warning facilities available in religious places such as
mosques.
“The only information sharing method available now is to use siren. This society
is centred and linked to religious institutions and mosques. In our area, the
network and proximity of religious places available is a positive aspect, since it
is widely available and can be used for transmitting information very easily”
(Interview #31)
When during Tsunami early warning is issued asking people to move away from
the sea, people will go to temple even the Temple is in the coastal area that is
risky to Tsunami. We have pointed out in the evacuation map that people should
evacuate in the direction out of coastal area that is away from the Temple. We
have not shown the Temple as an evacuation centre, and we have indicated
school or community centre as an evacuation centre. But still people do go to
Temple in the wrong evacuation direction” (Interview #13)
(3) Culture of women in the society: Many interview participants in this case study
highlighted the cultural barriers exist for women to actively participate in disaster
related activities such as in evacuation drills and first aid training. The existent
cultural practice of women not participating in public forums and programs pose an
enormous challenge to prepare them for disaster risk and response activities.
Chapter 5: Interview analysis-Identification of potential surrogates 191
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.23): a)
women participation in disaster related training such as first aid; b) gender sensitive
disaster programs; and c) gender related restrictions and social norms.
“Sometimes religious and cultural beliefs can give greater impact. There are
some religious restrictions such as men and women do not mingle together.
For young girls, we need to find separate accommodation during disasters.
Generally women are separated and they will be hosted in a separate
evacuation centre. When we keep all men and women together, there are some
debates. People give more priority for religious beliefs and practice over than
any other issues” (Interview #12)
5.5.3 Higher-order themes for case study #3 – Kalmunai M division (KMM)
In case study #3, six themes were generated and three combined themes identified
(Figure 5.24). These include:
1. Cultural role of women in the society;
2. Awareness raising through faith-based activities;
3. Faith-oriented practices during disasters.
Figure 5.24. Leximancer concept/theme maps from interview
data of case study #3
1
2
3
Chapter 5: Interview analysis-Identification of potential surrogates 192
(1) Cultural role of women in the society: The culture of women has been a dominant
factor in existent cultural/religious practices that impede disaster preparedness of the
community. Since case study #2 and #3 are Muslim dominated society (100% Muslim
urban areas), these two areas have similar themes.
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.24): a)
degree of social activities of women that are considered to be acceptable among the
strong faith-based society; b) degree of religious norms followed with regard to
women’s dress; and c) degree of women participation in trainings such as first aid and
evacuation.
“In some societies, there are regulations or norms for women. Even in
emergencies, Muslim women do not go out without another person. We
experienced similar problems during previous disasters. More women such
as widows or women headed households lost their lives. My opinion is that
in the Muslim culture, if a women can dress properly within the religious
norms, she can go out to earn her living and search for livelihood. Access to
information is the key lacking part for women. They do not know what
happens during disasters” (Interview #42)
(2) Awareness raising through faith-based activities: The faith-based engagement
of the society has many positive factors in enhancing resilience. The strong faith-based
engagement is capitalised and can be used as an opportunity to raise awareness about
disaster impacts. Regular engagement in religious activities in public platforms are
good opportunities to raise awareness on disaster related messaging to the public,
which can have wider reach and internalised effectively by the community due to their
strong religious beliefs.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.24): a)
awareness programs held in religious institutions such as sermons; b) awareness
programs and capacity building trainings for religious leaders on disaster management;
and c) available faith-based mechanisms/engagement strategies by the disaster
management committee promoting disaster resilience.
“People mostly believe that the disasters and their damage are god’s will
and people do not most often show interest to prepare for disasters. Mosques
provide awareness programs. During Friday sermons, the religious leaders
Chapter 5: Interview analysis-Identification of potential surrogates 193
and priests make people aware and give more knowledge to people about
disasters and preparedness activities” (Interview #29)
(3) Faith-oriented practices during disasters: Some communities which are rooted
in religious beliefs and strongly believe in their traditional religious practices, observe
some faith-based practices before, during, and after disasters. For example, in the
Muslim society, there has been a religious belief and practice of large gatherings for
prayers during drought seasons asking for rain from God. Similarly during flooding or
excessive rain or any other disaster, to plead with God through special prayers to
safeguard the community from danger. Similar practices are also practised in other
religions as well, such as in Hindu and Buddhism where there are special prayers and
alms giving ceremonies being in Temples.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.24): a)
available religious practices in different stages of a disaster cycle; b) participation of
the public in these religious practices; and c) participation of the population in annual
disaster remembrance days conducted by religious institutions.
“In Tamil culture, seeds are saved underground. When there is a disaster like
cyclone, it is safe under the ground. For example when there is no rain,
Muslims pray and gather asking their god for rain…. A prayer is the key
believe among Muslims, when they face hardships. The coordination between
faith-based organisations is a good indication. There are many factions
among Muslims based on faith beliefs and differences. When there is a
disaster, they coordinate and work. During the normal time, there are many
difference and divisions. Faith based divisions are in normal time reduce the
cohesion before disasters (during the normal times)” (Interview #32)
5.5.4 Higher-order themes for case study #4 – Sub-national level
In case study #4, ten themes were generated and five combined higher-order themes
were identified (Figure 5.25). These include:
1. Available faith based organisations and support;
2. Culture in evacuation of women;
3. Cultural/religious barriers for preparedness;
4. Role of religious institutions in disaster management;
Chapter 5: Interview analysis-Identification of potential surrogates 194
5. Trust in early warning messages.
(1) Available faith based organisations and support: The role of faith based
organisations in disaster management, particularly in disaster response and recovery
have been consistently highlighted by many interview participants during this study.
Sri Lanka, being a multi religious society, with strong religious beliefs rooted in the
community, the role of faith in disasters largely need to be capitalised for positive
outcomes, according to many interview participants. Although there are barriers for
enhancing community resilience to disasters due to some religious beliefs that
negatively impact disaster preparedness and resilience, the close interaction and belief
systems of the population with faith based organisation and leaders play a key role in
educating the public on the importance of disaster resilience.
Figure 5.25. Leximancer concept/theme maps from interview data of
case study #4
1
4
3
5
2
Chapter 5: Interview analysis-Identification of potential surrogates 195
Three key concepts identified in this theme are (as shown in box 1 in Figure 5.25): a)
available faith-based organisations (Number of FBOs registered in the area); b)
projects involved or implemented in disaster management; and c) existence of a
disaster management structure within the organisation.
“There are many religious organisations within each religion. There is a
catholic youth union. These are very small organisations not a big NGO. A
support comes from the religious people and when a priest asks for support
using a loud speaker, they announce in the community, immediately support
comes. Because, when a priest says that they need to support people affected
by disasters, people immediately support. There is no need for confirmation.
When there is a fire in a house announced by a priest, people will not look at
where it happened. They will just support because the Priest or Moulavi asked
this help. Since this belief exists, immediately they collect money and support
when there is a disaster. The message is immediately passed through and there
is no need for confirmation, since their belief is so high” (Interview #13)
(2) Cultural/religious barriers for preparedness: There are many barriers for
disaster preparedness activities in a strong faith based community due to some myths
and misunderstood religious beliefs in relation to disaster preparedness. Although
many interview participants believed that religion can play a big role in advocating for
better disaster preparedness, the lack of understanding about disaster management
scientifically pose a serious barrier among the faith leaders and followers to use
religious practices to prepare for disasters. The culture of disaster preparedness should
be promoted decrying the barriers in religious practices.
Three key concepts identified in this theme are (as shown in box 2 in Figure 5.25): a)
participation of religious leaders in disaster preparedness projects; b) number of
disaster preparedness projects implemented by religious institutions/faith based
organisations; and c) percentage of religious leaders trained in disaster management.
“We can look at cultural practices positively. In some societies we can’t see
‘working together’ culture. In some cultures, there are some barriers in
preparedness. But, for disaster response, it is positive. There is a culture of
post disaster work, but they do not think that this could be better done for
preparedness work. For example, when there was a flood in Colombo, Council
of Muslim priests, a religious coordination body went and supported after flood
Chapter 5: Interview analysis-Identification of potential surrogates 196
in post disaster work. They did not go after flood to check the preparedness
needs of families affected by past disasters to prepare for them for future
disasters. Donors are also emotionally influenced towards disaster response”.
(Interview #10)
(3) Culture in evacuation of women: Gender is another important parameter in
disaster management, particularly in the strong faith based communities. There are
many restrictions imposed on women in the name of following faith and cultural
norms. For example, women are afraid to evacuate alone during emergencies, when a
household is women headed, because of the fear that the community will see these
women in a different perspective. This fear makes women feel insecure and restrict
their mobility in disaster situations.
Three key concepts identified in this theme are (as shown in box 3 in Figure 5.25): a)
participation of women in disaster management related training such as swimming and
first aid; b) percentage of women headed households evacuated in the past disaster
early warning/past death tolls of women and other vulnerable groups; and c) trend in
the rate of crimes against women and Gender Based Violence.
“If we look at individual preparedness, there are restrictions due to cultural
norms and gender related issues for women. Women are more vulnerable, but
it is very difficult to train them for swimming in our culture. For example when
we do trainings for disaster evacuation such as swimming, we can check how
many women enrol in swimming training. This is a good measure. We can
also check in other training such as first aid training, how many women attend
these trainings” (Interview #10)
(4) Role of religious institutions in disaster management: The role of religious
institutions in disaster management has been widely acknowledged as an important
factor in a strong faith-based community. People tend to listen and trust more, religious
leaders than civic leaders. However, there is lack of initiatives by religious institutions
on disaster preparedness due to lack of understanding and knowledge about disaster
management among them. However, with limited understanding and knowledge on
disaster management, religious institutions can easily mobilise volunteers during
disasters due to their extended volunteer network developed on the basis of religious
engagement with youth and adults. They can become the forefront of disaster response
and relief activities such as evacuation, relief collection, and distribution.
Chapter 5: Interview analysis-Identification of potential surrogates 197
Three key concepts identified in this theme are (as shown in box 4 in Figure 5.25): a)
available facilities in religious institutions for disaster preparedness; b) organisation
and participation in disaster management activities and projects; and c) available
disaster related support mechanisms in religious institutions.
“To accommodate people during disasters, mosques are very important. Since
they have two stories building, people go to mosques for evacuation. However,
preparedness was less in these religious institutions. There are information
centres such as Police, Government Administration office, Local Authority
Office. In some places, these institutions have not developed a good network
with CBOs and other organisations, such as religious institutions”.
(Interview #11)
(5) Trust in early warning messages: Early warning is the critical component of any
disaster response. Hence, the preparedness measures for early warning dissemination
to the communities that are most vulnerable to disasters become a key factor. In order
to act timely and properly, the community at risk should trust the early warning
message to take necessary actions according to the warning message disseminated.
However, there seems to be a lack of trust on warning messages among the community
issued by the media or government institutions due to past experience of false
warnings. When it comes to warning dissemination, the trust was built on religious
institutions and leaders for generations.
Three key concepts identified in this theme are (as shown in box 5 in Figure 5.25): a)
percentage of religious institutions as early warning dissemination centres; b) religious
institutions equipped with facilities for early warning; and c) degree of participation
of religious institutions in early warning drills.
“Unless the disaster comes to their step, they don’t believe in it. Even if we are
saying that there is a threat that we are expecting a disaster and there is a
warning, there is a possibility for a disaster tomorrow or day after tomorrow,
people do not listen. People trust religious leaders and trust whatever they say.
Similarly in other areas, priests are given utmost respect. They listen to the
chief priest of the temple. They are also doing lot of work” (Interview #17)
Chapter 5: Interview analysis-Identification of potential surrogates 198
5.5.5 Final surrogates identified through cross-case synthesis for indicator #5
Table 5.5 below summarises the mapping of higher-order themes (taken as
surrogates) which emerged from the thematic analysis of interview data from the four
case studies.
Table 5.5.Surrogates (higher-order themes) mapping for indicator#5
Case study
locations/area
Surrogates to measure cultural and behavioural
norms in disaster management (Emerging
themes)
S51 S52 S53 S54 S55 S56
Case study #1 (KMT) X X X X
Case study #2 (SM) X X X
Case study #3 (KMM) X X X
Case study #4
(sub-national level) X X X X
S51: Faith-based organisations/practices/activities
S52: Culture of women in the society
S53: Involvement of religious institutions in disaster preparedness/response activities
S54: Early warning dissemination trust on religious institutions
S55: Religious places as evacuation centres with facilities
S56: Government disaster management plan integrating religious institutions/ faith-
based organisations
For each of the potential surrogates, a brief description of the surrogate, its
relationship with the target indicator, and assessment protocols from the synthesis of
interview responses are summarised below.
1. Faith-based organisations/practices/activities (S51): The communities with strong
religious beliefs have faith-based organisations. Past evidence shows that faith-based
organisations have played a major role in disaster response and recovery activities.
Although faith-based organisations are not trained professionally to work in disaster
management, their activities such as leading an evacuation work, most importantly in
critical situations cannot be underestimated. However, they lack strategies in disaster
preparedness work and are often influenced by faith based values such as helping each
other in difficult times and place the wellbeing of the community as a priority,
particularly in hardship. This surrogate was highlighted in all four case studies.
Chapter 5: Interview analysis-Identification of potential surrogates 199
The surrogate (S51) measurement protocol can include the measure of faith-based
organisations registered and active in the division, the faith-based organisations which
have disaster management in their portfolio, percentage of faith-based organisations
that have the volunteer base for disaster relief work, and percentage of population
attached to the faith-based organisations in the division.
2. Culture of women in society (S52): In certain cultures and faith based communities,
the restrictions for women in many aspects of social life can be seen. For example, in
Muslim villages, lack of mobility of women alone in public have been a social norm
and people believe that it has many advantages in terms of reduction in harassment
and crimes against women. However, the limitations of women being restricted
culturally, such as the need for the same dress code during an emergency, has
negatively impacted on the ability of rescuing them during disasters. The existing
cultural norms as to how the women are treated in a society is a good indicator of
existent cultural and behavioural norms that can impede or assist in disaster
management activities. This surrogate was highlighted in three case studies except case
study #1.
The surrogate (S52) can be measured by the number of women volunteers trained
in first aid, swimming and other critical disaster management skills, extent of women
volunteer networks/organisations working in disaster management projects, and the
percentage of the women population employed against the women population
employed in critical jobs such as police and emergency health services.
3. Involvement of religious institutions in disaster preparedness, relief and response
activities (S53): This surrogate was highlighted as a key facet of the indicator –‘cultural
and behavioural norms in disaster management’ in case studies #1, #3, and #4. When
there is a stronger trust on religious institutions and faith-based engagement by a
community, preparing religious places as evacuation centres to accommodate people
in times of disasters is not sufficient and effective. The involvement of religious
leaders and faith based organisations proactively in all phases of disaster management
cycle will help productive and effective plans and projects. However, the degree of
belief on such measures and willingness to support preparedness and resilience
building activities can be a good surrogate to measure the existent local cultural and
religious beliefs of a community.
Chapter 5: Interview analysis-Identification of potential surrogates 200
The surrogate (S53) can be measured by the religious leaders trained on disaster
management skills such as search and rescue/other volunteer basic skills such as first
aid, disaster preparedness activities engaged by religious institutions, and the
participation of committee members of the religious institutions in disaster
management committee activities or other government projects.
4. Early warning dissemination trust on religious institutions (S54): The trust on
religious institutions such as Mosques, Temples, and Churches can be indicated by the
issuance of early warning and disseminations. The trust on religious institutions is
higher, when the government systems lack good systems and facilities to educate the
public on early warning. People consider religious leaders as trustworthy and
therefore, local authorities utilise the religious institutions and leaders to disseminate
the disaster early warning and to raise awareness on disaster risk reduction. The trust
is already built with religious institutions in strong faith-based communities through
participation in religious activities. This surrogate was highlighted in two case studies
(case studies #2 and #4).
The surrogate (S54) can be measured by the facilities available for early warning
dissemination by religious institutions, the percentage of population who attend
religious institutions regularly (some minimum attachment), the coverage of early
warning dissemination through religious places, and the ability and available
mechanism or organisational structure for early warning dissemination.
5. Religious places as evacuation centres with facilities (S55): This surrogate was
highlighted only in case study #1. The religious places, schools, and community
buildings are demarcated as evacuation centres during disasters. However, better
facilities for accommodating people particularly taking care of people with specific
needs in those evacuation centres become the priority for any disaster management
agency and for the local authorities. People from faith oriented backgrounds seek
shelter in religious places than other infrastructure facilities. Hence, the ability of the
religious places with sufficient facilities to accommodate people evacuated during
disasters can be a surrogate to measure the existent cultural and religious beliefs that
can help in managing disaster situations.
Further, the measurement of this surrogate (S55) should include the measure of
religious places demarcated as evacuation centres, the past occupancy of the religious
places vs other places demarcated as evacuation centres, the number of religious places
Chapter 5: Interview analysis-Identification of potential surrogates 201
available with and without evacuation centre facilities, and the disaster awareness
programs conducted at the religious based evacuation centres.
6. Government disaster management plan integrating religious institutions/ faith-
based organisations (S56): This surrogate was selected as the fifth surrogate from case
study #1. The role of faith based organisations in a strongly religious community
cannot be overlooked due to long term trust built by them with the community. The
local authorities leading disaster management planning process and implementing
projects or actions have invited and included faith-based organisations and their
leaders/members to be part of the disaster management committee. The active
participation and proactive initiatives by the faith-based organisations will help to take
forward the implementation of disaster management activities proposed in the disaster
management plan.
The surrogate (S56) can be assessed by the measure of number of local cultural
and faith based organisations in the disaster management committee,
activities/projects by the cultural and faith based organisations with the government in
disaster preparedness work, and the capacity of cultural and faith based committees to
engage in disaster preparedness work (volunteer base, financial capacity, and
infrastructure or equipment etc.).
5.5.6 Summary of findings for indicator #5
The study initially identified 74 concepts and 33 themes from four case studies
for indicator #5. Similar themes were then aggregated and six higher-order themes
were identified through cross-case synthesis which can be considered as potential
surrogates to measure cultural and behavioural norms and practices in disaster
Figure 5.26. Summary of synthesis for fifth social resilience indicator –
social beliefs
Chapter 5: Interview analysis-Identification of potential surrogates 202
management. The summary of synthesis for the fifth social resilience indicator – social
beliefs is shown in Figure 5.26.
The following three surrogates, S51: Faith based
organisations/practices/activities, S52: Culture of women in the society, and S53:
Involvement of religious institutions in disaster preparedness, relief and response
activities have high validity, since they were identified in three of the four case studies.
Another set of relevant higher-order themes (S54: Early warning dissemination
trust on religious institutions, S55: Religious places as evacuation centres with
facilities, and S56: Government disaster management plan integrating religious
institutions/ faith-based organisations) were found in at least one of the case studies,
can also be potential surrogates to measure the cultural and behavioural norms and
practices in disaster management. Hence, six potential surrogates to measure the
cultural and behavioural norms and practices in disaster management are highly
reliable and practically applicable in similar contexts, since they were identified in
consultation with practitioners and policy makers who are highly experienced in
implementing disaster management activities at community level.
Chapter 5: Interview analysis-Identification of potential surrogates 203
SUMMARY OF POTENTIAL SURROGATES AND SELECTION OF
SET OF SURROGATES FOR EVALUATION IN PHASE II
The potential surrogates were obtained by analysing the higher-order themes
generated from the case study data analysis. All potential surrogates for the five social
resilience indicators identified from the case studies analysis, as shown in Sections 5.1
to 5.5, were compared and consolidated in Table 5.6 below.
Table 5.6. Cross-case tabulation for potential surrogates
Potential surrogates
Case
Study
#1
Case
Study
#2
Case
Study
#3
Case
Study
#4
Indicator 1: mobility and access to transport facilities
S11: Available transport facilities
targeting PwSN X X X X
S12: Evacuation places and centres X X X X
S13: Awareness programs/Early
warning systems X X X X
S14: Evacuation routes and plans X X
S15: Social support systems X
S16: Emergency information
dissemination and sources X
Indicator 2: social trust in pre and post disaster phases
S21: Effectiveness of community
based organisations/social service X X X X
S22: Level of services and resources of
local authorities/state support
for people
X X X X
S23: Functioning and effectiveness of
disaster management systems and
complain mechanisms
X X X
S24: Trust on information sharing/
early warning dissemination X
S25: Level of public support for
awareness and public programs X
S26: Public-government officer
relationship X
Indicator 3: learning from the past disaster experience
S31: Reaction to disaster early warning X X X X
S32: Awareness and disaster
knowledge level X X X
Chapter 5: Interview analysis-Identification of potential surrogates 204
S33: New DRR programs such as
innovative construction methods X X X
S34: Functional level of the disaster
management committee/members X X
S35: Disaster Risk Reduction (DRR)
and Disaster Preparedness
strategy
X
S36: Evacuation drills & disaster
preparedness kits X X
Indicator 4: involvement of People with Specific Needs (PwSN)
S41: Social safety programs for PwSN X X X X
S42: PwSN committees/groups or
representation of PwSN in
committees
X X X
S43: Organisations/projects for PwSN X X X X
S44: Participation of PwSN in training
programs X
S45: Disaster facilities with
access/priority to PwSN X X
S46: Planning and resources for PwSN
(organisational and government
support)
X X
Indicator 5: existent religious, cultural and behavioural practices
S51: Faith-based
organisations/practices and
activities
X X X X
S52: Culture of women in the society
(Gender norms) X X X
S53: Involvement of religious
institutions in disaster
preparedness, relief and response
activities
X X X
S54: Early warning dissemination trust
on religious institutions X X
S55: Religious places as evacuation
centres with facilities X
S56: Government disaster management
plan integrating religious
institutions/faith-based
organisations
X
Chapter 5: Interview analysis-Identification of potential surrogates 205
There are six potential surrogates for each of the five social resilience indicators
as shown in Table 5.6. However, some of the surrogates were only identified in one or
two of the case studies among the four case studies. In order to keep the number of
surrogates manageable for an online survey, it was decided to limit it to surrogates that
have a higher validity, which were identified in multiple case studies. Therefore,
potential surrogates that were identified in minimum three of the four case studies were
selected for evaluation in phase II. This made a total of 15 potential surrogates for
ranking by experts.
Three potential surrogates for each of the five key social resilience indicators
that were identified at least in three of the four case study areas that were selected for
evaluation and ranking in the next phase of this research is listed in Table 5.7
Table 5.7. Potential surrogates selected for evaluation in online survey (phase II)
Resilience indicator Potential surrogate measures
I1: Measuring ‘social
mobility and access to
transport facilities’
S11: Available transport facilities targeting PwSN
S12: Evacuation places and centres
S13: Awareness programs/Early warning systems
I2: Measuring ‘social
trust’
S21: Effectiveness of community based
organisations/social service
S22: Level of services and resources of local
authorities/state support for people
S23: Functioning and effectiveness of disaster
management systems and complain mechanisms
I3: Measuring the
‘learnings from the
past’
S31: Reaction to disaster early warning
S32: Awareness and disaster knowledge level
S33: New DRR programs such as innovative
construction methods
I4:Measuring
‘involvement/equity for
persons with specific
needs (PWSN)’
S41: Social safety programs for PwSN
S42: PwSN committees/groups or representation of
PwSN in committees
S43: Organisations/projects for PwSN
I5: Measuring
‘cultural/religious
norms and practices’
S51: Faith-based organisations/practices and activities
S52: Culture of women in the society (Gender norms)
S53: Involvement of religious institutions in disaster
preparedness, relief and response activities
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 206
Chapter 6: Survey analysis - Evaluation and
ranking of potential surrogates
As shown in Figure 6.1, this chapter has five key sections including the last
section (Section 6.5) as a summary of findings from phase II online survey.
Section 6.1 presents the key findings from the phase II of this research, which
aimed to evaluate and rank the potential surrogates identified in phase I of the study.
Those potential surrogates to assess social resilience were evaluated by international
and national disaster management experts. The results of the survey were analysed
using the multi-criteria decision making with equal criteria weights.
Section 6.2 presents the calculation of weights for each criterion from the survey
inputs by disaster management experts.
Section 6.3 provides a summary of the PROMETHEE ranking done with the
weights for the surrogate evaluation criteria obtained from the experts’ judgement
through the phase II survey (as shown in Section 6.2).
Section 6.4 presents the list of first ranked social resilience surrogates that was
selected for application as a final output from the evaluation and ranking of potential
surrogates.
Finally, Section 6.5 provides a brief summary of the phase II online survey
results.
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 207
6.1. Chapter 6 with key sections in the thesis structure
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 208
6.1. PROMETHEE RANKING AND ANALYSIS OF POTENTIAL
SURROGATES WITH EQUAL CRITERIA WEIGHTS
The results of PROMETHEE, which was used as a Multi-Expert Multi Criteria
Decision Analysis (ME-MCDA) to rank potential surrogates are presented in Sections
6.1.1 to 6.1.5. Two types of analysis were carried out for each social resilience
indicator:
1. Ranking of potential surrogates: Overall PROMETHEE ranking for each
social resilience indicator (Table 6.1) was based on the analysis of alternatives against
all five criteria as an overall group decision making using the inputs from multi-
experts. The Phi value is the net flow value as a result of the pairwise comparisons of
surrogates.
2. Analysis of opinions about potential surrogates by different cohorts of experts:
It is possible that different types of disaster management experts can have different
preferences for surrogates. Since the experts, who participated in the evaluation of
surrogates, have different degree of experience and also belong to different categories
such as practitioners, researchers, and policy makers, it is important to analyse
similarities and differences between their preferences. GAIA representations are
shown in Figures 6.2a-6.6a for different years of experience ranging from >10 years,
5-10 years, 3-5 years, to <3 years, while GAIA representations are shown in Figures
6.2b-6.6b for different types of experts ranging from practitioners, researchers, and
policy makers.
Table 6.1. Overall PROMETHEE rankings for five social resilience indicators
Resilience
indicator Rank Potential surrogate measures Net Phi
I1: Measuring
‘social
mobility and
access to
transport
facility’ using
surrogates
1 S12: Availability of evacuation places
and centres 0.0318
2 S13: Awareness raising programs/plans
and early warning systems -0.0080
3
S11: Transport facilities available
(emphasis to access transport for
persons with special needs)
-0.0239
I2: Measuring
‘social trust’
using
surrogates
1 S21: Effectiveness of CBO’s
activities/social service 0.0500
2
S22: Level of services and resources of
local authorities/Support for people
from state institutions
-0.0125
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 209
3
S23:Functioning and effectiveness of
disaster relief/management system and
complain mechanisms
-0.0375
I3: Measure the
‘learnings
from the past’
using
surrogates
1 S31: Reaction to disaster early warning 0.0750
2 S32: Awareness and disaster
knowledge level 0.0136
3
S33: New DRR programs including
new construction methods (e.g.
Houses)
-0.0886
I4:Measuring
‘involvement/e
quity for
persons with
specific needs
(PWSN)’
using
surrogates
1 S41: Social safety programs for PwSN 0.0466
2 S43: Organizations/projects for PwSN 0.0080
3
S42: PwSN Committees/registered
groups or representation of PwSN in
committees
-0.0545
I5: Measuring
‘cultural/religi
ous norms and
practices’
using
surrogates
1 S52: Culture of women in the society 0.0318
2 S51: Faith-based
organizations/practices/activities 0.0045
3
S53: Involvement of religious
institutions in disaster preparedness,
relief and response activities.
-0.0364
6.1.1 Indicator #1: Measuring ‘social mobility’
In this study, the surrogate ‘S12 - measure of evacuation places and centres’ was
preferred over the other two surrogates (S13 and S11) by the experts. This could be due
to the higher influence of evacuation potential of the population at-risk for emerging
disasters on social mobility. The identification and demarcation of evacuation places
and centres may have been done by authorities. However, the level of awareness of
evacuation places and centres among the population who are vulnerable to disasters
may be lacking to enable effective social mobility due to the absence of required
facilities for people with specific needs. On the other hand, the evacuation in times of
disasters using vehicles is most often a challenge in urban context, where streets can
be narrow that result in traffic congestion. Hence, the availability of transport facilities
sometimes may not be given first priority for the measurement of social mobility
during disasters.
Opinions of cohorts of experts on surrogates to measure indicator #1
Experts over five years of experience largely preferred the surrogate S12 over S13
and S11. However, the experts with average experience between 3 – 5 years opted
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 210
Figure 6.2 (b). GAIA representation of surrogates to measure social
mobility for different types of experts
Figure 6.2 (a). GAIA representation of surrogates to measure social
mobility for experts with varied years of experience
Legends for Figures 6.2 (a) and (b)
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 211
S13 as the surrogate measure of first choice. However, the experts with less than three
years of experience out-ranked S13 and S12 over S11. Overall, the results are skewed
towards S12, because the experts who have more than five years of experience form
the majority surveyed (68%). As shown in Figure 6.2a, the orientation of the decision
axis (red thick axis) indicate which cohorts of experts are in agreement with the
PROMETHEE rankings and who are not. Although it is obvious that the availability
of transport facilities and effective early warning messages are key to timely mobility
of people at-risk, the availability of evacuation centres and people’s awareness can be
the most important factor in determining the effectiveness of social mobility according
to the PROMETHEE ranking analysis. This could be the reason, the most experienced
cohort of experts aligned with the overall PROMETHEE ranking of the surrogate
(Figure 6.2a).
Based on occupation, all three groups of experts - practitioners, policy makers,
and researchers - ranked S12 as the most preferred surrogate. The surrogate S13 was
ranked second by policy makers and researchers, however it was the less preferred
option for practitioners. Similarly, Surrogate S11 performed better for practitioners,
compared to researchers and policy makers (Figure 6.2b). Practitioners had a strong
preference for surrogate S12 and S11. However, policy makers had greater preference
for surrogate S13 compared to S11. The surrogate S11 did not perform well among
researchers and policy makers compared to surrogates S12 and S13. Hence, this study
found, practitioners preferred the measure of evacuation places and centres (S12) and
available transport facilities (S11) to predict the mobility and transport accessibility
compared to the measure of awareness programs/early warning (S13). The policy
community prioritised the awareness of the availability of evacuation places/centres
(S13).
6.1.2 Indicator #2: Measuring ‘social trust’
In this study, the surrogate S21 - effectiveness of Community Based
Organizations’ (CBO) activities/social service was ranked first in PROMETHEE
ranking. It was also evident from this study that surrogate S22 – the existing level of
services and resources from the local authorities/state institutions got priority ranking
than surrogate S23 – the functioning and effectiveness of disaster management
mechanisms to measure social trust. In a resource limited local governance, the
functioning and effectiveness of disaster management mechanisms may become weak,
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 212
where the trust is built through routine work and development activities. Therefore,
the effectiveness and satisfactory level of routine services and resource allocation to
the community by local authorities (S22) can also be a priority measure of social trust
compared to the surrogate - functioning of disaster management mechanisms (S23).
Opinions of cohorts of experts on surrogates to measure indicator #2
Figure 6.3(a) shows that the results are skewed towards S21 where the decision
of experts with over 10 years of experience is closer. However, experts with 3-5 years
of experience preferred S22 over S21 and S23. The experts with 5-10 years of experience
were not conclusive about their preference between S21 and S23, while experts with
less than 3 years of experience were not conclusive in preferences between S21 and S22.
The less experienced cohort (less than 5 years of experience) preferred the measure of
service and resources by the local authorities and government departments as a priority
surrogate than the effectiveness of CBOs to assess social trust. In some cases, it is
possible that the measure of services and resource allocation with state departments
and local authorities can be easily done rather than obtaining accurate information for
measuring effectiveness of CBOs in measuring social trust in a disaster context.
The policy and practice groups aligned with the overall PROMETHEE rankings.
However, the highest preference of the research group inclined towards surrogate S22
as shown in Figure 6.3(b), which is similar to the preferences of less experienced
cohort of experts.
6.1.3 Indicator #3: Measuring ‘learnings from the past’
Surrogate S31 – the reaction by the community to disaster early warning
messages was preferred compared to other two surrogates (S32 and S33) to measure
learnings from the past disasters in the PROMETHEE ranking. Although, S32 – the
level of awareness and disaster management knowledge and S33 – new DRR programs
implemented such as new methods of housing construction - can provide a priority
measure of learnings from the past disasters as a key community competency to
disaster resilience. Experts in this study prioritized the reaction to disaster early
warning messages as a good surrogate measure to assess learning from past disasters.
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 213
Figure 6.3(a). GAIA representation of surrogates to measure social
trust for experts with varied years of experience
Figure 6.3 (b). GAIA representation of surrogates to measure social
trust for different types of experts
Legend for Figures 6.3(a) and (b)
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 214
Opinions of cohorts of experts on surrogates to measure indicator #3
Experts with experience of over 10 years had similar overall preferences towards
indicator#3 surrogate measures. As shown in Figure 6.4(a), the first preference of
experts with over 10 years of experience and experts with less than 5 years of
experience was S31. Figure 6.4 (b) also indicates that the first ranked surrogate among
researchers and practitioners is S31. Surrogate S32 – the level of awareness and
knowledge about disasters can also be a good measure for learnings from the past
disasters, similar to surrogate S31 – reaction to disaster early warning messages, which
is preferred by policy experts and experts with 5-10 years of experience. More
awareness and better knowledge about disaster risks will lead to better reaction to
disaster early warning messages. However, the measurement complexity of surrogate
S31 – reaction to disaster early warnings can be higher compared to surrogate S32 –
measure of awareness and disaster knowledge level.
6.1.4 Indicator #4: Measuring ‘involvement/equity for persons with specific
needs (PWSN)’
In this study, surrogate S41 - Social safety programs for Persons with Specific
Needs (PwSN) was preferred compared to the other two surrogates (S42 and S43) to
assess the involvement and equity measures. The other two surrogates are S43:
Organizations/projects for PwSN and S42: PwSN Committees/registered groups or
representation of PwSN in committees. The social safety programs focus on vulnerable
groups in a community in a disaster situation. The inclusion of PwSN such as disabled,
elderly, and women headed households in the existing social safety programs helps to
improve their resilience to disasters. Surrogate S43 - availability of projects or specific
organizations to work on PwSN can be another potential surrogate which was ranked
second by the experts. This study found that the surrogate S42 - the representation of
PwSN in committees/the existence of such committees/registered groups as the least
preferred surrogate to indicate the involvement and equity for PwSN. The participation
in committees most often do not completely reflect the active implementation of
projects which can bring real impact. However, the social safety programs can indicate
the tangible involvement of people in building resilience.
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 215
Figure 6.4 (b). GAIA representation of surrogates to measure
learnings from the past disasters of different types of experts
Figure 6.4 (a). GAIA representation of surrogates to measure learnings
from the past disasters of experts with varied years of experience
Legend for Figures 6.4 (a) and (b)
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 216
Opinions of cohorts of experts on surrogates to measure indicator #4
The preference of all cohorts of experts retained S41 as the first ranked surrogate,
except the cohort with 5-10 years of experience, who ranked S43 as their first
preference. However, all cohorts ranked S42 as the least preferred surrogate as shown
in Figures 6.5(a) and 6.5(b). Similarly, preferences of practitioners and policy makers
were aligned with the overall ranking of surrogates, whereas the first preference of
researchers was the surrogate S43 – ‘the availability of organizations and projects’
targeting PwSN. This preference was similar to the cohort of experts with 5-10 years
of experience. In conclusion, preference of more experienced practitioners and policy
makers were same as the overall preference of surrogates to measure indicator #4.
Further, all cohorts of experts ranked surrogate S42- ‘representation of PwSN in
committees or in registered groups as a weak surrogate to measure the involvement
and equity for PwSN.
6.1.5 Indicator #5: Measuring ‘cultural/religious norms and practices’
In this study, the first ranked surrogate for measuring cultural/religious norms
and practices was S52: culture of women in society. Among the three surrogates
evaluated by experts, surrogate S51: faith-based organizations/practices/activities was
ranked second and surrogate S53: involvement of religious institutions in disaster
preparedness, relief and response activities was the least preferred surrogate to
measure cultural/religious norms and practices. Hence, the measure of gender based
practices was prioritised as an important surrogate in this study compared to faith-
based practices and involvements. The cultural practices among women, such as their
engagement in public forums and participation in awareness programs may be critical
in determining the social resilience to disasters in many contexts. In the evaluation of
surrogates by experts, it is likely that most of the experts preferred the most critical
factor of the respective resilience indicator as the most preferred surrogate.
Opinions of cohorts of experts on surrogates to measure indicator #5
As shown in Figures 6.6 (a), highly experienced cohort of experts with more than
5 years differed from the overall ranking and opted surrogate S51 as their first
preference to measure cultural/religious norms and practices. However, experts with
less than 5 years of experience have shown a similar preference to overall ranking.
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 217
Figure 6.5 (b). GAIA representation of surrogates to measure
‘involvement/equity for PWSN’ of different type of experts
Figure 6.5 (a). GAIA representation of surrogates to measure
‘involvement for PwSN’ of experts with varied years of experience
Legend for Figures 6.5(a) and (b)
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 218
Similarly, the practitioners and policy makers followed the same preference of overall
ranking, the cohort of researchers differed from overall ranking, selecting S51 as their
first preferred surrogate (Figure 6.6 (b)). From the analysis, researchers viewed the
role of faith based practices as an important element in measuring social beliefs
compared to cultural practices specific to women, since some specific cultural
practices are at times influenced by faith orientations. The measurement of faith based
practices (surrogate S51) in a community can also provide a broader measure including
the gender specific cultural practices that can enhance or deteriorate resilience. The
different cohort of experts have contrasting opinions between S52 and S51 as the priority
surrogate to assess cultural/religious practices and norms.
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 219
Figure 6.6 (a). GAIA representation of surrogates to measure
‘cultural/religious practices’ of experts with varied years of experience
Figure 6.6 (b). GAIA representation of surrogates to measure
‘cultural/religious norms and practices’ of different type of experts
Legend for Figures 6.6 (a) and (b)
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 220
CALCULATION OF SURROGATE EVALUATION CRITERIA
WEIGHT
The consolidated Analytic Hierarchy Process resulted in a weightage for each of
the surrogate evaluation criteria (Table 6.2). The results show that time-sensitivity,
communicability and accuracy are the three criteria that gained weight more than 20%.
The other two criteria - measurement complexity (13.8%) and cost-effectiveness
(16%) gained less weightage among the five surrogate evaluation criteria. The results
further showed that the respondents have more concerns on the ability of the surrogates
to measure resilience in different time periods/phases of a disaster and the ability of
surrogates to predict the target indicators accurately.
Table 6.2. Criteria weight obtained from survey responses using AHP
Criterion Criteria name Weight
1 Crit-1 Accuracy 23.9%
2 Crit-2 Cost-effectiveness 16.0%
3 Crit-3 Measurement complexity 13.8%
4 Crit-4 Communicability 22.3%
5 Crit-5 Time-sensitivity 24.0%
The weight for the criteria - cost-effectiveness and measurement complexity are
less than the average 20% (20% is the weight if the equal weightage is applied as it
was done in section 6.1). The weights for other three criteria (accuracy,
communicability, and time-sensitivity), have got weightage more than average 20%.
The calculation of weightage show that accuracy, communicability, and time-
sensitivity are three more important criteria than cost-effectiveness and measurement
complexity for evaluating surrogates, according to the results in this study.
OVERALL PROMETHEE RANKING WITH WEIGHTED CRITERIA
In section 6.1, PROMETHEE ranking of potential surrogates obtained with equal
weights for all five surrogate evaluation criteria was presented. This section presents
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 221
PROMETHEE rankings of same potential surrogates obtained with the weighted
criteria (Table 6.3).
Table 6.3. Overall PROMETHEE rankings for five social resilience indicators with
weighted criteria
Resilience
indicator
Ran
k
Alternatives (Potential surrogate
measures) Net Phi
I1:Measuring
‘social mobility
and access to
transport
facility’
1 S12: Availability of evacuation places
and centres 0.0339
2
S13: Awareness raising
programs/plans and early warning
systems
-0.0095
3
S11: Transport facilities available
(emphasis to access transport for
persons with special needs)
-0.0244
I2:Measuring
‘social trust’
1 S21: Effectiveness of CBO’s
activities/social service 0.0641
2
S22: Level of services and resources
of local authorities/Support for
people from state institutions
-0.0253
3
S23:Functioning and effectiveness of
disaster relief/management system
and complain mechanisms
-0.0388
I3:Measure the
‘learnings from
the past’
1 S31: Reaction to disaster early
warning 0.0803
2 S32: Awareness and disaster
knowledge level 0.0322
3
S33: New DRR programs including
new construction methods (e.g.
Houses)
-0.1125
I4:Measuring
‘involvement/eq
uity for persons
with specific
needs (PWSN)’
1 S41: Social safety programs for
PwSN 0.0512
2 S43: Organizations/projects for PwSN 0.0124
3
S42: PwSN Committees/registered
groups or representation of PwSN in
committees
-0.0636
I5: Measuring
‘cultural/religiou
s norms and
practices’
1 S52: Culture of women in the society 0.0347
2 S51: Faith-based
organizations/practices/activities 0.0066
3
S53: Involvement of religious
institutions in disaster preparedness,
relief and response activities.
-0.0413
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 222
The PROMETHEE rankings between equally weighted criteria and consolidated
AHP weighted criteria were compared. There is no difference in the overall ranking,
although net phi values are different. Figures 6.7 to 6.11 show the net flow value
difference between each of the surrogate for equal criteria weights and experts’
consolidated criteria weights. Further, the differences in net flow values between
surrogates for both weights are also very minimal as shown in Figures 6.7 to 6.11.
It could be because the experts’ evaluation of surrogates was mostly consistent
and within a small margin of variation. The small deviation in the Likert scale will not
influence a larger deviation in the net phi value. This means that there is no influence
in ranking as a result of an extreme opinion in the criteria with higher or lower weight.
It can be concluded from this analysis that equal weight for five surrogate evaluation
criteria can be used for evaluating social resilience surrogates to rank and select
surrogates in disaster management
Figure 6.7. Comparison of net flow values (ranking) of surrogates for
indicator #1 [CW – Criteria Weight Equal and Experts]
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 223
Figure 6.8. Comparison of net flow values (ranking) of surrogates for
indicator #2 [CW – Criteria Weight Equal and Experts]
Figure 6.9. Comparison of net flow values (ranking) of surrogates for
indicator #3 [CW – Criteria Weight Equal and Experts]
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 224
Figure 6.10. Comparison of net flow values (ranking) of surrogates for
indicator #4 [CW – Criteria Weight Equal and Experts]
Figure 6.11. Comparison of net flow values (ranking) of surrogates for
indicator #5 [CW – Criteria Weight Equal and Experts]
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 225
FIRST RANKED SOCIAL RESILIENCE SURROGATE IN DISASTER
MANAGEMENT
The five first ranked surrogates include one surrogate for each of the five
resilience indicator, which were ranked first as the optimum surrogate among all
surrogate evaluation criteria. These are as follows:
S*1: Availability/access of evacuation centres for measuring I1: ‘social mobility and
access to transport facility’
S*2: Effectiveness/performance of CBO activities/social service for measuring I2:
‘social trust’
S*3: Reaction to disaster early warning for measuring I3: ‘learnings from the past’
S*4: Social safety programs for PwSN for measuring I4: ‘involvement/equity for
persons with specific needs (PWSN)’
S*5: Gender norms/culture of women in the society for measuring I5:
‘cultural/religious norms and practices’.
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 226
Figure 6.12. First ranked surrogates for priority assessment of social resilience
indicators in disaster management
Chapter 6: Survey analysis - Evaluation and ranking of potential surrogates 227
SUMMARY OF FINDINGS FROM THE SURVEY RESEARCH
Three potential surrogates for each of the five selected social resilience
indicators were identified in an exploratory case study in a disaster context (in phase
I) and evaluated independently against five criteria by multiple experts consisting of
practitioners, researchers, and policy makers through an online survey. Potential
surrogates were then ranked using multi-criteria group decision support system in
PROMETHEE.
The most-preferred surrogate (first ranked) can be the utmost critical facet of the
respective resilience indicator in a disaster context. Hence, the first ranked surrogate
can provide a fairly good representation of overall resilience of the respective indicator
as it is also mostly very relevant in practice. However, divergent opinions exist among
the different cohort of experts on the overall ranking of surrogates. For example, the
comparison between overall ranking of surrogates and the ranking of different cohort
of experts showed that the preferences of experts with more than five years of
experience from practitioners and policy makers have mostly aligned with overall
ranking of surrogates. Results further revealed that experienced practitioners tend to
opt for surrogates that can be easily measured with the existing data and communicated
without much complexities for effective policy decisions. The results from this study
will also have greater practical applicability in the field and policy decisions, since
more than two-third of the experts are highly experienced practitioners and policy
makers in disaster management.
The third and final key step in the social resilience surrogate framework is the
selection of optimum surrogates for application. This includes three sub-steps: (1)
evaluation of surrogates against five surrogate evaluation criteria, (2) ranking of
potential surrogates based on the evaluation results, and (3) selection of optimum
surrogates for application. In phase II of this study, the first sub-step was done through
an online survey and the second sub-step was executed through the analysis of the data
obtained from the survey. The third sub-step was done by selecting first ranked
surrogates for application.
Chapter 7: Synthesis of key findings 228
Chapter 7: Synthesis of key findings
This chapter has four key sections, as shown in Figure 7.1.
Sections 7.1 to 7.3 brings together key findings that emerged from the analysis
of data in Chapters 4, 5 and 6 in relation to each of the three research objectives (RO1
to RO3) as defined in Section 1.5. The research objectives are aligned with the three
key steps (A to C) of the conceptual surrogate development framework (See Figure
3.6) tested in this study to assess social resilience in a disaster context. These sections
also provide an interpretation of key findings with reference to the literature so as to
highlight the contribution to knowledge and demonstrate achievement of the three
research objectives.
The Section 7.4 details the revisions to the conceptual surrogate development
framework based on the preceding discussions. This revised framework for future
application, is presented as an integrated framework of all three key steps, which
answers the key research question of this study.
7.1. Chapter 7 with key sections in the thesis
structure
Chapter 7: Synthesis of key findings 229
KEY FINDINGS IN RELATION TO RESEARCH OBJECTIVE ONE
(RO1)
RO1: To select key social resilience indicators that require surrogate
approach by developing an adaptive and inclusive social resilience
framework
RO1 of this study was tested in key step A of the conceptual surrogate
development framework (See Figure 3.6) through the selection of social resilience
indicators for applying the surrogate approach. The key outcomes in this step are the
development of an inclusive and adaptive ‘5S’ social resilience framework, the
surrogate decision criteria, and the selection of key social resilience indicators for
applying the surrogate approach as shown in Figure 7.2.
A.1: Identify key social resilience indicators:
The identification of social resilience indicators was done by developing an
inclusive and adaptive ‘5S’ social resilience framework, through a critical review of
existent social resilience frameworks, in the literature review and research design
phase. This study found that, a generic, but adaptable framework such as ‘5S’
framework (see Figure 2.5) proposed in this research help to select key social resilience
indicators in a consistent manner to develop the surrogate approach. There has been a
research gap to develop a comprehensive framework that is scientifically grounded,
but can be practically applicable to select resilience indicators for assessment (Keating
et al., 2017). Hence, the ‘5S’ framework in social resilience assessment that was
developed in this study, was used to select indicators methodically to apply the
surrogate approach. This study further found that, most of the social resilience
7.2. Key step A and related outcomes to achieve RO1
Chapter 7: Synthesis of key findings 230
indicators in the ‘5S’ framework are either not feasible to measure through direct
methods or the existing census-based measures for them are not adequate, hence
require new methods for measurement, such as a surrogate approach.
The ‘5S’ framework is structured in 5 key dimensions of social resilience by
incorporating 16 characteristics and 46 indicators, mostly process-oriented indicators
(See Figure 2.5). Many existent frameworks in the literature have used outcome-
oriented indicators (Cutter et al., 2008) for resilience assessment rather than process-
oriented indicators (Sharifi, 2016). Many of the existing resilience frameworks were
developed to a specific context, hence, they tend to select specific indicators relevant
to the context, which limits its applicability to a wider context (Woolf et al., 2016).
For example, Kwok et al. (2016) and Khalili et al. (2015) developed context specific
social resilience indicators, which leave out some key indicators relevant in other
context, which make their framework not very adaptable to different contexts.
The existent frameworks mostly considered social resilience characteristics such
as social demography, social networks, and community engagement (Saja et al., 2018)
and have not given importance to social resilience dimensions such as social trust,
social competence, social equity and diversity/inclusiveness, and social beliefs. None
of the existing social resilience frameworks have succeeded in integrating all key
indicators in a generic and adaptable structure for social resilience measurement to-
date, makes the ‘5S’ framework innovative, which is adaptable in any context. These
findings extend the research of Cutter (2016), Sharifi (2016), and Kwok et al. (2016),
and Khalili et al. (2015) on the need for an inclusive and adaptable framework, by
identifying key social resilience indicators and structuring it in a ‘5S’ framework,
which will assist in selecting social resilience indicators to apply surrogate approach
in any context.
A.2: Decision for surrogate approach/define objective:
Once the key social resilience indicators are identified, a decision for surrogate
approach needs to be made, if the identified social resilience indicators are not easily
measurable. There has been a tendency to prioritise easily measurable outcome-
oriented resilience characteristics. The existing approaches used mostly from the
publicly available census data are useful as a tool for initial resource allocation and
investment decisions at high level (Jülich, 2017) (See Appendix A for existing
measures using census data for five selected social resilience indicators). However,
Chapter 7: Synthesis of key findings 231
they are often contested for their practical applicability at the community level for
effective resilience building interventions, as they often fail to capture process-
oriented and dynamic resilience features. All the indicators except six indicators in the
two social resilience characteristics (social demography and household structure) of
the ‘5S’ framework require surrogate approach for their assessment.
Since there are no previous studies on the surrogate approach in disaster
management, a set of surrogate decision criteria were drawn from the surrogate
approach literature in environmental science. The most important decision factor
which led to the adoption of a surrogate approach in ecology is the difficulty to directly
assess ecological systems (Lindenmayer et al., 2015b). However, this study found that
a set of surrogate decision criteria are needed to select social resilience indicators to
develop a surrogate approach. Hence, three key surrogate decision criteria used in this
study to select the target indicator for applying the surrogate approach are: (1) The
indicators should be process-oriented resilience indicators that are not a very static
indicator (dynamic, which frequently changes over time) (Cai et al., 2018; Cutter,
2016). (2) Indicators are complex for conceptualisation and cannot be easily measured
quantitatively (Sharifi & Yamagata, 2016). (3) The existing measures using indirect
methods do not provide an adequate measure of the target indicator (for example, the
existing measures mainly used data from publicly available census data sources)
(Jülich, 2017). These findings extend Lindenmayer et al. (2015b) research on the use
of key factors to decide on a surrogate approach in environmental science, by
formulating three surrogate decision criteria for systematically selecting resilience
indicators for developing a surrogate approach in a disaster management context.
For the purpose of this research to test the surrogate approach, five social
resilience indicators were selected from each of the five dimensions of the ‘5S’ social
resilience framework. This was done through review of literature on existing
measurements, based on the above key selection criteria for applying the surrogate
approach. In addition to the above three criteria to apply surrogate approach, this study
also considered indicators that are relevant to multiple disasters and different
geographical and socio-economic contexts, to make the findings widely applicable in
different contexts.
Chapter 7: Synthesis of key findings 232
KEY FINDINGS IN RELATION TO RESEARCH OBJECTIVE TWO
(RO2)
RO2: To identify potential surrogates to measure key social resilience
indicators in disaster management
In order to achieve RO2 of this study, the key step B of the conceptual surrogate
development framework (See Figure 3.6) was implemented to identify potential
surrogates to measure the five key social resilience indicators. The key outcomes of
this process as shown in Figure 7.3, include: six potential surrogates for each of the
five social resilience indicators; a set of measurement protocols for each of the
potential surrogates; and finally, the selection of surrogates identified in at least three
of the four case studies for further evaluation against surrogate evaluation criteria in
Phase II.
B.1. Explore all potential surrogates
This study found six potential surrogates for each of the five social resilience
indicators selected for testing the surrogate approach, as listed in Table 5.6. However,
three of the potential surrogates identified for each of the five social resilience
indicators have high validity, since they were found in at least three of the four case
studies in this research. Each indicator is discussed below in relation to their
contribution to the resilience assessment literature.
7.3. Key step B and related outcomes to achieve RO2
Chapter 7: Synthesis of key findings 233
Indicator #1: Assessing social mobility and access to transport facilities:
The six potential surrogates and corresponding measurement protocol for
indicator #1, are summarised in Section 5.1.5. Three potential surrogates that were
found in multiple case studies include: S11: Available transport facilities targeting
People with Specific Needs (PwSN), S12: Evacuation places and centres, and S13:
Awareness programs/Early warning systems as shown in Table 5.6.
In the literature, social mobility and access to transport is most commonly
measured by vehicle ownership and available transport means (Burton, 2015; Kotzee
& Reyers, 2016) using census data (Kusumastuti et al., 2014; Mayunga, 2007; Qasim
et al., 2016b). This study highlighted that the use of a vehicle by every household ends
up in chaotic traffic congestion, given the narrow roads and bridges. Hence, the priority
for transport assistance should be given to people with specific needs (Peacock et al.,
2010). This study also identified the measure of vehicle availability and accessibility
for the transportation of people with specific needs (S11), as a potential surrogate to
assess social mobility. This finding extends the work of Peacock et al. (2010) on
assessing transport assistance for people with specific needs, by proposing a new
surrogate - vehicle availability and accessibility for transportation of people with
specific needs (S11), to assess social mobility in times of disasters, which has not been
used in a disaster context.
This study findings also highlighted that at times, people in highly congested
urban areas need to evacuate by foot directly to the nearest evacuation centre. When
the evacuation centre is located far away, people may need to go to the nearest
highway, where there is access to mass transportation. For example, Guadagno (2016)
emphasised that the identification of evacuation centres and awareness programs for
effective evacuation are important measures of resilience to disasters. These findings
extends the research by Guadagno (2016) on the identification of evacuation centres
and awareness programs for effective evacuation as measures of social mobility by the
use of two potential surrogates - evacuation centres/places with accessibility for PwSN
(S12) and awareness programs to effectively respond to early warning messages (S13),
for the assessment of social mobility.
Chapter 7: Synthesis of key findings 234
Indicator #2: Assessing social trust in a disaster context:
This study found six potential surrogates and corresponding measurement
protocol for indicator #2, as summarised in Section 5.2.5. Three potential surrogates
that were found in multiple case studies include: S21: Effectiveness of community
based organisations/social service; S22: Level of services and resources of local
authorities/state support for people and S23: Functioning and effectiveness of disaster
management systems and complaint mechanisms as shown in Table 5.6.
In the literature, social trust was mostly assessed through direct methods using
community surveys and observations (Uslaner, 2016) or through publicly available
census-based measures such as voter turn-out in elections, level of ethnic segregation,
and crime rate (Asadzadeh et al., 2017; Joerin et al., 2014; Sherrieb et al., 2010).
Although, the critical role played by CBOs to help communities to enhance their
resilience is well-established in the literature, Drennan and Morrissey (2019)
highlighted that how effectively CBOs perform disaster management activities need
to be assessed. This study found that the effectiveness and performance of CBOs and
their level of active social service (S21) is a potential surrogate measure of social trust
in a disaster context.
Further, the need for high-quality disaster resilience building programs to build
trust demand proper resource allocation and functioning of disaster management
systems by local authorities, since they play an important role in disaster management
(Henstra, 2010). This study also found two more potential surrogates - level of services
and resource allocation from local authorities in disaster management activities (S22)
and regular functioning of disaster management systems (S23) to assess social trust in
a disaster context. All three surrogates (S21- S23) found in this study can capture the
important processes related to social trust with different social entities as opposed to
census data. These findings contradict that of Asadzadeh et al. (2017), Joerin et al.
(2014), and Sherrieb et al. (2010), on effectively assessing social trust in a disaster
context through census-based measures, by providing new measures such as
effectiveness of community based organisations/social service (S21), level of services
and resources of local authorities/state support for people (S22), and functioning and
effectiveness of disaster management systems and complaint mechanisms (S23) for the
assessment of social trust in a disaster context.
Chapter 7: Synthesis of key findings 235
Indicator #3: Assessing learnings from the past as social competence:
This study found six potential surrogates and corresponding measurement
protocol for indicator #3, as summarised in Section 5.3.5. Three potential surrogates
that were found in multiple case studies include: S31: Reaction to disaster early
warning, S32: Awareness and disaster knowledge level, and S33: New DRR programs
such as innovative construction methods as shown in Table 5.6.
Many frameworks fail to incorporate the learnings from past disaster experience
as an indicator due to the difficulty in measuring it through census based datasets.
Effective early warning systems have saved many fatalities in the past and every time
when there is a disaster, people learn new ways to react to early warning (Keating et
al., 2016). Further, the perceptions of emerging disaster risk and hazard severity has
been cited in the literature as a potential measure for community competence and
learnings from the past experience (Cutter, 2016; Leykin et al., 2016). This study
finding supports the research by Cutter (2016) and Leykin et al. (2016) on assessing
learnings from the past as a social competence through perceptions of disaster risk and
hazard severity, by the use of surrogate - awareness and disaster knowledge level (S32)
as a measure of learnings from the past disaster experience.
Further, there has been increasing implementation of innovative community
based disaster risk reduction (DRR) initiatives based on past disaster experience
(Izumi et al., 2019), which provide an important measure of learnings from past
disasters. However, the existent frameworks failed to include the measure of
innovative initiatives as a measure of learnings from the past disasters. These findings
extend the research of Izumi et al. (2019) on the identification of innovative
community DRR initiatives as potential measures for learnings from the past disasters
by two potential surrogates - the reaction to disaster early warning (S31) and
implementation of innovative Disaster Risk Reduction (DRR) programs (S33), for the
assessment of learnings from the past disasters as a community competence.
Indicator #4: Assessing involvement of people with specific needs as social equity:
This study found six potential surrogates and corresponding measurement
protocol for indicator #4, as summarised in Section 5.4.5. Three potential surrogates
that were found in multiple case studies include: S41: Social safety programs for PwSN,
Chapter 7: Synthesis of key findings 236
S42: PwSN committees/groups or representation of PwSN in committees, and S43:
Organisations/projects for PwSN as shown in Table 5.6.
In a disaster context, the highest priority should always be given to People with
Specific Needs (PwSN) such as children, older people, pregnant and lactating mothers,
and people with disabilities, who are the most vulnerable segment of the population be
easily and severely affected by a disaster (Sphere, 2018). However, most of the
resilience frameworks operationalised in a disaster context used census based social
demographic measures such as percentages of elderly population and children,
population in productive age, race and ethnicity, female population, people with
disability and age dependency ratio (Sherrieb et al., 2010; Woolf et al., 2016; Yoon et
al., 2016), to assess involvement of PwSN.
The effective design and use of safety net programs to increase resilience to
disasters and to respond to post-disaster needs are increasingly emphasised in disaster
management (Pelham et al., 2011). Further, the inclusion of people with specific needs
in the decision making structure such as in disaster management committees or in
organisations dealing with disasters, play an important role in enhancing their
resilience (Twigg et al., 2018). The existent frameworks fail to include key surrogate
measures such as social safety programs for PwSN (S41), PwSN committees/groups or
representation of PwSN in committees (S42), and Organisations/projects for PwSN
(S43) as found in this study. These findings are contrary to research findings of Sherrieb
et al. (2010), Woolf et al. (2016), and Yoon et al. (2016) on assessing the involvement
of PwSN as social equity through measures such as percentage of elderly population,
productive age population, and female population, by providing more important
measures in a disaster context such as social safety programs for PwSN (S41), PwSN
committees/groups or representation of PwSN in committees (S42), and
Organisations/projects for PwSN (S43) for assessing the involvement of PwSN.
Indicator #5: Assessing cultural norms/behaviours as social belief:
This study found six potential surrogates and corresponding measurement
protocol for indicator #5, as summarised in Section 5.5.5. Three potential surrogates
that were found in multiple case studies include: S51: Faith-based
organisations/practices and activities, S52: Culture of women/Gender norms that hinder
disaster management activities, and S53: Involvement of faith-based organisations and
Chapter 7: Synthesis of key findings 237
religious institutions in disaster management. These were found as potential surrogates
across many case study locations as shown in Table 5.6.
In some communities which are faith-oriented, social beliefs/norms are largely
influenced by religious beliefs and practices. Religious belief was measured through a
survey of households who ‘believe that disasters happen by god’s will and do nothing’
(Lovell & Le Masson, 2014). Some other frameworks have used census-based
measures (Cutter, 2016; Peacock et al., 2010; Sherrieb et al., 2010).
The gender norms and cultural traditions in certain cultures and faiths are crucial
factors to understand the diversity needs of resilience building in a disaster context
(Hazeleger, 2013). This study found that the cultural or religious barriers for women
to actively participate in social activities, more specifically the involvement of women
in disaster related projects as a key measure of resilience across all case study
locations. Similar measures can be considered as one of the priority surrogates in
similar contexts, such as in strong faith-oriented communities. Further, the utilisation
of resources, practices, and networks available with faith-based organisations are key
sources of building resilience to disasters (Alawiyah et al., 2011; Ostadtaghizadeh et
al., 2016), particularly in strong faith-oriented communities such as in this case study
locations. Hence, these findings extend the research by Peacock et al. (2010), Cutter
(2016) and Sherrieb et al. (2010) on assessing cultural norms using census-based
measures from public data bases, by three potential surrogates (S51, S52, and S53) from
locally available data sources, for assessing cultural practices as social beliefs in a
disaster context.
B.2. Establish the surrogacy relationship
In this study, the relationship of each potential surrogate with the target indicator
was established through qualitative interpretations using interview transcripts, as
detailed in Chapter 5. The surrogate relationship with the target indicator of measure
is established mostly through statistical inferences and measurement methods largely
using sampling approaches (Athey et al., 2016). For example, in a stormwater quality
study using surrogates, different quantitative techniques were used to establish the
surrogacy relationship (Singh et al., 2013; Ziyath et al., 2013), such as multivariate
data analysis (Settle et al., 2007) and single linear regression (Miguntanna et al., 2010).
Since, the social resilience indicators selected for surrogate development in a disaster
context were process-oriented and dynamic indictors, it is very difficult to determine
Chapter 7: Synthesis of key findings 238
the strength and sensitivity of the surrogacy relationship quantitatively at the initial
stage of exploring potential surrogates. Even, in the ecological context, establishing
surrogacy relationship through understanding causal relationships between surrogates
and the target is difficult, since robust quantitative tests are needed (Lindenmayer &
Likens, 2011).
The interview participants explained, how the potential surrogate they proposed
are linked to the target and how it changes, through examples from their work in
disaster management. The understanding of the link between the surrogate and the
target indicator by disaster management stakeholders at the local level, who implement
disaster resilience projects is important to inform the literature (Keating & Hanger-
Kopp, 2019; Levine, 2014). This study found that the discussion with experts to
establish surrogacy relationship on the proposed potential surrogates was a robust
method at the initial stages of exploring potential surrogates for social resilience
assessment in disaster management. The methodology of this study extends the
research by Athey et al. (2016), Settle et al. (2007), and Miguntanna et al. (2010) on
establishing surrogacy relationship through quantitative methods. This is done in this
research by establishing surrogacy relationship for social resilience measures in a
disaster context using qualitative interpretations through stakeholder engagement and
practical examples locally.
B.3. Determine the protocols for surrogate measurement:
This study also identified a set of surrogate measurement protocols for all
potential surrogates as detailed in Chapter 5. In general, the surrogates in ecology were
measured by the population trends of species to monitor changes in biodiversity
(Gregory et al., 2007), and mapping of surrogate systems to understand surrogate
behaviour (Lindenmayer et al., 2015b). However, Cutter et al. (2010) highlighted that
determining standards and matrices for resilience assessment is a challenge. For
example, trend analysis in sustainability assessment (Singh et al., 2009), and
participatory mapping such as vulnerability and community resource maps in disaster
risk management projects (Cadag & Gaillard, 2012) have been used as assessment
tools in vulnerability and sustainability assessment.
This study found spatial and temporal types of measurement protocols proposed
for measuring potential surrogates using locally available and frequently updated
administrative data. These can be widely categorised as the following key types:
Chapter 7: Synthesis of key findings 239
analysing trends of initiatives or projects such as social safety program subscribers
targeted for disaster related assistance, spatial mapping of accessibility and social
entities, such as access to evacuation centres by the most vulnerable social groups and
active CBOs spatial coverage; and coverage of community based disaster risk
reduction projects from the reports produced by the state departments or local
authorities. These findings extends the research by Singh et al. (2009) and Cadag and
Gaillard (2012) on spatial and temporal participatory mapping in sustainability and
vulnerability assessment by analysing trends for disaster related initiatives in the
community, mapping of accessibility of disaster related entities/social entities, and
mapping of the coverage of disaster related projects to measure the proposed
surrogates in social resilience assessment in disaster management.
Further, the qualitative measures found in this study included: the recording of
past disaster experiences, identification of positive or negative trends in the community
that hinder resilience, and changes or improvements happened for the target measures.
As opposed to the current tendency to quantify resilience for developing an index for
different geographic locations, the focus of resilience assessment should also be on
what interventions are needed that will help communities to build their resilience to
emerging disasters (Levine, 2014). The practitioner perspective of resilience
assessment demands more practically oriented methods to assess resilience (Keating
& Hanger-Kopp, 2019).
In the existent social resilience assessment frameworks, only a small number of
frameworks have used qualitative measures. This include: recording the improvements
and weaknesses in asset base, capacities, and external resources of community
interventions (Woolf et al., 2016); recording the ideas for resilience improvements and
provided case study examples for key resilience concepts such as social networks,
economy, and infrastructure (Hegney et al., 2008); and participatory tools such as
stakeholder analysis, vulnerability and capacity assessment, and community
conversations to assess social resilience (Pfefferbaum et al., 2013). This study found
recording of past disaster experiences and positive/negative trends in the community
that supports or hinder as key types of qualitative measurement protocols to assess
social resilience indicators such as the learnings from the past disaster experience as a
social competency and cultural norms and behaviours as social beliefs that support or
hinder resilience. Further, the changes and improvements for the target surrogate
Chapter 7: Synthesis of key findings 240
measures need to be recorded qualitatively, so that the required resilience building
activities can be identified. These findings extend the research by Woolf et al. (2016),
Pfefferbaum et al. (2013), and Hegney et al. (2008) on qualitative resilience
assessment methods by recording past disaster experiences, identification of positive
or negative trends in the community that hinder resilience, and changes or
improvements of the target surrogate measures. The measurement protocols for the
surrogates that were ranked first in the next phase (RO3) and how they contribute to
the literature are discussed in Section 7.3.1.
KEY FINDINGS IN RELATION TO RESEARCH OBJECTIVE THREE
(RO3)
RO3: To evaluate and select optimum surrogates for application by ranking the
potential surrogates against surrogate evaluation criteria
In order to achieve RO3, the key step C of the surrogate development framework
was implemented to evaluate potential surrogates identified in the case study research
(phase I). The key outcome of this process as shown in Figure 7.4, is the selection of
first ranked surrogates for priority measurement, based on the ranking obtained from
the robust evaluation process against five surrogate evaluation criteria and analysis of
ranking by three cohorts of experts: practitioners, policy makers, and researchers.
C.1. Evaluation of potential surrogates against criteria
Three potential surrogates identified for each indicator that were found in at least
three of four case study locations (Table 5.7) were evaluated in this study. The
evaluation of surrogates implemented in this study is a robust process, since each of
the potential surrogates were evaluated against each of the surrogate evaluation criteria
using qualitative 1-5 Likert scale (From very good to very bad). In the literature,
resilience indicators are mostly evaluated using pair-wise comparisons of indicators,
without imposing set of evaluation criteria to evaluate each indicator (Alshehri et al.,
2015b; Orencio & Fujii, 2013) or to rank indicators across different case study areas
(Carone et al., 2018). Hence, the method of evaluation for each surrogate against each
criteria applied in this study extends the literature on evaluation methods used by
Alshehri et al. (2015b), Orencio and Fujii (2013), and Carone et al. (2018) in resilience
assessment by evaluating each surrogate against each surrogate evaluation criteria on
a qualitative scale.
Chapter 7: Synthesis of key findings 241
C.2. Rank the potential surrogates
The experts’ evaluation of potential surrogates against five surrogate evaluation
criteria was analysed using a multi-criteria decision analysis tool to rank the potential
surrogates. The final outcome by implementing key step C of the surrogate
development framework is the selection of first ranked surrogates for application.
(Figure 6.12). This study further found that the overall ranking of three potential
surrogates were mostly aligned with the ranking of experts from the policy making
and practitioner cohorts, as discussed in Chapter 6 for each of the target indicators.
Hence, the application of priority surrogates, which ranked first have wide practical
applicability in the assessment of target social resilience indicators at the community
and sub-national levels.
Further, the application of PROMETHEE as a multi-criteria decision making
method to rank potential surrogates also extends Alshehri et al. (2015b), Carone et al.
(2018), and Orencio and Fujii (2013) research on applying AHP applied to rank
resilience indicators by the use of qualitative Likert scale for evaluation of surrogates
in PROMETHEE.
7.4. Key step C and related outcomes to achieve RO3
Chapter 7: Synthesis of key findings 242
C.3. Select the optimum surrogates for application
The evaluation of surrogates in PROMETHEE resulted in a first ranked
surrogate (Figure 6.12) for priority assessment of each target social resilience
indicator. The five first ranked surrogates to assess social resilience are highly relevant
for practical application, since they were identified in at least three of four case study
locations in Phase I and ranked first in the evaluation in Phase II of the study. These
are listed below:
- I1-Social mobility: S*1 - Availability/accessibility of evacuation centres;
- I2-Social trust: S*2 - Effectiveness/performance of community-based
organisations;
- I3-Social competence: S*3 - Reaction to early warning as a learning from the
past;
- I4-Social equity for PwSN: S*4 - Effectiveness of social safety programs ; and
- I5-Social cultural beliefs: S*5 - Gender norms and culture of women.
The relevance and measurement protocols of the five first ranked surrogates to
advance the resilience assessment knowledge using surrogate approach are discussed
below.
7.3.1 The relevance and measurement protocols of first ranked surrogates for
assessing social resilience indicators
I1-Social mobility: S*1 - Availability/accessibility of evacuation centres
Two most important interconnected components of a disaster preparedness and
response system include evacuation centres and early warning systems (Sorensen &
Sorensen, 2007). A set of measurement protocols identified in the case study locations
(Phase I of this study) for surrogate - S*1 are provided in Section 5.1.5.
The availability of and access to evacuation centres are key decision making
factors for peoples’ mobility in a disaster situation (Bañgate et al., 2017), because the
degree of availability of evacuation centres and the level of awareness largely
influence the decision for evacuation and mobility in times of disasters. However, this
study found that the accessibility of the evacuation centres for PwSN as the priority
surrogate to assess social mobility. In most instances, the focus of measure is given for
demarcating evacuation centres in community maps as part of the disaster
preparedness plans (Wright & Johnston, 2010), but there has been lack of auditing of
Chapter 7: Synthesis of key findings 243
the evacuation centres to assess their suitability for use by People with Specific Needs
(PwSN). Hence, the finding extends the research by Wright and Johnston (2010) on
existing measures such as demarcating evacuation centres by the measure of
availability/accessibility of evacuation centres with facilities for PwSN (S*1), since the
mobility assistance in a disaster context should be prioritised for PwSN.
This study highlighted that some parts of the population may be disconnected
from the evacuation centres in a disaster situation, which makes the identification of
alternative routes an important social mobility measurement protocol. The
identification of alternative routes was done in evacuation transportation planning
(Campos et al., 2012). This study found that the identification of alternative evacuation
routes should be one of the key measurement protocols for assessing the accessibility
of evacuation centres. In the existent resilience frameworks, alternative evacuation
routes were assessed through arterial roads/km2 and distance to the nearest highway
using census data (Kotzee & Reyers, 2016; Parsons et al., 2016). These findings
contradicts the research by Kotzee and Reyers (2016) and Parsons et al. (2016) on the
existing social mobility measures such as arterial roads/km2 and distance to the nearest
highway by the identification of alternative routes to evacuation centres as a
measurement protocol for the surrogate - availability/accessibility of evacuation
centres (S*1).
I2-Social trust: S*2 - Effectiveness/performance of community-based
organisations
Community Based Organisations (CBOs) are one of the key social systems that
play an important role in enhancing resilience to disasters, more importantly in the
disaster preparedness phase. The involvement of CBOs in resilience building projects
provide an important measure of trust built in the community (Gin et al., 2017). A set
of measurement protocols identified in case study locations (Phase I of this study) for
surrogate - S*2 are provided in Section 5.2.5.
The increase in the involvement of CBOs in local disaster management work
improves the effectiveness of disaster response and recovery activities (Drennan &
Morrissey, 2019). This study highlighted that CBOs were faster to respond to address
immediate relief and recovery needs in disaster situations, as compared to the state
mechanisms which take time to respond due to bureaucratic hierarchy of decision
making. Hence, this study identified the importance of the disaster management
Chapter 7: Synthesis of key findings 244
activities by CBOs and their ability to mobilise resources to assess social trust in a
disaster context.
The assessment of social trust is more than just numbers of registered CBOs in
the community, as it should capture how those CBOs function in a community to build
trust and the extent to which they engage with the community in a disaster context
(Cutter, 2016). However, research by Cutter (2016) did not propose measurement
protocols for assessing the engagement of CBOs in disaster management work. Yoon
et al. (2016) measured social resilience using census data such as the number of
registered CBOs, their volunteer base, and past budget. The study findings extends the
research Yoon et al. (2016) and Cutter (2016) on assessing CBOs’ performance using
census-based measures by the new surrogate measures such as mapping of actively
functioning CBOs in the selected region, their past experiences in disaster management
work, resource allocation for disaster management activities, and the provision for
disaster management work in CBO constitutions.
I3-Social competence: S*3 - Reaction to early warning as a learning from the past
The reaction to disaster early warning provides an important and priority
measure of competencies of a community as a learning from past disaster experience.
Early warnings in disaster situations mostly fail due to the lack of effective social
processes in which early warning messages are poorly communicated (Kelman &
Glantz, 2014). A set of measurement protocols identified in case study locations (Phase
I of this study) for the surrogate - S*3 are provided in Section 5.3.5.
There were many instances in the past when people reacted to disaster early
warnings ineffectively and the real learning to face future disasters happens by false
reactions. In the case study areas, people have learnt lessons over the past years and
improved their understanding of early warning messages from their inappropriate
reactions to early warning. The improvements or lapses as to how the community
reacts to the disaster early warning messages can be measured to understand whether
the community has learned lessons from the past disaster experiences. Sharma and Patt
(2012) identified three different key elements related to early warning response: the
severity of the impact of past disaster experience; past experience with false early
warning alarms; and past evacuation experience including the quality of evacuation
centres. However, the effectiveness of early warning is mostly assessed by the
Chapter 7: Synthesis of key findings 245
availability of public awareness programmes/disaster drills in the existing resilience
frameworks (Joerin et al., 2014; Lorenz, 2013).
This study found that the assessment of reactions in past disaster early warning
instances and during drills provide a priority measure of communities’ ability to learn
lessons from the past disasters. When people participate in disaster drills and how they
react to disaster early warning messages during drills can be measured by the
improvements in early warning/evacuation drills and the trends in the participation of
people from most vulnerable areas. Further, the past real early warning instances and
the reaction of the public by the trend in number of people who reacted/evacuated
appropriately and trend in confirmation calls to disaster management centre are also
proposed as measurement protocol to assess reaction to early warning. These findings
extend Joerin et al. (2014) and Lorenz (2013) measures highlighted above on the
availability of public awareness programs/disaster drills. The new measures found in
this study include: the identification of early warning systems built after a disaster or
the improvements in existing early warning systems, the past real early warning
instances and the reaction of the public by number of people reacted appropriately, the
improvements in early warning/evacuation drills and trends in peoples’ participation,
trends in number of confirmation calls to disaster management centre after early
warning messages, and the number of people evacuated with and without official early
warning messages from local authorities.
I4-Social equity for PwSN: S*4 - Effectiveness of social safety programs
Adaptive social safety schemes such as targeting transfer of essential resources
to prepare for disasters provide not only short-term benefits, but largely contribute to
strengthen the resilience of the most vulnerable segment of the population (Béné et al.,
2012; Wu & Drolet, 2016). A set of measurement protocols identified in case study
locations (Phase I of this study) for surrogate - S*4 are provided in Section 5.4.5.
Social safety programs are also key processes for enhancing social support to the
most needy to promote self-recovery after disasters (IFRC, 2016). This study also
emphasised that the social safety programs ensure the right to priority assistance and
access to necessary resources for people who need special and utmost care in a society,
in times of a disaster. In disaster situations, social and cultural networks also serve as
social safety net mechanisms for people affected by disasters through the provision of
emergency food, shelter, and health assistance (USIOTWSP, 2007). In the existing
Chapter 7: Synthesis of key findings 246
social resilience frameworks, the diversity of available social assistance programs
targeting various groups was used as a measure for social support systems (Burton,
2015).
Although social safety programs are still centred on poverty reduction and social
wellbeing strategies, there has been an increasing importance given to social safety as
an integrated set of programs to address poverty, vulnerability, risk, and inequality
(Fiszbein et al., 2013). This study highlighted that the integration of disaster
preparedness and risk reduction assistance within longer-term safety programs is being
increasingly introduced, particularly for People with Specific Needs (PwSN). These
findings extend the research by Burton (2015) on assessing social support systems
through the measurement of availability of diverse social assistance programs targeting
various groups. The new measures to assess social support systems found in this study
include: the measure of social safety programs effectiveness through trend in the
inclusion of most vulnerable people in social safety program and the degree of disaster
preparedness integration within the social safety programs to assess the involvement
of people with specific needs as a social equity in a disaster context.
I5-Social cultural beliefs: S*5 - Gender norms and culture of women
The gender norms are important to understand local or cultural beliefs that may
hinder building resilience to disasters among other barriers such as race and social
class (Kapucu et al., 2013). For example, this study highlighted the mobility limitations
in public for women headed households due to cultural barriers in some communities,
which can reduce their resilience to disasters. A set of measurement protocols
identified in case study locations (Phase I of this study) for surrogate - S*5 are provided
in Section 5.5.5.
The disaster management strategy and programs should ensure gender equality
and cultural diversity, which is also an important measure of community inclusiveness.
The role of women in disaster related work is neglected due to cultural norms in some
communities (Lovell & Le Masson, 2014). The lack of women trained on critical
disaster management skills such as first aid was highlighted in this study as an
important concern in communities with certain cultural or faith practices that has a
very restricted role for women in public places. Many of the existing social resilience
frameworks limit the measure of gender to socio-demographic indicators such as the
percentage of female population (Parsons et al., 2016; Yoon et al., 2016) and Kotzee
Chapter 7: Synthesis of key findings 247
and Reyers (2016) used percentage of female labour as a measure of employment
equity in a disaster context.
The interaction between culture, social networks, and personal attributes of
women play a key role in determining social resilience in communities that prioritize
the cultural and religious norms and practices (Cottrell, 2006). For example, women,
who play a complementary role rather than an independent role in some contexts, are
one of the social segments that are highly exposed to disasters due to many gender
specific vulnerabilities such as cultural restrictions on mobility and decision making
powers (Alam & Rahman, 2014). Further, this study found that the absence of women
volunteer networks/organisations working in disaster management projects and the
lack of women population employed in critical jobs such as police and emergency
services are key challenges in disaster management work. These findings contradict
the research by Kotzee and Reyers (2016), Yoon et al. (2016), and Parsons et al. (2016)
on assessing gender related indicators through socio-demographic indicators such as
the percentage of female population and percentage of female labour, by measuring
gender norms in a disaster context through more specific social and cultural processes
that support or hinder resilience. The new surrogate measures proposed in this study
include, the number of women volunteers trained on first aid, swimming and other
critical disaster management skills, extent of women volunteer networks/organisations
working in disaster management projects, and the percentage of the female population
employed against the female population employed in critical jobs such as police and
emergency health services.
REVISIONS TO THE CONCEPTUAL SURROGATE DEVELOPMENT
FRAMEWORK
The revisions to the conceptual surrogate development framework (See Figure
3.6) are presented in this section, based on the findings and learnings from testing of
three key steps of conceptual surrogate development framework as explained in the
preceding sections. The integrated surrogate development framework (Figure 7.5) is
the main contribution to knowledge from this study, since it is a refined version based
on a robust testing of the conceptual framework developed through the review of
literature. The development of this framework answers the key research question of
this study, “How can key social resilience indicators in a disaster context be measured
using surrogate approach?”
Chapter 7: Synthesis of key findings 248
Figure 7.5. An integrated (revised) surrogate development framework for resilience assessment in disaster management
Chapter 7: Synthesis of key findings 249
7.4.1 An integrated surrogate development framework in disaster management
for future application
All sub-steps and key elements remain largely the same with some minor
changes in the integrated framework (Figure 7.5), compared to the conceptual
framework (Figure 3.6). The logical order of one sub-step and some key elements
within sub-steps are revised in the integrated framework, as discussed below.
(1) Key step A: Selection of social resilience indicators for surrogate
development:
There are no changes in the sub-steps of ‘key step A’. However, the key elements
within both sub-steps are included in the integrated surrogate development framework.
A.1. Identify key social resilience indicators:
Select the context: The context of social resilience measurement in a disaster context
needs to be decided as boundary conditions within which the social resilience
measurement becomes valid. In the tested framework, setting the context was part of
key step B in this research, since the data collection was done after selecting the key
indicators from the literature review. However, the context needs to be decided if the
surrogates are explored in a particular context, to make them applicable in the same
context.
The boundary conditions include: geography, disaster type, and target group. Although
some resilience indicators are more generic, many of the social resilience measures are
context-specific phenomena (Mitchell & Harris, 2012),. Hence, setting the context can
be two types: a) if there is a need for a specific measure to be applied in the local
context, the boundary can be set as the type of disaster exposure in the region, and
specific target group; or b) if the surrogate approach is applied to generic indicators,
multi-hazard context and common target group can be used, which can have a wide
applicability.
Select key indicators relevant to the context to develop surrogates: The critical
review of social resilience literature identified many process-oriented indicators,
which were often neglected in the existing resilience assessment frameworks. They
were structured in five social resilience dimensions in a ‘5S’ social resilience
framework (Saja et al., 2018). This framework or any other social resilience
framework that can guide to methodically identify key social resilience indicators most
relevant in the context of measurement to apply the surrogate approach can be used.
Chapter 7: Synthesis of key findings 250
A.2. Decision for surrogate approach:
Once the social resilience indicators are selected, the decision for surrogate
approach needs to be made. The decision for the surrogate approach is based on three
surrogate decision criteria applied in this study:
1. Indicators should be process-oriented resilience indicators that are not static
(dynamic, which frequently change overtime).
2. Indicators are complex for conceptualisation and cannot be easily measured
quantitatively.
3. The existing measures using indirect methods do not provide an adequate measure
of the target indicator.
The inclusion of three surrogate decision criteria provides a uniform approach
for the users to make a methodical decision regarding the surrogate approach. This
could be either done through literature search or from reports or through consultation
with key disaster management experts in the selected study area.
(2) Key step B: Identification of potential surrogates for the selected key
indicators:
Key step B was revised from three to two sub-steps. The sub-step B.3 –
‘determining the protocols for surrogate measurement’ in the original framework is
moved to sub-component C.3 in the revised framework. Since the protocols for
surrogate measurement are only needed for the final selected surrogates, it was not
necessary to determine surrogate measurement protocols for all the potential
surrogates at the time of identification of potential surrogates.
There is no change in sub-step B.1. However, for sub-step B.2 in Figure 7.5, two
key elements in the tested conceptual framework were the strength and sensitivity of
the surrogacy relationship. At the initial stage of identifying potential surrogates for
measuring social resilience indicators, establishing surrogacy relationship (strength
and sensitivity) through qualitative explanation can be done, as tested in this study.
The qualitative interpretation of surrogacy relationship helps to elaborate the different
dynamics of its relationship, which is difficult to do using quantitative methods.
However, the evaluation of strength and sensitivity of the surrogacy relationship are
considered, when the potential surrogates are evaluated (Key step C) against the
criteria – ‘accuracy’ and ‘time-sensitivity’. The ‘accuracy’ criteria assesses the degree
Chapter 7: Synthesis of key findings 251
of accuracy of the surrogate for the target measure, which considers how strongly the
surrogate is connected to the target. The ‘time-sensitivity’ criteria assesses the change
of surrogate over time (in disaster preparedness, response, and recovery phases).
The robustness of the strength and sensitivity of the surrogacy relationship can
be increased using quantitative approaches such as statistical and correlation analysis
methods (Ziyath et al., 2013). The surrogate relationship with the target indicator of
measure in environmental science is established mostly through statistical inferences
and measurement methods largely used in sampling approaches, as discussed in
Section 7.2 (Athey et al., 2016). Similar quantitative approaches to establish surrogacy
relationship can also be applied in resilience measurement in a disaster context.
However, in the context of social resilience assessment, quantitative findings also need
to be interpreted qualitatively, since qualitative explanation can increase the richness
of understanding the surrogacy relationship.
(3) Key step C: Selection of optimum surrogates for application in a disaster
context:
In this key step, the important addition is sub-step C.3 – protocols for surrogate
measurement, which was moved from the key step B as explained in the above section.
There is no change in sub-step C.1 from the tested framework for selecting optimum
surrogates. However, the sub-step C.3 in the tested framework is merged as part of
sub-step C.2 in the integrated (revised) framework. Since the selection of optimum
surrogates is an end result of ranking surrogates, it is more suitable to combine the
selection process with the sub-step - ranking of surrogates (C.3) (Figure 7.5).
Further to the application of the integrated surrogate development framework to
advance the surrogate approach research in disaster management, it can be applied by
practitioners at the local and sub-national levels with appropriate adaptations using
participatory methods. For example, the potential surrogates can be identified using
focus groups or participatory workshops with disaster management
stakeholders/committees. The evaluation of surrogates to select the final set of
surrogates for application can be done by participatory multi-criteria decision making
tools such as pair-wise comparisons. This is a one-off process and final set of
surrogates can be regularly updated to continuously monitor the progress of social
resilience indicators.
Chapter 8: Conclusions and recommendations for future research 252
Chapter 8: Conclusions and
recommendations for future research
This chapter contains four key sections: Section 8.1 presents the achievement of
three study objectives aligned with the three key steps of the surrogate development
framework (A to C). The next section (Section 8.2) outlines how this study addresses
the key research question. The following sections present the study contribution to
theory, policy and practice (Section 8.3) and study limitations (Section 8.4). The final
section provides key recommendations for future research (Section 8.5).
ACHIEVEMENT OF RESEARCH OBJECTIVES ONE TO THREE
The schematic diagram in Figure 8.1 shows the achievement of research
objectives in each key step of surrogate development framework (A to C), aligned with
each Research Objective (RO1 to RO3). The achievement of each research objective
as shown in Figure 8.1 is discussed below.
Research Objective one (RO1): To select key social resilience indicators that
require surrogate approach by developing an adaptive and inclusive social
resilience framework
The key step A of the surrogate development framework for selecting resilience
indicators to apply the surrogate approach was operationalised in the literature review
and research design phase of this study to achieve RO1. A critical review of social
resilience frameworks found that there was no systematic approach to identify key
indicators to apply the surrogate approach. This review resulted in a set of key social
resilience indicators, which were then structured in an inclusive and adaptive ‘5S’
social resilience framework (Figure 2.5) to guide the selection of social resilience
indicators to develop the surrogate approach. Further, three surrogate decision criteria
were found to select social resilience indicators to apply surrogate approach: the
indicators should be process-oriented resilience indicators that are not static indicators;
indicators are complex for conceptualisation and cannot be easily measured
quantitatively; and the existing measures using indirect methods do not provide an
adequate measure of the target indicator. Based on the surrogate decision criteria, five
indicators were selected from the ‘5S’ framework to develop the surrogate approach.
Chapter 8: Conclusions and recommendations for future research 253
Figure 8.1. Overall schematic showing achievement of research objectives in each key step of surrogate
development to respond to the key RQ
RO – Research Objective RQ – Research Question
Chapter 8: Conclusions and recommendations for future research 254
Research objective two (RO2): To identify potential surrogates to measure key
social resilience indicators in disaster management
The key step B of the surrogate development framework was operationalised to
identify potential surrogates (RO2) using a case study approach in phase I of this study.
The analysis of case study interview data from disaster management experts
(Practitioners and policy makers) revealed six potential surrogates for each of the
social resilience indicators (Table 5.6) and a set of measurement protocols for each
surrogate (Sections 5.1.5 - 5.5.5). The potential surrogates found in this study provide
a significant contribution to knowledge on resilience assessment (as explained in
Section 7.2), since many of the existing measures were based on census data which do
not provide an adequate assessment of resilience. However, some of the potential
surrogates were only identified in one or two of the four case study units. Among six
potential surrogates, three surrogates were found across multiple case studies for each
of the five social resilience indicators. Most of these surrogates and their measurement
protocols contribute as new measures to extend the existing resilience measures in the
literature. Further, some surrogates for indicators such as social trust and equity for
people with specific needs contradict existing measures proposed or applied in the
social resilience assessment literature in disaster management. Three potential
surrogates found in multiple case study units which have high validity were chosen for
further evaluation and ranking in phase II to select the optimum surrogate for
application.
Research objective three (RO3): To evaluate and select optimum surrogates for
application by ranking the potential surrogates against surrogate evaluation
criteria
The final key step C of the surrogate framework to select optimum surrogates
for application in a disaster context (RO3), was operationalised in phase II of this
research using an online survey with disaster management experts ranging from
research, policy and practice cohorts. The five first ranked surrogates (Figure 6.12)
were found as the most robust surrogates for application, as explained in Section 7.3,
include: availability/accessibility of evacuation centres to assess social mobility;
effectiveness/performance of community-based organisations to assess social trust;
reaction to early warning as a learning from the past to assess social competence;
effectiveness of social safety programs to assess social equity for PwSN; and gender
norms and culture of women to assess social cultural beliefs. The analysis also showed
Chapter 8: Conclusions and recommendations for future research 255
that most of the first ranked surrogates were also the preference of highly experienced
experts from the cohort of practitioners and policy makers, and their ranking mostly
aligned with overall ranking of surrogates (Section 6.4).
The application of three key steps of surrogate development framework yielded
priority surrogates for application to assess social resilience to disasters, which is the
final outcome by synthesising the findings from three research objectives, achieved
through a robust multi-phase mixed method sequential research strategy. The findings
from this synthesis addressed the key knowledge gap on the need for a method to
identify and select priority surrogates using a set of measurement protocols for
assessing social resilience indicators (See Sections 7.2 and 7.3), which is a new
contribution to the resilience assessment knowledge in disaster management.
ADDRESSING THE KEY RESEARCH QUESTION AND AIM
The key Research Question (RQ) of this study is - ‘how can key social resilience
indicators in a disaster context be measured using surrogate approach?’ as described
in Section 1.5. To investigate the above key RQ, the main aim of this research was to
develop an approach for conceptualising, identifying, and evaluating surrogates to
assess social resilience indicators in a disaster context.
A conceptual surrogate development framework for assessing social resilience
in disaster management (See Figure 3.6) was created from the review of surrogate
approach literature in environmental science and tested through a multi-phase, mixed-
method research in this study. An integrated surrogate development framework that
was created from the lessons of testing the conceptual framework for future
application, is the main contribution to the knowledge in resilience assessment in
disaster management. The surrogate approach developed in this research can address
the challenges in resilience assessment by identifying a set of potential surrogates. The
proposed potential surrogates can be measured by accessing the most updated
administrative data at the community and sub-national levels and participatory
methods with key disaster management stakeholders as explained in Chapter 5. The
results from the assessment of social resilience indicators using the surrogate approach
will help to devise comprehensive action-oriented resilience decision making. Further,
the resilience measurement using surrogates will assist to regularly update and monitor
Chapter 8: Conclusions and recommendations for future research 256
social resilience status, since they will use regularly updated administrative data
available at the local or sub-national levels.
The surrogate development framework provides a new method to assess
resilience indicators. This allows continuous monitoring of resilience and to devise
appropriate strategies and plans for resilience enhancement of communities to
emerging disasters. The creation of the surrogate development framework and testing
it through a rigourous research method in this study achieved the research aim, which
was to ‘develop an approach for conceptualising, identifying, and evaluating
surrogates to assess social resilience indicators in a disaster context’.
STUDY CONTRIBUTIONS TO KNOWLEDGE AND PRACTICE
8.3.1 Contribution to knowledge
This research makes three innovative contributions to knowledge with respect to
resilience assessment in a disaster context, by developing and operationalising the
surrogate development framework to assess social resilience.
Firstly, the integrated (revised) surrogate development framework (Figure 7.5)
to conceptualise, identify, and select surrogates to assess social resilience indicators
created in this study is innovative. It is the key contribution to resilience assessment
knowledge, since a framework to apply surrogate approach does not currently exist in
disaster management literature. This framework can be used in any context by disaster
management stakeholders to select surrogates for real world application. The
integrated surrogate development framework will address the knowledge gap in
resilience measurement methods in disaster management.
Secondly, a set of potential surrogates and their measurement protocols
(Sections 5.1.5 - 5.5.5) that were developed through an exploratory multiple case study
research at the local level has contributed to resilience assessment knowledge in
disaster management. These surrogates have wide applicability with sufficient
contextualisation in any urban context, since the selected social resilience indicators
such as social mobility, social trust, community competence, social equity, and social
cultural beliefs are important and common in many disaster and geographical contexts.
Thirdly, the first ranked surrogates were selected through a robust multi-phase
process of identification and evaluation of potential surrogates as part of a sequential
exploratory research design process in this study contribute to the priority resilience
Chapter 8: Conclusions and recommendations for future research 257
assessment knowledge. The broader applicability of first ranked surrogates to the
disaster management literature was ensured by consulting disaster management
experts beyond Sri Lanka in the second phase of this research through an online survey.
8.3.2 Contribution to policy and practice
The findings from this research contributes to the disaster management policy
and practice in three ways.
Firstly, for policy makers and practitioners, the first ranked surrogates (Figure
6.12) can be a starting point for further consultation with disaster management
stakeholders at the local level for practical application to assess social resilience
indicators.
Secondly, a method to measure potential surrogates (measurement protocols)
proposed in this study has real-world application to undertake social resilience
assessment in disaster management. The practitioners and policy makers at the
community and sub-national levels can utilise the proposed surrogate measurement
protocols (Sections 5.1.5 - 5.5.5) to assess current status of resilience and plan
activities needed for resilience enhancement, based on the assessment results. The
surrogate approach will assist practitioners to assess resilience at the local level, since
they use locally available, frequently updated, and easily accessible administrative
data.
Thirdly, the overall contribution is the introduction of the surrogate approach in
disaster management with the aim to assess social resilience locally. The integrated
surrogate development framework was proposed by testing it through consultation
with practitioners and policy makers working in different levels from community to
national levels. Hence, it can be applied in any local context with appropriate
participatory tools by engaging key disaster management stakeholders to select the
required surrogates for application.
Chapter 8: Conclusions and recommendations for future research 258
STUDY LIMITATIONS
The findings presented in this study can be applicable to any context, since all
the social resilience indicators selected are generic to different contexts. However, a
number of study limitations need to be considered.
1. This study was conducted in a specific socio-economic and cultural context in a
developing country. For example, the study area was largely dominated by Muslims
and Hindu population (minority populations in Sri Lanka), which have influenced
some findings such as in the case of social beliefs (religious and cultural beliefs).
Hence, the application of these findings in a different cultural setting require proper
contextualisation of socio-economic and cultural characteristics.
2. This study was conducted in the Eastern coastal region of Sri Lanka, which is prone
to floods, cyclone, and Tsunami. Although many findings are common and can be
applicable to any disaster type, the application of some of findings to other disaster
types need to consider specific characteristics of the disaster.
Chapter 8: Conclusions and recommendations for future research 259
KEY RECOMMENDATIONS FOR FUTURE RESEARCH
The following key recommendations are proposed for future research studies in
assessing social resilience to disasters.
1. Advancing disaster resilience measurement research through the surrogate
approach in different contexts:
The surrogate approach in this study was applied in an urban context in a developing
country. Future research can test the surrogate framework to assess social resilience in
rural contexts, and in developed countries in order to develop a generic approach to
any context. Future research contexts also can include different socio-cultural settings
such as multi-cultural and marginalised communities and different disaster types such
as bush fires and volcanos.
2. Application of first ranked surrogates to assess social resilience:
Future research needs to apply first ranked surrogates found in this study and improve
it based on lessons from applying it in disaster management practice.
3. Application of surrogate measurement protocols:
Future research need to test the application of a set of surrogate measurement protocols
found in this study for each of the surrogates in order to measure the target resilience
indicator in different contexts to further advance the resilience assessment.
4. Developing a composite social resilience surrogate model:
A composite surrogate model is a conceptual mapping of surrogates with multiple
indicators and final outcomes. The potential surrogates identified in this study can be
applied in future research programs to develop composite surrogate models that will
better reflect the complex inter-linkages between surrogates.
5. Quantitative methods to establish surrogate and target indicator relationship and
surrogate measurement protocols
This research established the relationship of surrogates with target indicators and
surrogate measurement protocols qualitatively. Future research can test quantitative
methods to establish surrogate relationships and measurement protocols.
Bibliography 260
Bibliography
Abenayake, C., Yoshiki, M., Marasinghe, A., Takashi, Y., & Masahiro, I. (2016).
Applicability of extra-local methods for assessing community resilience to
disasters: A case of Sri Lanka. Journal of Environmental Assessment Policy
and Management, 18(02), 1650010.
Adger, W. N. (2000). Social and ecological resilience: are they related? PROGRESS
IN HUMAN GEOGRAPHY, 24(3), 347-364.
Adger, W. N. (2003). Social capital, collective action, and adaptation to climate
change. Economic geography, 79(4), 387-404.
Adger, W. N., Hughes, T. P., Folke, C., Carpenter, S. R., & Rockström, J. (2005).
Social-ecological resilience to coastal disasters. Science, 309(5737), 1036-
1039.
Ahern, J. (2011). From fail-safe to safe-to-fail: Sustainability and resilience in the
new urban world. Landscape and Urban Planning, 100(4), 341-343.
Ainuddin, S., & Routray, J. K. (2012). Earthquake hazards and community resilience
in Baluchistan. Natural Hazards, 63(2), 909-937. doi:10.1007/s11069-012-
0201-x
Ainuddin, S., Routray, J. K., & Ainuddin, S. (2015). Operational indicators for
assessing vulnerability and resilience in the context of natural hazards and
disasters. International Journal of Risk Assessment and Management, 18(1),
66-88. doi:10.1504/IJRAM.2015.068135
Alam, K., & Rahman, M. H. (2014). Women in natural disasters: a case study from
southern coastal region of Bangladesh. International Journal of Disaster Risk
Reduction, 8, 68-82.
Alasuutari, P., Bickman, L., & Brannen, J. (2008). The SAGE handbook of social
research methods: Sage.
Alasuutari, P., Bickman, L. & Brannen, J. (2008). Focus groups. In J. Smithson
(Ed.), The SAGE handbook of social research methods (pp. 357-370).
London: SAGE Publications Ltd.
Alawiyah, T., Bell, H., Pyles, L., & Runnels, R. C. (2011). Spirituality and faith-
based interventions: Pathways to disaster resilience for African American
Hurricane Katrina survivors. Journal of Religion & Spirituality in Social
Work: Social Thought, 30(3), 294-319.
Aldrich, D. P., & Meyer, M. A. (2014a). Social Capital and Community Resilience.
American Behavioral Scientist, 59(2), 254-269.
doi:10.1177/0002764214550299
Aldrich, D. P., & Meyer, M. A. (2014b). Social capital and community resilience.
American Behavioral Scientist, 0002764214550299.
Aldrich, D. P., & Meyer, M. A. (2015). Social Capital and Community Resilience.
American Behavioral Scientist, 59(2), 254-269.
doi:10.1177/0002764214550299
Aldunce, P., Beilin, R., Howden, M., & Handmer, J. (2015). Resilience for disaster
risk management in a changing climate: Practitioners’ frames and practices.
Global Environmental Change, 30, 1-11.
doi:http://dx.doi.org/10.1016/j.gloenvcha.2014.10.010
Bibliography 261
Alexander, D. E. (2013). Resilience and disaster risk reduction: an etymological
journey. Natural Hazards and Earth System Sciences, 13(11), 2707-2716.
Alshehri, S. A., Rezgui, Y., & Li, H. (2015a). Delphi-based consensus study into a
framework of community resilience to disaster. Natural Hazards, 75(3),
2221-2245. doi:10.1007/s11069-014-1423-x
Alshehri, S. A., Rezgui, Y., & Li, H. (2015b). Disaster community resilience
assessment method: a consensus-based Delphi and AHP approach. Natural
Hazards, 78(1), 395-416. doi:10.1007/s11069-015-1719-5
Angus, D., Rintel, S., & Wiles, J. (2013). Making sense of big text: a visual-first
approach for analysing text data using Leximancer and Discursis.
International Journal of Social Research Methodology, 16(3), 261-267.
Arbon, P., Steenkamp, M., Cornell, V., Cusack, L., & Gebbie, K. (2016). Measuring
disaster resilience in communities and households. International Journal of
Disaster Resilience in the Built Environment, 7(2), 201-215.
doi:10.1108/ijdrbe-03-2015-0008
Aronson, J. K. (2005). Biomarkers and surrogate endpoints. British journal of
clinical pharmacology, 59(5), 491-494.
Asadabadi, M. R., Chang, E., & Saberi, M. (2019). Are MCDM Methods Useful? A
Critical Review of Analytic Hierarchy Process (AHP) and Analytic Network
Process (ANP). Cogent Engineering(just-accepted), 1623153.
Asadzadeh, A., Kötter, T., Salehi, P., & Birkmann, J. (2017). Operationalizing a
concept: The systematic review of composite indicator building for
measuring community disaster resilience. International Journal of Disaster
Risk Reduction.
Asher, M. J., Croke, B. F., Jakeman, A. J., & Peeters, L. J. (2015). A review of
surrogate models and their application to groundwater modeling. Water
Resources Research, 51(8), 5957-5973.
Athey, S., Chetty, R., Imbens, G., & Kang, H. (2016). Estimating treatment effects
using multiple surrogates: The role of the surrogate score and the surrogate
index. arXiv preprint arXiv:1603.09326.
Axinn, W. G., & Pearce, L. D. (2006). Mixed method data collection strategies:
Cambridge University Press.
Baker, S. G. (2005). A simple meta-analytic approach for using a binary surrogate
endpoint to predict the effect of intervention on true endpoint. Biostatistics,
7(1), 58-70. doi:10.1093/biostatistics/kxi040
Bañgate, J., Dugdale, J., Adam, C., & Beck, E. (2017). A review on the influence of
social attachment on human mobility during crises. Paper presented at the
T2-Analytical Modelling and Simulation Proceedings of the 14th ISCRAM
Conference, Albi, France.
Barton, P. S., Pierson, J. C., Westgate, M. J., Lane, P. W., & Lindenmayer, D. B.
(2015). Learning from clinical medicine to improve the use of surrogates in
ecology. Oikos, 124(4), 391-398.
Beccari, B. (2016). A Comparative Analysis of Disaster Risk, Vulnerability and
Resilience Composite Indicators. PLoS Currents, 8. Retrieved from
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4807925/
Becker, D., Schneiderbauer, S., Forrester, J. M., & Pedoth, L. (2015). Guidelines for
development of indicators, indicator systems and provide challenges: CRED,
Louvain.
Begum, D. (2008). Disaster Management in Bangladesh: Addressing women's needs.
BRAC University.
Bibliography 262
Bell, E., Bryman, A., & Harley, B. (2018). Business research methods: Oxford
university press.
Béné, C., Wood, R. G., Newsham, A., & Davies, M. (2012). Resilience: New Utopia
or New Tyranny? Reflection about the Potentials and Limits of the Concept
of Resilience in Relation to Vulnerability Reduction Programmes. IDS
Working Papers, 2012(405), 1-61. doi:10.1111/j.2040-0209.2012.00405.x
Bennett, E., Cumming, G., & Peterson, G. (2005). A systems model approach to
determining resilience surrogates for case studies. Ecosystems, 8(8), 945-957.
doi:10.1007/s10021-005-0141-3
Berkes, F., & Seixas, C. S. (2005). Building resilience in lagoon social–ecological
systems: a local-level perspective. Ecosystems, 8(8), 967-974.
doi:10.1007/s10021-005-0140-4
Bion, W. R., Farr, R. M., Glaser, B. G., & Strauss, A. L. (2000). Qualitative
Researching with Text, Image and Sound. London: SAGE Publications Ltd.
Retrieved from http://methods.sagepub.com/book/qualitative-researching-
with-text-image-and-sound. doi:10.4135/9781849209731
Birkmann, J. (2006). Measuring vulnerability to natural hazards: towards disaster
resilient societies.
Birkmann, J. (2013). Data, indicators and criteria for measuring vulnerability:
Theoretical bases and requirements. In J. Birkmann (Ed.), Measuring
vulnerability to natural hazards: Towards disaster resilient societies (second
edition). United Nations University
Birnbaum, M. L., Daily, E. K., O'Rourke, A. P., & Loretti, A. (2016). Research and
Evaluations of the Health Aspects of Disasters, Part IX: Risk-Reduction
Framework. Prehospital and disaster medicine, 31(3), 309-325.
doi:10.1017/S1049023X16000352
Blau, P. M. (1977). A Macrosociological Theory of Social Structure. American
Journal of Sociology, 83(1), 26-54. Retrieved from
http://www.jstor.org.ezp01.library.qut.edu.au/stable/2777762
Boeije, H. (2009). Analysis in qualitative research: Sage publications.
Boin, A., Comfort, L. K., & Demchak, C. C. (2010). The rise of resilience.
Designing resilience: Preparing for extreme events, 1-12.
Brans, J.-P., & De Smet, Y. (2016). PROMETHEE Methods. In S. Greco, M.
Ehrgott, & J. R. Figueira (Eds.), Multiple Criteria Decision Analysis: State of
the Art Surveys (pp. 187-219). New York, NY: Springer New York.
Brinkhoff, P. (2011). Multi-criteria analysis for assessing sustainability of remedial
actions-applications in contaminated land development. Retrieved from
Brown, C., Shaker, R. R., & Das, R. (2018). A review of approaches for monitoring
and evaluation of urban climate resilience initiatives. Environment,
Development and Sustainability, 20(1), 23-40. doi:10.1007/s10668-016-9891-
7
Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O'Rourke, T. D., Reinhorn, A.
M., Shinozuka, M., Tierney, K., Wallace, W. A., & von Winterfeldt, D.
(2003). A framework to quantitatively assess and enhance the seismic
resilience of communities. Earthquake spectra, 19(4), 733-752.
doi:10.1193/1.1623497
Bryman, A. (2015). Social research methods: Oxford university press.
Burton, C. G. (2015). A Validation of Metrics for Community Resilience to Natural
Hazards and Disasters Using the Recovery from Hurricane Katrina as a Case
Bibliography 263
Study. Annals of the Association of American Geographers, 105(1), 67-86.
doi:10.1080/00045608.2014.960039
Cadag, J. R. D., & Gaillard, J.-C. (2012). Integrating knowledge and actions in
disaster risk reduction: the contribution of participatory mapping. Area,
44(1), 100-109.
Cai, H., Lam, N. S., Qiang, Y., Zou, L., Correll, R. M., & Mihunov, V. (2018). A
synthesis of disaster resilience measurement methods and indices.
International Journal of Disaster Risk Reduction, 31, 844-855.
Campos, V., Bandeira, R., & Bandeira, A. (2012). A method for evacuation route
planning in disaster situations. Procedia-Social and Behavioral Sciences, 54,
503-512.
Carone, M. T., Marincioni, F., & Romagnoli, F. (2018). Use of multi-criteria
decision analysis to define social resilience to disaster: the case of the EU
LIFE PRIMES project. Energy Procedia, 147, 166-174.
Carpenter, S. R., Westley, F., & Turner, M. G. (2005). Surrogates for resilience of
social–ecological systems. Ecosystems, 8(8), 941-944. doi:10.1007/s10021-
005-0170-y
Chandra, A., Williams, M., Plough, A., Stayton, A., Wells, K. B., Horta, M., & Tang,
J. (2013). Getting actionable about community resilience: The Los Angeles
county community disaster resilience project. American Journal of Public
Health, 103(7), 1181-1189. doi:10.2105/AJPH.2013.301270
Cinelli, M., Coles, S. R., & Kirwan, K. (2014). Analysis of the potentials of multi
criteria decision analysis methods to conduct sustainability assessment.
Ecological Indicators, 46, 138-148.
Cottrell, A. (2006). Weathering the strom: Women’s prepareness as a form of
resilience to weather-related hazards in Northern Australia Disaster
resilience: An integrated approach (pp. 128-142): Charles C. Thomas
Publisher Ltd.
Cox, R. S., & Hamlen, M. (2015). Community Disaster Resilience and the Rural
Resilience Index. American Behavioral Scientist, 59(2), 220-237.
doi:10.1177/0002764214550297
CRED. (2018). Economic Losses, Poverty & Disasters 1998-2017 Retrieved from
www.cred.be,. www.cred.be,
CRED. (2019a). 2018 REVIEW OF DISASTER EVENTS Retrieved from
https://www.cred.be/2018-review-disaster-events. from CRED and UNISDR
https://www.cred.be/2018-review-disaster-events
CRED. (2019b). Natural Disasters 2018. Retrieved from Brussels:
https://emdat.be/sites/default/files/adsr_2018.pdf
Creswell, J. W., & Clark, V. L. P. (2007). Designing and conducting mixed methods
research (2nd edition ed.): SAGE.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative,
and mixed methods approaches: Sage publications.
Cruzes, D. S., & Dyba, T. (2011). Recommended steps for thematic synthesis in
software engineering. Paper presented at the Empirical Software Engineering
and Measurement (ESEM), 2011 International Symposium on.
Cruzes, D. S., Dybå, T., Runeson, P., & Höst, M. (2015). Case studies synthesis: a
thematic, cross-case, and narrative synthesis worked example. Empirical
Software Engineering, 20(6), 1634-1665.
Bibliography 264
Custance, J., & Hillier, H. (1998). Statistical issues in developing indicators of
sustainable development. Journal of the Royal Statistical Society: Series A
(Statistics in Society), 161(3), 281-290.
Cutter, S. L. (2016). The landscape of disaster resilience indicators in the USA.
Natural Hazards, 80(2), 741-758. doi:10.1007/s11069-015-1993-2
Cutter, S. L., Ash, K. D., & Emrich, C. T. (2014). The geographies of community
disaster resilience. Global Environmental Change, 29, 65-77.
doi:http://dx.doi.org/10.1016/j.gloenvcha.2014.08.005
Cutter, S. L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., & Webb, J.
(2008). A place-based model for understanding community resilience to
natural disasters. Global Environmental Change, 18(4), 598-606.
doi:http://dx.doi.org/10.1016/j.gloenvcha.2008.07.013
Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2003). Social Vulnerability to
Environmental Hazards*. Social Science Quarterly, 84(2), 242-261.
doi:10.1111/1540-6237.8402002
Cutter, S. L., Burton, C. G., & Emrich, C. T. (2010). Disaster resilience indicators for
benchmarking baseline conditions. Journal of Homeland Security and
Emergency Management, 7(1), 51. doi:10.2202/1547-7355.1732
Davies, J. (2010). Preparation and process of qualitative interviews and focus groups.
Practical research and evaluation: A start-to-finish guide for practitioners,
126-144.
Davis, C. (2016). Focus groups: Applying communication theory through design,
facilitation, and analysis: Routledge.
De Ruyter, K. (1996). Focus versus nominal group interviews: a comparative
analysis. Marketing Intelligence & Planning, 14(6), 44-50.
DiCicco‐Bloom, B., & Crabtree, B. F. (2006). The qualitative research interview.
Medical education, 40(4), 314-321.
Djalante, R., & Thomalla, F. (2011). Community Resilience to Natural Hazards and
Climate Change: A Review of Definitions and Operational Frameworks.
Asian Journal of Environment and Disaster Management, 3(3).
doi:10.3850/S1793924011000952
Donnelly, A., Jones, M., O'Mahony, T., & Byrne, G. (2007). Selecting
environmental indicator for use in strategic environmental assessment.
Environmental Impact Assessment Review, 27(2), 161-175.
Doorn, N. (2017). Resilience indicators: opportunities for including distributive
justice concerns in disaster management. Journal of risk research, 20(6), 711-
731.
Drennan, L., & Morrissey, L. (2019). Resilience policy in practice—Surveying the
role of community based organisations in local disaster management. Local
Government Studies, 45(3), 328-349.
EC. (2015). Indicators for sustainable cities. In-depth Report 12. . Retrieved from
Produced for the European Commission DG Environment by the Science
Communication Unit, UWE, Bristol. : Available at:
http://ec.europa.eu/science-environment-policy
Eckstein, D. (2018). Global climate risk index 2018. A briefing paper. Retrieved
from
https://germanwatch.org/sites/germanwatch.org/files/Global%20Climate%20
Risk%20Index%202019_2.pdf
Eiser, J. R., Bostrom, A., Burton, I., Johnston, D. M., McClure, J., Paton, D., Van
Der Pligt, J., & White, M. P. (2012). Risk interpretation and action: A
Bibliography 265
conceptual framework for responses to natural hazards. International Journal
of Disaster Risk Reduction, 1, 5-16.
Enarson, E. (1998). Through women’s eyes: A gendered research agenda for disaster
social science. Disasters, 22(2), 157-173.
Endress, M. (2015). The social constructedness of resilience. Social Sciences, 4(3),
533-545.
Faifua, D. (2014). The key informant technique in qualitative research: SAGE
Publications, Ltd.
FAO. (2008). Food Security Information for Action , Vulnerability, Lesson 3 -
Vulnerability Indicators
Fernández, N. G. (2013). The management of missing values in PROMETHEE
methods.
Fiszbein, A., Kanbur, R., & Yemtsov, R. (2013). Social protection, poverty and the
post-2015 agenda: The World Bank.
Fleming, T. R., & Powers, J. H. (2012). Biomarkers and surrogate endpoints in
clinical trials. Statistics in medicine, 31(25), 2973-2984.
Flick, U. (2014). An introduction to qualitative research (5th ed.). London: Sage.
Fontana, A., & Prokos, A. H. (2016). The interview: From formal to postmodern:
Routledge.
Fothergill, A., & Peek, L. A. (2004). Poverty and disasters in the United States: A
review of recent sociological findings. Natural Hazards, 32(1), 89-110.
Frailing, K., & Harper, D. W. (2017). The Resilience of Communities Toward a
Criminology of Disaster: What We Know and What We Need to Find Out (pp.
167-193). New York: Palgrave Macmillan US.
Frazier, T. G., Thompson, C. M., Dezzani, R. J., & Butsick, D. (2013). Spatial and
temporal quantification of resilience at the community scale. Applied
Geography, 42, 95-107. doi:10.1016/j.apgeog.2013.05.004
Gin, J. L., Eisner, R. K., Der-Martirosian, C., Kranke, D., & Dobalian, A. (2017).
Preparedness is a marathon, not a sprint: A tiered maturity model for
assessing preparedness in homeless residential organizations in Los Angeles.
Natural hazards review, 19(1), 04017027.
Goepel, K. D. (2013). Implementing the analytic hierarchy process as a standard
method for multi-criteria decision making in corporate enterprises–a new
AHP excel template with multiple inputs. Paper presented at the Proceedings
of the international symposium on the analytic hierarchy process.
GoSL. (2018). Population and Population Density by D.S. Division - 2018
Retrieved from
http://www.statistics.gov.lk/statistical%20Hbook/2019/Ampara/2.4.1.pdf.
Retrieved 20 February 2020, from District Secretariate, Ampara, Sri Lanka
http://www.statistics.gov.lk/statistical%20Hbook/2019/Ampara/2.4.1.pdf
Grantham, H. S., Pressey, R. L., Wells, J. A., & Beattie, A. J. (2010). Effectiveness
of biodiversity surrogates for conservation planning: different measures of
effectiveness generate a kaleidoscope of variation. PLoS One, 5(7).
Grayson, R. B., Finlayson, B. L., Gippel, C. J., & Hart, B. T. (1996). The potential of
field turbidity measurements for the computation of total phosphorus and
suspended solids loads. Journal of Environmental Management, 47(3), 257-
267. doi:10.1006/jema.1996.0051
Greene, J. C., & Hall, J. N. (2010). Dialectics and pragmatism: Being of
consequence. Handbook of mixed methods in social and behavioral research,
119-144.
Bibliography 266
Gregory, R. D., Vorisek, P., Van Strien, A., GMELIG MEYLING, A. W., Jiguet, F.,
Fornasari, L., Reif, J., Chylarecki, P., & Burfield, I. J. (2007). Population
trends of widespread woodland birds in Europe. Ibis, 149, 78-97.
Guadagno, L. (2016). Human Mobility in the Sendai Framework for Disaster Risk
Reduction. International Journal of Disaster Risk Science, 7(1), 30-40.
doi:10.1007/s13753-016-0077-6
Gubrium, J., Holstein, J., Marvasti, A., & McKinney, K. (2012). The SAGE
Handbook of Interview Research: The Complexity of the Craft Retrieved
from http://methods.sagepub.com/book/handbook-of-interview-research-2e
doi:10.4135/9781452218403
Hancock, D. R., & Algozzine, B. (2016). Doing case study research: A practical
guide for beginning researchers: Teachers College Press.
Hazeleger, T. (2013). Gender and disaster recovery: Strategic issues and action in
Australia. Australian Journal of Emergency Management, The, 28(2), 40.
Hegney, D., Ross, H., & Baker, P. (2008). Building resilience in rural communities:
toolkit.
Henn, M., Weinstein, M., & Foard, N. (2009). A critical introduction to social
research (2nd Edition ed.): Sage Publications.
Henstra, D. (2010). Evaluating local government emergency management programs:
What framework should public managers adopt? Public Administration
Review, 70(2), 236-246.
Ho, D., Newell, G., & Walker, A. (2005). The importance of property-specific
attributes in assessing CBD office building quality. Journal of Property
Investment & Finance, 23(5), 424-444.
Hoffmann, R., & Muttarak, R. (2017). Learn from the Past, Prepare for the Future:
Impacts of Education and Experience on Disaster Preparedness in the
Philippines and Thailand. World Development, 96, 32-51.
doi:https://doi.org/10.1016/j.worlddev.2017.02.016
Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review
of Ecology and Systematics, 4(1), 1-23.
Hyde, K. M. (2006). Uncertainty analysis methods for multi-criteria decision
analysis.
IFRC. (2016). World Disasters Report 2016: Resilience: saving lives today, investing
for tomorrow. Retrieved from www.ifrc.org/wdr2016.
Ishizaka, A., & Nemery, P. (2013). A Multi-Criteria Group Decision Framework for
Partner Grouping When Sharing Facilities. Group Decision and Negotiation,
22(4), 773-799. doi:10.1007/s10726-012-9292-8
Izumi, T., Shaw, R., Djalante, R., Ishiwatari, M., & Komino, T. (2019). Disaster risk
reduction and innovations. Progress in Disaster Science, 2, 100033.
Jameel, M. I. M., Musthaffa, A.H.M. (2009). Disaster history of Sainthamaruthu
village History of Sainthamaruthu (pp. 449). Sainthamaruthu: Community
Welfare and Disaster Management Council, Grand Mosque, Sainthamaruthu-
Maligaikadu, Sri Lanka.
JICA. (2008). RECOVERY, REHABILITATION AND DEVELOPMENT PROJECT
FOR TSUNAMI AFFECTED AREA OF NORTHERN AND EASTERN
REGION - Chapter 6 Retrieved from
http://open_jicareport.jica.go.jp/pdf/11871076_01.pdf
Joerin, J., Shaw, R., Takeuchi, Y., & Krishnamurthy, R. (2014). The adoption of a
climate disaster resilience index in Chennai, India. Disasters, 38(3), 540-561.
Bibliography 267
Johnson, J. M., & Rowlands, T. (2012). The SAGE Handbook of Interview
Research: The Complexity of the Craft (2 ed.). Thousand Oaks, California:
SAGE Publications, Inc. Retrieved from
http://methods.sagepub.com/book/handbook-of-interview-research-2e.
doi:10.4135/9781452218403
Jones, L., & Tanner, T. (2017). ‘Subjective resilience’: using perceptions to quantify
household resilience to climate extremes and disasters. Regional
Environmental Change, 17(1), 229-243. doi:10.1007/s10113-016-0995-2
Jülich, S. (2017). Towards a Local-Level Resilience Composite Index: Introducing
Different Degrees of Indicator Quantification. International Journal of
Disaster Risk Science, 8(1), 91-99. doi:10.1007/s13753-017-0114-0
Kafle, S. K. (2012). Measuring disaster-resilient communities: a case study of coastal
communities in Indonesia. Journal of business continuity & emergency
planning, 5(4), 316-326. Retrieved from
http://www.ingentaconnect.com/content/hsp/jbcep/2012/00000005/00000004
/art00004
Kapucu, N., Hawkins, C. V., & Rivera, F. I. (2013). Disaster Preparedness and
Resilience for Rural Communities. Risk, Hazards & Crisis in Public Policy,
4(4), 215-233. doi:10.1002/rhc3.12043
Keating, A., Campbell, K., Szoenyi, M., McQuistan, C., Nash, D., & Burer, M.
(2017). Development and testing of a community flood resilience
measurement tool. Natural Hazards and Earth System Sciences, 17(1), 77.
Keating, A., & Hanger-Kopp, S. (2019). Practitioner perspectives of disaster
resilience in international development. International Journal of Disaster
Risk Reduction, 101355. doi:https://doi.org/10.1016/j.ijdrr.2019.101355
Keating, A., Venkateswaran, K., Szoenyi, M., MacClune, K., & Mechler, R. (2016).
From event analysis to global lessons: disaster forensics for building
resilience. Natural Hazards and Earth System Sciences, 16(7), 1603-1616.
Keck, M., & Sakdapolrak, P. (2013). What is social resilience? Lessons learned and
ways forward. Erdkunde, 5-19.
Kelman, I., & Glantz, M. H. (2014). Early Warning Systems Defined. In A. Singh &
Z. Zommers (Eds.), Reducing Disaster: Early Warning Systems For Climate
Change (pp. 89-108). Dordrecht: Springer Netherlands.
Khalili, S., Harre, M., & Morley, P. (2015). A temporal framework of social
resilience indicators of communities to flood, case studies: Wagga wagga and
Kempsey, NSW, Australia. International Journal of Disaster Risk Reduction,
13, 248-254. doi:10.1016/j.ijdrr.2015.06.009
Kilic, H. S., Zaim, S., & Delen, D. (2015). Selecting “The Best” ERP system for
SMEs using a combination of ANP and PROMETHEE methods. Expert
Systems with Applications, 42(5), 2343-2352.
doi:https://doi.org/10.1016/j.eswa.2014.10.034
Kimhi, S., & Shamai, M. (2004). Community resilience and the impact of stress:
Adult response to Israel's withdrawal from Lebanon. Journal of Community
Psychology, 32(4), 439-451.
Klein, R. J., Nicholls, R. J., & Thomalla, F. (2003). Resilience to natural hazards:
How useful is this concept? Global Environmental Change Part B:
Environmental Hazards, 5(1-2), 35-45.
Kotzee, I., & Reyers, B. (2016). Piloting a social-ecological index for measuring
flood resilience: A composite index approach. Ecological Indicators, 60, 45-
53.
Bibliography 268
Kulig, J. C., Edge, D. S., Townshend, I., Lightfoot, N., & Reimer, W. (2013).
COMMUNITY RESILIENCY: EMERGING THEORETICAL INSIGHTS.
Journal of Community Psychology, 41(6), 758-775. doi:10.1002/jcop.21569
Kusumastuti, R. D., Viverita, Husodo, Z. A., Suardi, L., & Danarsari, D. N. (2014).
Developing a resilience index towards natural disasters in Indonesia.
International Journal of Disaster Risk Reduction, 10, Part A, 327-340.
doi:http://dx.doi.org/10.1016/j.ijdrr.2014.10.007
Kwok, A. H., Doyle, E. E. H., Becker, J., Johnston, D., & Paton, D. (2016). What is
‘social resilience’? Perspectives of disaster researchers, emergency
management practitioners, and policymakers in New Zealand. International
Journal of Disaster Risk Reduction, 19, 197-211.
doi:http://dx.doi.org/10.1016/j.ijdrr.2016.08.013
Lane, P., Barton, P., & Lindenmayer, D. (2015). Use of surrogates in medicine: ideas
that may be useful for ecology. Indicators and Surrogates of Biodiversity and
Environmental Change, 1, 103.
Leeuw, E. d. (2008). The SAGE Handbook of Social Research Methods. London:
SAGE Publications Ltd. Retrieved from
http://methods.sagepub.com/book/the-sage-handbook-of-social-research-
methods. doi:10.4135/9781446212165
Levine, S. (2014). Assessing resilience: why quantification misses the point.
Humanitarian Policy Group (ODI) Working Paper.
Leximancer. (2017). Leximancer User Guide Release 4.5.
Leykin, D., Lahad, M., Cohen, R., Goldberg, A., & Aharonson-Daniel, L. (2016).
The dynamics of community resilience between routine and emergency
situations. International Journal of Disaster Risk Reduction, 15, 125-131.
doi:http://dx.doi.org/10.1016/j.ijdrr.2016.01.008
Lindenmayer, D., Barton, P., & Pierson, J. (2015a). Indicators and Surrogates of
Biodiversity and Environmental Change: CSIRO PUBLISHING.
Lindenmayer, D., Pierson, J., Barton, P., Beger, M., Branquinho, C., Calhoun, A.,
Caro, T., Greig, H., Gross, J., & Heino, J. (2015b). A new framework for
selecting environmental surrogates. Science of the total Environment, 538,
1029-1038. doi:http://dx.doi.org/10.1016/j.scitotenv.2015.08.056
Lindenmayer, D. B., & Likens, G. E. (2011). Direct measurement versus surrogate
indicator species for evaluating environmental change and biodiversity loss.
Ecosystems, 14(1), 47-59. doi:10.1007/s10021-010-9394-6
Lorenz, D. F. (2013). The diversity of resilience: contributions from a social science
perspective. Natural Hazards, 67(1), 7-24.
Lovell, E., & Le Masson, V. (2014). Equity and inclusion in disaster risk reduction:
building resilience for all: Overseas Development Institute.
Maclaren, V. W. (1996). Urban sustainability reporting. Journal of the American
Planning Association, 62(2), 184-202.
Maduz, L., & Roth, F. (2017). The Urbanization of Disaster Management. CSS
Analyses in Security Policy, 204.
Maguire, B., & Hagan, P. (2007). Disasters and communities: understanding social
resilience. Australian Journal of Emergency Management, The, 22(2), 16.
Majumder, M. (2015). Multi Criteria Decision Making Impact of Urbanization on
Water Shortage in Face of Climatic Aberrations (pp. 35-47). Singapore:
Springer Singapore.
Bibliography 269
Manyena, B. (2016). After Sendai: Is Africa Bouncing Back or Bouncing Forward
from Disasters? International Journal of Disaster Risk Science, 7(1), 41-53.
doi:10.1007/s13753-016-0084-7
Markelj, J., Kitek Kuzman, M., Grošelj, P., & Zbašnik-Senegačnik, M. (2014). A
simplified method for evaluating building sustainability in the early design
phase for architects. Sustainability, 6(12), 8775-8795.
Marshall, C., & Rossman, G. B. (2014). Designing qualitative research (5th ed.):
Sage publications.
Matyas, D., & Pelling, M. (2015). Positioning resilience for 2015: the role of
resistance, incremental adjustment and transformation in disaster risk
management policy. Disasters, 39(s1), s1-s18. doi:10.1111/disa.12107
Mayunga, J. S. (2007). Understanding and applying the concept of community
disaster resilience: a capital-based approach. Summer academy for social
vulnerability and resilience building, 1, 16.
McMillen, H., Campbell, L., Svendsen, E., & Reynolds, R. (2016). Recognizing
Stewardship Practices as Indicators of Social Resilience: In Living Memorials
and in a Community Garden. Sustainability, 8(8), 775. Retrieved from
http://www.mdpi.com/2071-1050/8/8/775
Mellin, C., Delean, S., Caley, J., Edgar, G., Meekan, M., Pitcher, R., Przeslawski,
R.,Williams, A., Bradshaw, C. (2011). Effectiveness of biological surrogates
for predicting patterns of marine biodiversity: a global meta-analysis. PLoS
One 6, e20141.
Miguntanna, N. S., Egodawatta, P., Kokot, S., & Goonetilleke, A. (2010).
Determination of a set of surrogate parameters to assess urban stormwater
quality. Science of the total Environment, 408(24), 6251-6259.
doi:10.1016/j.scitotenv.2010.09.015
Miller, M., Paton, D., & Johnston, D. (1999). Community vulnerability to volcanic
hazard consequences. Disaster Prevention and Management: An
International Journal, 8(4), 255-260.
Mills, J., Harrison, H., Franklin, R., & Birks, M. (2017). Case study research:
Foundations and methodological orientations. Paper presented at the Forum
Qualitative Sozialforschung/Forum: Qualitative Social Research.
Mitchell, T., & Harris, K. (2012). Resilience: A risk management approach. ODI
background note, 1-7.
Mitchell, T., Jones, L., Lovell, E., Comba, E. (2013). Disaster Risk Management in
Post-2015 Development Goals - Potential targets and indicators. Overseas
Development Institute, London.
Moher D, L. A., Tetzlaff J, Altman DG. (2009). Preferred Reporting Items for
Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS
Med, 6(7). doi:10.1371/journal.pmed1000097
Morgan, D. L. (2007). Paradigms Lost and Pragmatism Regained:Methodological
Implications of Combining Qualitative and Quantitative Methods. Journal of
Mixed Methods Research, 1(1), 48-76. doi:10.1177/2345678906292462
Nadel, S. F. (2013). The theory of social structure: Routledge.
Neuman, L. W. (2014). Social Research Methods: Qualitative and Quantitative
Approaches (7E ed.): Pearson Education India.
Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F., & Pfefferbaum, R. L.
(2008). Community resilience as a metaphor, theory, set of capacities, and
strategy for disaster readiness. American journal of community psychology,
41(1-2), 127-150. doi:DOI 10.1007/s10464-007-9156-6
Bibliography 270
O’Loughlin, L. S., Lindenmayer, D. B., Smith, M. D., Willig, M. R., Knapp, A. K.,
Cuddington, K., Hastings, A., Foster, C. N., Sato, C. F., & Westgate, M. J.
(2018a). Surrogates underpin ecological understanding and practice.
Bioscience, 68(9), 640-642.
O’Loughlin, L. S., Lindenmayer, D. B., Smith, M. D., Willig, M. R., Knapp, A. K.,
Cuddington, K., Hastings, A., Foster, C. N., Sato, C. F., & Westgate, M. J.
(2018b). Surrogates Underpin Ecological Understanding and Practice.
BioScience.
Oppenheim, A. N. (2000). Questionnaire design, interviewing and attitude
measurement: Bloomsbury Publishing.
Orencio, P. M., & Fujii, M. (2013). A localized disaster-resilience index to assess
coastal communities based on an analytic hierarchy process (AHP).
International Journal of Disaster Risk Reduction, 3, 62-75.
doi:http://dx.doi.org/10.1016/j.ijdrr.2012.11.006
Ostadtaghizadeh, A., Ardalan, A., Paton, D., Jabbari, H., & Khankeh, H. R. (2015).
Community disaster resilience: a systematic review on assessment models
and tools. PLoS Currents, 7.
doi:10.1371/currents.dis.f224ef8efbdfcf1d508dd0de4d8210ed
Ostadtaghizadeh, A., Ardalan, A., Paton, D., Khankeh, H., & Jabbari, H. (2016).
Community disaster resilience: a qualitative study on Iranian concepts and
indicators. Natural Hazards, 83(3), 1843-1861. doi:10.1007/s11069-016-
2377-y
Park, B., & Youngchul Kim, R. (2014). Making a decision about importance analysis
and prioritization of use cases through comparison the analytic hierarchy
process (AHP) with use case point (UCP) technique. International Journal of
Software Engineering and Its Applications, 8(3), 89-96.
Parsons, M., Glavac, S., Hastings, P., Marshall, G., McGregor, J., McNeill, J.,
Morley, P., Reeve, I., & Stayner, R. (2016). Top-down assessment of disaster
resilience: A conceptual framework using coping and adaptive capacities.
International Journal of Disaster Risk Reduction, 19, 1-11.
doi:http://dx.doi.org/10.1016/j.ijdrr.2016.07.005
Paton, D. (2007). Preparing for natural hazards: The role of community trust.
DISASTER PREVENTION AND MANAGEMENT, 16(3), 370-379.
doi:10.1108/09653560710758323
Paton, D., Millar, M., & Johnston, D. (2001). Community resilience to volcanic
hazard consequences. Natural Hazards, 24(2), 157-169.
Patton, M. Q. (2002). Qualitative evaluation and research methods (3rd ed.): SAGE
Publications, inc.
Peacock, W. G., Brody, S. D., Seitz, W. A., Merrell, W., Vedlitz, A., Zahran, S.,
Harriss, R., & Stickney, R. (2010). Advancing Resilience of Coastal
Localities: Developing, Implementing, and Sustaining the Use of Coastal
Resilience Indicators: A Final Report. Hazard Reduction and Recovery
Center.
Pelham, L., Clay, E., & Braunholz, T. (2011). Natural disasters: what is the role for
social safety nets? : World Bank.
Penn-Edwards, S. (2010). Computer aided phenomenography: The role of
Leximancer computer software in phenomenographic investigation. The
Qualitative Report, 15(2), 252.
Peters, K., Bahadur, A., Tanner, T., & Langston, L. (2016). ‘Resilience’across the
post-2015 frameworks: towards coherence?
Bibliography 271
Petrini, M. A., Rocha, J. V., Brown, J. C., & Bispo, R. C. (2016). Using an analytic
hierarchy process approach to prioritize public policies addressing family
farming in Brazil. LAND USE POLICY, 51, 85-94.
Pfefferbaum, R. L., Pfefferbaum, B., Van Horn, R. L., Klomp, R. W., Norris, F. H.,
& Reissman, D. B. (2013). The Communities Advancing Resilience Toolkit
(CART): An Intervention to Build Community Resilience to Disasters.
Journal of Public Health Management and Practice, 19(3), 250-258.
doi:10.1097/PHH.0b013e318268aed8
Pickard, A. J. (2013). Research methods in information: Facet publishing.
Plough, A., Fielding, J. E., Chandra, A., Williams, M., Eisenman, D., Wells, K. B.,
Law, G. Y., Fogleman, S., & Magaña, A. (2013). Building Community
Disaster Resilience: Perspectives From a Large Urban County Department of
Public Health. American Journal of Public Health, 103(7), 1190-1197.
doi:10.2105/ajph.2013.301268
Punch, K. F. (2013). Introduction to social research: Quantitative and qualitative
approaches: sage.
Qasim, S., Qasim, M., Shrestha, R. P., Khan, A. N., & Tun, K. (2016a). Community
resilience to flood hazards in Khyber Pukhthunkhwa province of Pakistan.
International Journal of Disaster Risk Reduction.
Qasim, S., Qasim, M., Shrestha, R. P., Khan, A. N., Tun, K., & Ashraf, M. (2016b).
Community resilience to flood hazards in Khyber Pukhthunkhwa province of
Pakistan. International Journal of Disaster Risk Reduction, 18, 100-106.
doi:http://dx.doi.org/10.1016/j.ijdrr.2016.03.009
Quinlan, A. E., Berbés‐Blázquez, M., Haider, L. J., & Peterson, G. D. (2015).
Measuring and assessing resilience: broadening understanding through
multiple disciplinary perspectives. Journal of Applied Ecology.
Reed, M. S., Fraser, E. D. G., & Dougill, A. J. (2006). An adaptive learning process
for developing and applying sustainability indicators with local communities.
Ecological Economics, 59(4), 406-418.
doi:https://doi.org/10.1016/j.ecolecon.2005.11.008
Renschler, C. S., Frazier, A., Arendt, L., Cimellaro, G.-P., Reinhorn, A. M., &
Bruneau, M. (2010). A framework for defining and measuring resilience at
the community scale: the PEOPLES resilience framework. MCEER, Buffalo.
Rockström, J. (2003). Resilience building and water demand management for
drought mitigation. Physics and Chemistry of the Earth, Parts A/B/C, 28(20),
869-877.
Rodrigues, A. S., & Brooks, T. M. (2007). Shortcuts for biodiversity conservation
planning: the effectiveness of surrogates. Annual review of ecology,
evolution, and systematics, 713-737. doi:10.1
146/annurev.ecolsys.38.091206.095737
Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process.
European journal of operational research, 48(1), 9-26.
Saaty, T. L. (2008). Decision making with the analytic hierarchy process.
International journal of services sciences, 1(1), 83-98.
Saja, A. M. A., Goonetilleke, A., Teo, M., & Ziyath, A. M. (2019). A critical review
of social resilience assessment frameworks in disaster management.
International Journal of Disaster Risk Reduction, 101096.
doi:https://doi.org/10.1016/j.ijdrr.2019.101096
Saja, A. M. A., Teo, M., Goonetilleke, A., & Ziyath, A. M. (2018). An inclusive and
adaptive framework for measuring social resilience to disasters. International
Bibliography 272
Journal of Disaster Risk Reduction, 28, 862-873.
doi:https://doi.org/10.1016/j.ijdrr.2018.02.004
Saleh, A., & Bista, K. (2017). Examining factors impacting online survey response
rates in educational research: Perceptions of graduate students. Journal of
MultiDisciplinary Evaluation, 13(29), 63-74.
Sanyal, S., & Routray, J. K. (2016). Social capital for disaster risk reduction and
management with empirical evidences from Sundarbans of India.
International Journal of Disaster Risk Reduction, 19, 101-111.
Sapsford, R. (2006). Survey research (2nd edition ed.): Sage.
Saunders, M., Lewis, P., & Thornhill, A. (2016). Research Methods for Business
students.(ed. 7 th) Harlow: Pearson Education Limited.
Saunders, M. N., Lewis, P., Thornhill, A., & Bristow, A. (2015). Understanding
research philosophy and approaches to theory development.
Saunders, M. N. K., Lewis, P., & Thornhill, A. (2019). Research methods for
business students.
Schilling, K. E., Kim, S.-W., & Jones, C. S. (2017). Use of water quality surrogates
to estimate total phosphorus concentrations in Iowa rivers. Journal of
Hydrology: Regional Studies, 12, 111-121.
doi:https://doi.org/10.1016/j.ejrh.2017.04.006
Schipper, E. L. F., & Langston, L. (2015). A comparative overview of resilience
measurement frameworks.
Scopus. (2017). About Scopus Retrieved from
https://www.elsevier.com/solutions/scopus
Sempier, T., Swann, D., Emmer, R., Sempier, S., & Schneider, M. (2010). Coastal
community resilience index: a community self-assessment. online]
http://www. masgc. org/pdf/masgp/08-014. pdf (accessed 17 June 2013).
Serfilippi, E., & Ramnath, G. (2018). RESILIENCE MEASUREMENT AND
CONCEPTUAL FRAMEWORKS: A REVIEW OF THE LITERATURE.
Annals of Public and Cooperative Economics. doi:10.1111/apce.12202
Settle, S., Goonetilleke, A., & Ayoko, G. A. (2007). Determination of surrogate
indicators for phosphorus and solids in urban stormwater: application of
multivariate data analysis techniques. Water, air, and soil pollution, 182(1-4),
149-161.
Sharifi, A. (2016). A critical review of selected tools for assessing community
resilience. Ecological Indicators, 69, 629-647.
doi:10.1016/j.ecolind.2016.05.023
Sharifi, A., & Yamagata, Y. (2016). On the suitability of assessment tools for
guiding communities towards disaster resilience. International Journal of
Disaster Risk Reduction, 18, 115-124.
Sharma, U., & Patt, A. (2012). Disaster warning response: the effects of different
types of personal experience. Natural Hazards, 60(2), 409-423.
Sharp, J. L., Mobley, C., Hammond, C., Withington, C., Drew, S., Stringfield, S., &
Stipanovic, N. (2012). A Mixed Methods Sampling Methodology for a
Multisite Case Study. Journal of Mixed Methods Research, 6(1), 34-54.
doi:10.1177/1558689811417133
Shaw, D., Scully, J., & Hart, T. (2014). The paradox of social resilience: How
cognitive strategies and coping mechanisms attenuate and accentuate
resilience. Global Environmental Change, 25, 194-203.
doi:http://dx.doi.org/10.1016/j.gloenvcha.2014.01.006
Bibliography 273
Sherrieb, K., Louis, C. A., Pfefferbaum, R. L., Betty Pfefferbaum, J. D., Diab, E., &
Norris, F. H. (2012). Assessing community resilience on the US coast using
school principals as key informants. International Journal of Disaster Risk
Reduction, 2, 6-15. doi:http://dx.doi.org/10.1016/j.ijdrr.2012.06.001
Sherrieb, K., Norris, F. H., & Galea, S. (2010). Measuring capacities for community
resilience. Social Indicators Research, 99(2), 227-247. doi:10.1007/s11205-
010-9576-9
Sinclair, R. G., Rose, J. B., Hashsham, S. A., Gerba, C. P., & Haas, C. N. (2012).
Criteria for selection of surrogates used to study the fate and control of
pathogens in the environment. Appl. Environ. Microbiol., 78(6), 1969-1977.
Singh, A., Ayoko, G. A., Herngren, L., & Goonetilleke, A. (2013). A Multivariate
Approach to the Identification of Surrogate Parameters for Heavy Metals in
Stormwater. Water, Air, & Soil Pollution, 1(224), 1-9.
Singh, K. (2007). Quantitative social research methods: Sage.
Singh, R. K., Murty, H. R., Gupta, S. K., & Dikshit, A. K. (2009). An overview of
sustainability assessment methodologies. Ecological Indicators, 9(2), 189-
212.
Sorensen, J. H., & Sorensen, B. V. (2007). Community Processes: Warning and
Evacuation Handbook of Disaster Research (pp. 183-199). New York, NY:
Springer New York.
Sotiriadou, P., Brouwers, J., & Le, T.-A. (2014). Choosing a qualitative data analysis
tool: a comparison of NVivo and Leximancer. Annals of Leisure Research,
17(2), 218-234. doi:10.1080/11745398.2014.902292
Sphere. (2018). Humanitarian Charter and Minimum Standards in Disaster
Response - 2018 Edition. Geneva, Switzerland.
Stough, L. M., & Kang, D. (2015). The Sendai Framework for Disaster Risk
Reduction and Persons with Disabilities. International Journal of Disaster
Risk Science, 6(2), 140-149. doi:10.1007/s13753-015-0051-8
Swanborn, P. (2010). Case study research: What, why and how? : Sage.
Tapsell, S. (2007). Social indicator set. T11-07-01.
Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research:
Integrating quantitative and qualitative approaches in the social and
behavioral sciences: Sage.
Thoresen, S., Birkeland, M. S., Wentzel-Larsen, T., & Blix, I. (2018). Loss of trust
may never heal. Institutional trust in disaster victims in a long-term
perspective: associations with social support and mental health. Frontiers in
Psychology, 9, 1204.
Tierney, K. (2009). Disaster response: Research findings and their implications for
resilience measures. Retrieved from
Timmerman, P. (1981). Vulnerability resilience and collapse ofsociety. Rev. Models
Possible Clim. Appli-Cations.
Townshend, I., Awosoga, O., Kulig, J., & Fan, H. (2015). Social cohesion and
resilience across communities that have experienced a disaster. Natural
Hazards, 76(2), 913-938. doi:10.1007/s11069-014-1526-4
Tulloch, A. I., Chadès, I., Dujardin, Y., Westgate, M. J., Lane, P. W., &
Lindenmayer, D. (2016). Dynamic species co‐occurrence networks require
dynamic biodiversity surrogates. Ecography, 39(12), 1185-1196.
Twigg, J. (2009). Characteristics of a disaster-resilient community: a guidance note
(version 2).
Bibliography 274
Twigg, J., Kett, M., & Lovell, E. (2018). Disability inclusion and disaster risk
reduction.
Tyler, S., Nugraha, E., Nguyen, H. K., Nguyen, N. V., Sari, A. D., Thinpanga, P.,
Tran, T. T., & Verma, S. S. (2016). Indicators of urban climate resilience: A
contextual approach. Environmental Science & Policy, 66, 420-426.
doi:https://doi.org/10.1016/j.envsci.2016.08.004
Udie, J., Bhattacharyya, S., & Ozawa-Meida, L. (2018). A conceptual framework for
vulnerability assessment of climate change impact on critical oil and gas
infrastructure in the niger delta. Climate, 6(1), 11.
UN. (2016). Report of the open-ended intergovernmental expert working group on
indicators and terminology relating to disaster risk reduction. Retrieved from
https://www.preventionweb.net/files/50683_oiewgreportenglish.pdf
UNHABITAT. (2015). Kalmunai - Disaster Risk Reduction and Preparedness Plan -
towards a sustainable and resilient city. Retrieved from
http://unhabitat.lk/wp-content/uploads/2015/01/DRRPKmEng.pdf
UNISDR. (2009). 2009 UNISDR Terminology on Disaster Risk Reduction. Retrieved
from United Nations International Strategy for Disaster Reduction:
http://www.unisdr.org/files/7817_UNISDRTerminologyEnglish.pdf
UNISDR. (2015a). Proposed Updated Terminology on Disaster Risk Reduction: A
Technical Review. Retrieved from
http://www.preventionweb.net/files/45462_backgoundpaperonterminologyau
gust20.pdf
UNISDR. (2015b). Sendai framework for disaster risk reduction 2015–2030.: United
Nations International Strategy for Disaster Reduction Retrieved from
http://www.wcdrr.org/uploads/Sendai_Framework_for_Disaster_Risk_Reduc
tion_2015-2030.pdf.
UnitedWay. (1996). Measuring Program Outcomes: A Practical Approach.
USIOTWSP. (2007). How Resilient is Your Coastal Community? A Guide for
Evaluating Coastal Community Resilience to Tsunamis and Other Coastal
Hazards. Retrieved from Bangkok, Thailand:
Uslaner, E. M. (2016). Disasters, Trust, and Social Cohesion.
Vaismoradi, M., Jones, J., Turunen, H., & Snelgrove, S. (2016). Theme development
in qualitative content analysis and thematic analysis. Journal of Nursing
Education and Practice, 6(5).
Verheyden, T., & De Moor, L. (2016). Process-oriented social responsibility
indicator for mutual funds: A multi-criteria decision analysis approach.
International Journal of Multi-Criteria Decision Making, 6(1), 66-99.
VP. (2013). PROMETHEE Methods - Visual PROMETHEE 1.4 Manual. In V.
Solutions (Ed.).
Wedley, W. C. (1993). Consistency prediction for incomplete AHP matrices.
Mathematical and Computer Modelling, 17(4-5), 151-161.
Weeraratne, B. (2016). Re-defining urban areas in Sri Lanka. Colombo: Institute of
Policy Studies of Sri Lanka.
Wilkinson, O. (2015). Faith and Resilience after Disaster - The Case of Typhoon
Haiyan. Retrieved from
Woolf, S., Twigg, J., Parikh, P., Karaoglou, A., & Cheab, T. (2016). Towards
measurable resilience: A novel framework tool for the assessment of
resilience levels in slums. International Journal of Disaster Risk Reduction,
19, 280-302. doi:http://dx.doi.org/10.1016/j.ijdrr.2016.08.003
Bibliography 275
WorldBank. (2014). 3.12 World Development Indicators: Urbanization. Retrieved
from: http://wdi.worldbank.org/table/3.12
Wright, K., & Johnston, D. (2010). Post-earthquake sheltering needs: how loss of
structures and services affects decision making for evacuation. Paper
presented at the 2010 New Zealand Society for Earthquake Engineering
Conference Proceedings.
Wu, H., & Drolet, J. (2016). Adaptive social protection: Climate change adaptation
and disaster risk reduction Social development and social work perspectives
on social protection (pp. 116-139): Routledge.
Yamamoto, L., Serraglio, D. A., & Cavedon-Capdeville, F. d. S. (2018). Human
mobility in the context of climate change and disasters: a South American
approach. International Journal of Climate Change Strategies and
Management, 10(1), 65-85.
Yin, R. K. (2014). Case study research: Design and methods (5th ed.): Sage
publications.
Yoon, D. K., Kang, J. E., & Brody, S. D. (2016). A measurement of community
disaster resilience in Korea. Journal of Environmental Planning and
Management, 59(3), 436-460. doi:10.1080/09640568.2015.1016142
Ziyath, A. M., Teo, M., & Goonetilleke, A. (2013, 17-19 September 2013 ).
Surrogate indicators for assessing community resilience. Paper presented at
the Inter-national Conference on Building Resilience, Ahungalla, Sri Lanka.
Zubair, L., Ralapanawe, V., Yahiya, Z., Perera, R., Tennakoon, U., Chandimala, J.,
Razick, S., & Lyon, B. (2005). Fine Scale Natural Hazard Risk and
Vulnerability Identification Informed by Climate in Sri Lanka. Project
Report: International Research Institute for Climate and Society. New York.
Appendices 277
Appendices
Appendix A Existing social resilience measures identified in social
resilience frameworks analysed in this study
Appendix B QUT Human Research Ethics Committee Approval
Appendix C Letter of recruitment for interview participants
Appendix D Participant interview consent form
Appendix E Participant information sheet for interviews
Appendix F Interview guide
Appendix G Participant recruitment email for the survey
Appendix H Participant information for the survey
Appendix I Survey questionnaire in key survey
Appendix J Abstracts of published and under review manuscripts
Appendices 278
Appendix A
Existing social resilience measures identified in 31 social resilience frameworks
analysed in this study
The social resilience measure for other indicators of the ‘5S’ framework (Figure 2.5)
identified from the review of 31 existent social resilience frameworks are provided in
Saja et al. (2018).
A Sub-dimension: Social structure
References from the 31 social
resilience frameworks analysed Existing measures for access to transport
1 % population with vehicle access /Transport
dependence ratio
Kusumastuti, et al. (2014), Burton
(2015), Kotzee and Reyers (2016)
2 % Households with at least one
vehicle/vehicle facility
Cutter, et al. (2010), Qasim,
Qasim, Shrestha, Khan, Tun, et al.
(2016)
3 Access/evacuation potential Kotzee and Reyers (2016)
4 Available transportation means Mayunga (2007)
B Sub-dimension: Social capital References from the 31 social
resilience frameworks analysed Existing measures for social trust
5 Level of ethnic segregation Joerin, et al. (2014)
C Sub-dimension: Social mechanisms References from the 31 social
resilience frameworks analysed
Existing measures for past experience with disaster recovery/Learning from
the past
6 Hazard severity Cutter (2016)
D Sub-dimension: Social equity/diversity References from the 31 social
resilience frameworks analysed Existing measures for Involvement and equality for people with special needs
None N/A
E Sub-dimension: Social beliefs/culture/faith References from the 31 social
resilience frameworks analysed Existing indicators for existing cultural and behavioural norms
None N/A
Appendices 279
Appendix B
QUT Human Research Ethics Committee Approval
Appendices 280
Appendix C
Letter of recruitment for interview participants
10.11.2017
………………………………………
Subject Title:
Participation in a research study on surrogate indicators for measuring social resilience to
disasters (Interviews)
Dear colleagues
My name is Aslam Saja from the Science and Engineering Faculty, Queensland University of
Technology (QUT). I am undertaking a PhD on the use of surrogate indicators for measuring
social resilience to disasters.
The aim of this research is to identify, evaluate, and select surrogate indicators to measure
social resilience to disasters.
I’m looking for participants with minimum three years of experience in disaster management
at policy/ implementation level to participate in an interview which is being undertaken as a
key component of my doctoral study. Interview will last for approximately 75 to 90 minutes.
Interviews will be scheduled on a date and time that is convenient for you and at the place of
your choice.
More details of this project and about the interviews can be found in the attached Participant
Information Sheet.
If you are interested in participating or have any questions, please contact me via phone or
email.
Please note that this study has been approved by the QUT Human Research Ethics Committee
(approval number 1700000832). Any personal information that is collected, will be treated as
confidential. Participation in the interviews is strictly voluntary and your written consent will be
sought prior to conducting interviews.
Many thanks for your consideration of this request.
Aslam Saja
PhD Student (+94) 77 395 8387 [email protected]
Melissa Teo
Principal Supervisor (+617) 3138 9953 [email protected]
Science and Engineering Faculty, Queensland University of Technology
Appendices 281
Appendix D
Participant interview consent form
CONSENT FORM FOR QUT RESEARCH PROJECT
– Individual Interview –
Developing Surrogate Indicators to Measure
Social Resilience to Disasters QUT Ethics Approval Number 1700000832
RESEARCH TEAM
Mr Aslam Saja +94 773 958 387 [email protected]
Dr Melissa Teo +61 731 389 953 [email protected]
Prof Ashantha Goonetilleke +61 731 381 539 [email protected]
STATEMENT OF CONSENT
By signing below, you are indicating that you:
Have read and understood the information document regarding this project.
Have had any questions answered to your satisfaction.
Understand that if you have any additional questions you can contact the
research team.
Understand that you are free to withdraw at any time, without comment or
penalty.
Understand that if you have concerns about the ethical conduct of the project
you can contact the Research Ethics Advisory Team on +61 7 3138 5123 or
email [email protected].
Understand that the interview will include an audio recording.
Understand that non-identifiable data from this project may be used as
comparative data in future projects.
Agree to participate in the interview.
Name
Signature
Date
PLEASE RETURN THIS SIGNED CONSENT FORM TO THE RESEARCHER.
Appendices 282
Appendix E
Participant information sheet for interviews
PARTICIPANT INFORMATION FOR QUT RESEARCH PROJECT
– Individual Interview –
Developing Surrogate Indicators to Measure
Social Resilience to Disasters QUT Ethics Approval Number 1700000832
RESEARCH TEAM
Principal Researcher: Mr Aslam Saja PhD Student
Associate Researchers: Dr Melissa Teo Principal Supervisor
Prof Ashantha Goonetilleke Associate Supervisor
Science and Engineering Faculty
Queensland University of Technology (QUT)
DESCRIPTION
This research project is being undertaken as part of the PhD study by Aslam Saja.
The purpose of this research project is to develop surrogate indicators to measure social
resilience to disasters.
Disasters continue to cause enormous loss of lives and livelihoods, and severe disruptions
to social structures. Building resilient communities is crucial to reduce damages and to
recover quickly from disaster disruptions. Strengthening social resilience will help in
minimising damages and enable faster recovery from disasters. Hence, measuring social
resilience to disasters becomes essential. This research will develop a framework to identify,
evaluate, and select key surrogate indicators to measure social resilience to disasters.
You are invited to participate in this research project because you are a representative of a
government organization/local authority or a local/international non-governmental agency
working in Ampara district, Sri Lanka, who is involved in disaster management/disaster
resilience activities in your organization.
PARTICIPATION
Your participation will involve an audio recorded interview in your office or at an agreed
location at your convenience that will take approximately 90 minutes of your time.
Questions will be asked, such as:
What are the elements that indicate the ability of families to help their neighbours
during disasters?
How can we assess the level of trust among people to help them in disasters?
What are the sources of information that tell us your community’s trust in local
organizations/authorities helping them in disaster recovery?
Appendices 283
Your participation in this project is entirely voluntary. Even if you do agree to participate
you can withdraw from the project without comment or penalty. If you withdraw, on
request any identifiable information already obtained from you will be destroyed. Your
decision to participate or not participate will in no way impact on your current or future
relationship with QUT, Australia.
EXPECTED BENEFITS
It is expected that this project may not benefit you directly. However, it is expected to
benefit disaster management stakeholders engaged in planning and implementing
projects aimed to build social resilience. This research will contribute to measure social
resilience characteristics to disasters using surrogate indicators that are easily accessible.
Other expected benefits include:
Better understanding of the complex interrelationship of social resilience to disasters;
Addressing the practical and methodological challenges in measuring social resilience
indicators; and
Contribute to address the current knowledge gap in identifying and selecting
surrogate indicators to measure social resilience.
To recognise your contribution should you choose to participate, the research team is
offering a small souvenir.
RISKS
There are minimal risks associated with your participation in this project.
These include:
A low likelihood of unintentional disclosure of confidential information pertaining to
disaster management practices. Your responses and personal information will be treated
as confidential and aliases will be used instead of your real name in all transcripts and
future publications.
You may also have to give up some of your personal time to participate in the research.
The risks will be minimized through communication with you before the interview takes
place by obtaining your permission and willingness to be interviewed at your
convenience.
You may be suspicious of the researcher’s action and about the research. To reduce this
risk, you will be provided with a detailed explanation about the research and its purposes
prior to the interview.
To manage these risks, you are also reminded to consider the following before
participating in the interview or when responding to interview questions:
Seek the permission from your organization/superior (if needed) before participating
and abide by confidentiality and privacy rules as per your organisation’s requirements.
Consider your responses in relation to your experience/knowledge on social resilience
in disaster context.
Inform the interviewer if there are questions that they are uncomfortable with. Response
to questions are voluntary and you can withdraw your consent at any time. You also
have the option to verify the information provided prior to final inclusion in the research.
PRIVACY AND CONFIDENTIALITY
All comments and responses will be treated confidentially unless required by law. The
names of individual persons are not required in any of the responses and no names or
identifying information will be included in any reporting of the research.
Appendices 284
As the interview involves an audio recording:
You will have the opportunity to verify your comments and responses prior to final
inclusion.
The recording will be destroyed 5 years after the last publication.
The recording will not be used for any other purpose.
Only the named researchers will have access to the recording.
It is not possible to participate in the research without being recorded as all
information will be translated to English after the interviews are completed.
No specific individual can be identified by the researchers.
All data collected will be stored in secure severs at QUT, Australia, as per QUT’s
Management of Research Data policy. Please note that non-identifiable data from this
project may be used as comparative data in future projects or stored on an open access
database for secondary analysis.
CONSENT TO PARTICIPATE
We would like to ask you to sign a written consent form (enclosed) to confirm your
agreement to participate.
QUESTIONS / FURTHER INFORMATION ABOUT THE PROJECT
If have any questions or require further information please contact one of the listed
researcher:
Aslam Saja +94 773 958 387 [email protected]
Melissa Teo +61 731 389 953 [email protected]
CONCERNS / COMPLAINTS REGARDING THE CONDUCT OF THE PROJECT
QUT is committed to research integrity and the ethical conduct of research projects.
However, if you do have any concerns or complaints about the ethical conduct of the
project you may contact the QUT Research Ethics Advisory Team on +61 7 3138 5123 or
email [email protected]. The QUT Research Ethics Advisory Team is not connected
with the research project and can facilitate a resolution to your concern in an impartial
manner.
THANK YOU FOR HELPING WITH THIS RESEARCH PROJECT.
PLEASE KEEP THIS SHEET FOR YOUR INFORMATION.
Appendices 285
Appendix F
Interview guide
Interview structure Questions in each interview will be asked for following five social resilience indicators.
Interview questions will follow the same structure for each social resilience indicator:
- What are the potential surrogates to measure <social resilience indicator 1/2/3/4/5>
(To identify potential surrogates)
- Why it is the suitable surrogate indicator to measure <social resilience indicator
1/2/3/4/5>
(To establish surrogacy relationship to the target indicator)
- How can we measure those surrogates proposed for <social resilience indicator
1/2/3/4/5> (To identify protocols for surrogates to measure the target indicator)
- Probe more detail on each theme proposed
Interview questions 1. Social Mobility:
A key social resilience indicator to measure ability of people to have greater mobility during
and after disasters is having access to adequate transport facility.
Following questions will be asked to measure “social mobility and access to transport
facilities” for evacuation during/after a disaster.
Key target
indicator
Questions
Social
mobility
and access
to a
transport
facility
1. How people in your area evacuate when disaster early warning is issued?
2. What are the transport modes and facilities available for evacuation
during disasters in your area?
3. How did you assess the accessibility to a transport facility for evacuation
of people?
4. What are the other elements that can indicate the availability of transport
facilities and access to those transport facilities when needed during
disasters?
5. How can we know that there is adequate transport facility available for
evacuation during disasters?
Indicator No Social resilience indicator
Indicator 1 Social mobility and access to transport facility for evacuation
Indicator 2 Social trust in disaster preparedness/response/recovery
Indicator 3 Involvement/equity for people with special needs in disasters
Indicator 4 Learnings from the past disaster experience
Indicator 5 Cultural and behavioural norms that help/impede in disasters
Appendices 286
Probing more as to why it is a good indicator based on the potential themes
that participant proposed and what are the sources from which they can be
measured.
2. Social cohesion:
A key social resilience indicator to measure social cohesion in disaster management
activities is social trust (among people/with neighbours/with local organisations/local
authorities).
Following questions will be asked to measure “social trust” in disaster management
activities.
Key target
indicator
Questions
Social
trust
6. What do you think is the level of trust among people in your area?
7. During a disaster, will people in the neighbourhood help each other? If
so, to what extent?
8. How can we assess trust in the neighbourhood for help in the event of a
future disaster?
9. How can we assess trust of people in community based organizations and
non-government organisations in your area?
10. How can we assess trust of people in government institutions and local
government authorities?
Probing more as to why it is a good indicator based on the themes that
participant proposed and what are the sources from which they can be
measured.
3. Community inclusiveness and equity:
A key social resilience indicator to measure community inclusiveness and equity is
involvement/equity for people with special needs in disaster situations.
Following questions will be asked to measure “involvement/equity for people with
special needs” in disaster situations.
Key
target
indicator
Questions
Equity
for
people
with
special
needs
11. What type of assistance people with special needs (such as disable, elders,
marginalized people) have access to prepare for disasters?
12. What are the indicators that help to measure the assistance to people with
specific needs in general?
13. How can we assess the access to different types of assistance for people
with specific needs for preparing for a disaster?
14. How the equity of assistance and services to people with special needs
are ensured in your area?
15. How can we identify whether people with specific needs have access to
adequate assistance and services they require to manage disasters?
Probing more as to why it is a good indicator based on the potential themes
that participant proposed and what are the sources from which they can be
measured.
Appendices 287
4. Community competence:
A key social resilience indicator to measure community competence is learnings from
the past disaster experience.
Following questions will be asked to measure “learning from the past disaster
experience”.
Key target
indicator
Questions
Learnings
from the
past
disaster
experience
16. What are some initiatives of the community to mitigate and prepare for
disasters?
17. Can you provide some examples of the community initiatives that have
been done since the occurrence of the last disaster, which can help them
to minimize the impact of the future disasters?
18. What indications do you have that the community has done something
new since the last disaster, to mitigate the risk associated with the disaster
or to prepare to face the next disaster?
19. What are the indicators that help us to assess the community’s learning
from the past disaster experience?
20. How can we know that the community has taken some learnings from
the past disaster experiences and taken new initiatives/innovations to
increase its resilience?
Probing more as to why it is a good indicator based on the potential themes
that participant proposed and what are the sources from which they can be
measured.
5. Local culture/beliefs/faith:
A key social resilience indicator to measure local culture/beliefs/faith influence in
disaster is to measure cultural and behavioural norms that help/impede in disasters.
Following questions will be asked to measure “cultural and behavioural norms that
help/impede in disasters”.
Key target
indicator
Questions
Cultural
and
behavioural
norms that
help/impede
in disasters
21. What are some cultural norms in your area that is very specific only to
your area?
22. How do those cultural norms help in preparing for and responding to
disaster events? Provide some examples.
23. What are some indications of cultural norms that is specific in your
area? /what indicators help you to assess that certain cultural norms
exists that help/do not help in preparing for disasters?
24. How can we assess those cultural norms that help in preparing for
disasters/ that makes peoples’ less resilient to face disasters?
25. If you have some cultural norms specific to the area that help people
in preparing for disasters, how you make use of them in your work in
preparing communities for disasters?
Probing more as to why it is a good indicator based on the potential themes
that participant proposed and what are the sources from which they can be
measured.
Appendices 288
Appendix G
Participant recruitment email for the survey
Subject Title: Participation in a research study on surrogate indicators for measuring
social resilience to disasters (Online survey questionnaire)
Dear colleagues
My name is Aslam Saja from the Science and Engineering Faculty, Queensland
University of Technology (QUT). I am undertaking a PhD on the use of surrogate
indicators for measuring social resilience to disasters.
The aim of this research is to identify, evaluate, and select surrogate indicators to
measure social resilience to disasters.
I’m looking for participants with a minimum three years of experience in disaster
management at policy/ implementation/research level to complete a 15 to 20
minute online survey which is being undertaken as a key component of my doctoral
study.
More details of this project and about the online survey can be found in the
attached Participant Information Sheet.
Further details on the study and how to participate can be found by clicking on the
following link: xxxxxxxxxxxxxxxxxxx
If you are interested in participating or have any questions, please contact me via
email.
Please note that this study has been approved by the QUT Human Research Ethics
Committee (approval number 1700000832). The online survey is anonymous and
personal identifiable information such as your name or your contact details are NOT
required.
Many thanks for your consideration of this request.
Aslam Saja
PhD Student (+94) 77 395 8387 [email protected]
Melissa Teo
Principal Supervisor (+617) 3138 9953 [email protected]
Science and Engineering Faculty, Queensland University of Technology
Appendices 289
Appendix H
Participant information for the survey
PARTICIPANT INFORMATION FOR QUT RESEARCH PROJECT
Developing Surrogate Indicators to Measure Social
Resilience to Disasters QUT Ethics Approval Number 1700000832
RESEARCH TEAM
Principal Researcher: Mr Aslam Saja PhD Student
Associate Researchers: Dr Melissa Teo Principal Supervisor
Prof Ashantha Goonetilleke Associate Supervisor
Science and Engineering Faculty
Queensland University of Technology (QUT)
DESCRIPTION
This project is being undertaken as part of a PhD by Aslam Saja.
The purpose of this project is to develop surrogate indicators to measure social resilience to
disasters.
You are invited to participate in this project because you are a disaster management
professional or researcher with at least 3 years’ direct experience in disaster management in a
government institution or a non-government organization (NGO) or research/academic
institution and are aged above 18 years old.
PARTICIPATION
Your participation will involve the completion of an online survey and will take approximately
15 to 20 minutes of your time.
Questions will include:
In your opinion, how accurately <Surrogate indicator 1> can measure social trust
(Accuracy)
In your opinion, how easily the data can be accessible for <Surrogate indicator 1> to
measure social trust (Measurement complexity)
In your opinion, can <Surrogate indicator 1> be used to measure social trust in different
phases of a disaster (Time-sensitivity)
In your opinion, how easily can social trust be communicated using <Surrogate indicator
1> (Communicability)
In your opinion, how cost-effective <Surrogate indicator 1> is, to measure social trust
(Cost-effectiveness)
Your participation in this project is entirely voluntary. If you agree to participate, we ask that
you avoid skipping any questions where possible. Your decision to participate or not
participate will in no way impact upon your current or future relationship with QUT or
Appendices 290
University of Peradeniya. If you do agree to participate you can withdraw from the project
until the point of submission. Once the online survey is submitted, it will not be possible to
withdraw from the study as all responses are anonymous.
EXPECTED BENEFITS
It is expected that this project may not directly benefit you. However, it is expected to benefit
disaster management stakeholders engaged in planning and implementing projects aimed to
build social resilience. This research will contribute to measure social resilience characteristics
to disasters using surrogate indicators that are easily accessible.
Other expected benefits include:
• Better understanding of the complex interrelationship of social resilience to disasters;
• Addressing the practical and methodical challenges in measuring social resilience
indicators; and
• Contribute to address the current knowledge gap in identifying and selecting surrogate
indicators to measure social resilience. RISKS
There are no risks beyond your valuable time of 15-20 minutes associated with your
participation in online survey. There is a low likelihood of unintentional disclosure of
confidential information pertaining to disaster management practices.
PRIVACY AND CONFIDENTIALITY
All comments and responses are anonymous and will be treated confidentially unless
required by law. The names of individual persons are not required in any of the responses.
Any data collected as part of this project will be stored securely as per QUT’s Management of
research data policy. Please note that non-identifiable data from this project may be used as
comparative data in future projects or stored in an open access database for secondary
analysis.
CONSENT TO PARTICIPATE
Submitting the completed survey is accepted as an indication of your consent to participate
in this project.
QUESTIONS / FURTHER INFORMATION ABOUT THE PROJECT
If have any questions or require further information please contact one of the listed
researcher:
Aslam Saja +94 773 958 387 [email protected]
Melissa Teo +61 731 389 953 [email protected]
CONCERNS / COMPLAINTS REGARDING THE CONDUCT OF THE PROJECT
QUT is committed to research integrity and the ethical conduct of research projects.
However, if you do have any concerns or complaints about the ethical conduct of the project
you may contact the QUT Research Ethics Advisory Team on +61 7 3138 5123 or email
[email protected]. The QUT Research Ethics Advisory Team is not connected with the
research project and can facilitate a resolution to your concern in an impartial manner.
THANK YOU FOR HELPING WITH THIS RESEARCH PROJECT.
PLEASE KEEP THIS SHEET FOR YOUR INFORMATION.
Appendices 291
Appendix I
Survey questionnaire in KEY SURVEY
I.1: Introductory questions
1- Have you been involved in a disaster resilience project during the past 5 – 10
years? Yes b. No
2- If yes, in the disaster resilience project, what best describes your role in the
project?
a. Project Implementing Staff b. Project Manager c. Volunteer
d. Researcher e. Academic f. Policy maker g. other, please specify
3- Where do you currently work?
a. Government department b. Local NGO c. International NGO
d. UN agency e. Donor agency f. Private sector
g. Civil Society Organisation (CSO) h. Community Based
Organisation (CBO)
4. In which country do you currently work?
5. What are the countries you have undertaken/worked on disaster projects? List
all that applies
6. What is your gender? Male Female
7. How many years of experience you have in community resilience/disaster
resilience projects?
a. Less than 3 years b. 3-5 years c. 5-10 years d. More than 10 years
8. What is your highest level of education?
a. PhD b. Master degree c. Bachelor degree d. Advance diploma
e. Professional certificate f. High school education
Appendices 292
I.2: Evaluation of surrogates against five evaluation criteria:
A. Measuring access to transport facilities during and after disasters
Rate each surrogate proposed to measure “access to transport facility during and after
disasters” in the scale of 1 – 5 (Very high to very low)
I. How accurate are the following surrogate indicators proposed to measure “access
to transport facilities during and after disasters”?
Accuracy of the potential surrogate indicators
1 (Very high) 2 (High) 3 (Average) 4 (Low) 5 (Very low)
Surrogate 1
Surrogate 2
Surrogate 3
II. Rate the cost-effectiveness of the following surrogate indicators proposed to
measure “access to transport facilities during and after disasters”?
Cost-effectiveness of the potential surrogate indicators
1 (Very high) 2 (High) 3 (Average) 4 (Low) 5 (Very low)
Surrogate 1
Surrogate 2
Surrogate 3
III. In your opinion, how much the following surrogate indicators are difficult to
measure?
Measurement complexity of the potential surrogate indicators
1 (Very high) 2 (High) 3 (Average) 4 (Low) 5 (Very low)
Surrogate 1
Surrogate 2
Surrogate 3
IV. In your opinion, how easy the following surrogate indicators are to
communicate with the disaster management stakeholders?
Communicability of the potential surrogate indicators
1 (Very high) 2 (High) 3 (Average) 4 (Low) 5 (Very low)
Surrogate 1
Surrogate 2
Surrogate 3
V. In your opinion, can the following surrogate indicators be used to measure “access
to transport facility” in different time periods (Before/During/After)?
Time sensitivity of the potential surrogate indicators
1 (Very high) 2 (High) 3 (Average) 4 (Low) 5 (Very low)
Surrogate 1
Surrogate 2
Surrogate 3
Appendices 293
I.3. Importance of surrogate indicator evaluation criteria:
Please complete the following pair-wise comparison matrix of criteria based on the
importance of each criterion against another criterion list below on the scale of 1 to
5.
Appendices 294
Appendix J
Paper 1 Title: A critical review of social resilience assessment frameworks in
disaster management
Status: Published
Year: 2019
Journal: International Journal of Disaster Risk Reduction (Q1)
Abstract: In published format below
Appendices 295
Paper 2 Title: An inclusive and adaptive framework for measuring social
resilience to disasters
Status: Published
Year: 2018
Journal: International Journal of Disaster Risk Reduction (Q1)
Abstract: In published format below
Appendices 296
Paper 3 Title: Surrogate measures to assess mobility of people as a resilience
indicator in disaster management: An exploratory study in
Southeastern Sri Lanka
Status: Published
Year: 2020
Journal: International Journal of Disaster Risk Science (Q1)
Abstract: In the published format
Appendices 297
Paper 4 Title: Selection of surrogates to assess social resilience in disaster
management using Multi-Criteria Decision making
Status: Published
Year: 2020
Journal: International Journal of Disaster Resilience in the Built Environment
(Q1)
Abstract: In the published format
Appendices 298