Untangling the Drivers of Disaster Resilience Developing a Context, Capacity and Performance Model of Local Government DRR, Benjamin BECCARI
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6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
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Untangling the Drivers of Disaster Resilience Developing a Context, Capacity and Performance Model of Local Government DRR, Benjamin BECCARI
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Untangling the Drivers of Disaster Resilience:
Developing a Context, Capacity and Performance
Model of Local Government Disaster Risk Reduction
Benjamin Beccari, PhD Candidate,
Scuola Universitaria Superiore IUSS Pavia
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Rationale
Preparedville
• Active disaster committee
• High building code compliance
• Strong investment in DRR
Wontappenere
• Committee doesn’t meet
• 15 year old disaster plan
• Unknown code compliance
Why do some local
governments have
strong DRR action
and others don’t?
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
The Context Capacity and Performance Model of
Local Government DRR
PerformanceCapacityContext
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
The Context Capacity and Performance Model of
Local Government DRR
What is it?
• A framework for understanding the range of drivers and
barriers to local government action on DRR
• Hypotheses on the relationships between context, capacity
and performance factors
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
The Context Capacity and Performance Model of
Local Government DRR
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Validation Options
• Meta-Analysis
• Pros
– Use Existing Data
– Better review present
studies
– Identify better measures of
context and capacity
• Cons
– Insufficient overlap in
studied variables and areas
• Local Government Survey
• Pros
– Data gathered on consistent
basis
– Test and generate new
hypotheses
– Include broad variety of
contexts
• Cons
– Very low response rate
– No organisation would agree
to assist in distribution
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Expert Survey and stochastic-DEMATEL Analysis
• Pros
– More achievable than a local government survey
– Understand directionality and explore causal relationships
• Cons
– Less reliable and robust than a survey based on local government data
• Online survey distributed through social media
– Questions about relationship between CCPDRR model elements
– E.g. “How much does dispersion or concentration of political power
directly influence coordination of other organisations to reduce
disaster risk?”
– 49 quality controlled responses received
• Results analysed with stochastic-DEMATEL method
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Key Results
• Experts have wide
variance in opinions
• Context as influential as
Capacity
• All capacities have
similar levels of
importance
• Experts overstate
importance of Financial
Capacity, understate
importance of Policy
Context
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
More Research Needed
• Broader and larger expert survey on influences of local
government DRR
• Large, cross national survey of local governments
• Application of CCPDRR model to design of other large-N
studies of local governments and the development of case
studies
• More and more available cross-national data on local
governments that cover all context, capacity and performance
elements
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Thank you
ben@benbeccari.com
www.benbeccari.com
@casuscalamitas
Hinweis der Redaktion
Thanks for sticking around until the end today. This evening I’d like to present the main focus of my PhD research which I’m due to defend later this year.
We all know that local government are critical actors in DRR without which we can’t hope to reach the targets in the Sendai Framework. At this conference we’re hearing about many examples of local governments that are achieving great things in DRR – examples like preparedville…..
But we don’t often hear about cities like Wontappenere, or won’t happen here. Despite being superficially similar to Preparedville……
But what’s the difference – Why do some local governments have strong DRR action and others don’t.
To help answer this question I‘ve developed the Context, Capacity and Performance model of Local Government Disaster Risk Reduction
At a base level it consists of
Performance – Activities undertaken that reduce disaster risk
Capacity – The general and disaster specific resources that enable it to perform and determine its level of performance
Context – Those elements outside of a local government's organisation that influence its operation
The CCPDRR model does two things
Firstly it is..... Provides a taxonomy of these drivers and barriers.
Secondly it is......
Here is a scheme of the model and its components, with most of the relationships removed for clarity. I don’t have the time to go into all of these in detail, but the factors include the
Disaster context - disaster risk and recent disaster experience
Policy Context - levels of advocacy for DRR and central government DRR policies
Leadership Capacity - leader risk perception and commitment to DRR
Institutional Capacity - quality of governance, communication and risk perception
Core services – basic infrastructure and social services that reduce underlying risk and vulnerabilities
DRR Coordination - coordination of other organisations to reduce disaster risk
DRR Services - activities to reduce disaster risk using the local governments own resources
To expand on and validate this model I’ve explored a number of options to collect data:
Meta-analysis using latent variable modelling of existing datasets on local government DRR performance in the USA.
I contacted many organisations with access to large networks of local governments and none were willing to assist in distribution of the survey.
So I turned to using an expert survey on the relationships between the factors in the Context, Capacity and Performance Model of Local Government DRR
Now there are more experts than there are local governments and they’re more accessible. This, plus a shorter and easier survey increases the response rate and questions based on relationships themselves reduces the sample size requirement.
Examining expert opinion on the relationships between factors means that…..
Social media such as linkedin and facebook groups, twitter and the IAEM newsletter.
There were 139 questions in total with each respondent being presented with about 55 randomly selected questions with the option to answer more.
The stochastic DEMATEL method is a technique used to convert the opinions of large numbers of experts on the relationships between different factors into information on the importance and effect of those factors.
Experts have a wide variety of opinions – there was significant variance in the responses given.
The experts mostly considered the context factors to have similar influence on DRR performance as the capacity factors. This is counter to the CCPDRR model which hypothesises that the Capacity factors should have more influence.
Compared to the empirical literature there is a disagreement about the role of Financial Capacity with experts saying it is the second most important factor, whereas the empirical literature says it is one of the least important.
On the other hand experts say that Policy Context is the least important factor, whereas the empirical literature says it is one of the most important contextual factors.
These disagreements indicate that much more research is needed.
Broader survey to enable sub-setting of responses to compare the opinions of different groups to see how robust they are.
Implementation of the local government survey that I originally proposed would provide a much better test of the CCPDRR model and its hypotheses.
Greater application of the CCPDRR model to large sample size studies could enable future latent variable analyses and application to case studies could enable future Quantitative Case Analysis. Two systematic review techniques.
The lack of good data on local governments – especially cross-national data – is a big problem in the broader public administration literature. We need more investment in efforts to collect, collate and disseminate this data to researchers and the public alike. And we need much more investment, especially from multinational collaborations and the international community in efforts to gather this type of data.