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Are you interested in measuring community disaster resilience?

Our summary today works with the article titled Operationalising a concept: The systematic review of composite indicator building for measuring community disaster resilience from 2017 by A. Asadzadeh, T. Kötter, P. Salehi, and J. Birkmann, published in the International Journal of Disaster Risk Reduction. Since we are investigating the future of cities, I thought it would be interesting to see how to build indicators for an overarching community disaster resilience assessment. This article introduces an assessment framework to measure community disaster resilience while also investigating hierarchical, and inductive assessment methods.

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Welcome to today’s What is The Future For Cities podcast and its Research episode; my name is Fanni, and today I will introduce a research paper by summarising it. The episode really is just a short summary of the original paper, and, in case it is interesting enough, I would encourage everyone to check out the whole paper. Stay tuned until because I will give you the 3 most important things and some questions which would be interesting to discuss.

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The concept of community disaster resilience is becoming increasingly important within discourse on environmental changes. Community disaster resilience is frequently applied in response to multiple disasters at the community level and is used to promote proactive actions as well as the enhancement of inherent capacities instead of reactive responses. While resilience itself is a popular term, there is still considerable disagreement on its meaning in general or its operationalizability. Although the development of composite resilience indicators, also known as composite indices has been employed by disaster and resilience researchers, there is neither widely agreed standard procedure nor a comprehensive assessment of different measurement frameworks in the literature. To address these gaps, this paper aims to introduce a comprehensive standard procedure for developing composite indicators for operationalising community disaster resilience and to produce a quality assessment of current resilience measurement frameworks through the development of a meta-level framework.

While it is often argued that the term resilience was first formulised in the field of ecology, it has been used since the 16^th century. However, the debates around its meaning and connections to socio-ecological systems, sustainability, mitigation and adaptation, and more recently disaster risk reduction are still ongoing. Resilience is now considered to be a hot topic and carries similar influence to the weight of sustainability. Resilience, specially the concept of community resilience, encompasses the way in which communities face the increasing complexity and growing changes in global dynamics in order to better perceive, manage and govern complex socio-ecological systems, while also increasing their inherent capacity to cope with, adapt to, and shape change. Community resilience is best defined as a concept that enhances the ability of a community to prepare and plan for, absorb, recover from, and more successfully adapt to actual or potential adverse events in a timely and efficient manner. In episode 44 we investigated resilience from the community perspective, but now back to the article.

The first step toward community disaster resilience should be focused on understanding how it can be measured and operationalised. However, the measurement is only little empirically-based. Resilience is an abstract concept and it is difficult to quantify the concept in absolute terms. Hence, understanding the characteristics that contribute to resilience is a major milestone toward enhancing resilience and predisposes decision-makers, stakeholders, and other end-users to prioritise those actions that are needed to build and sustain resilience. Despite previous endeavours, the debate on the characteristics that contribute to resilience and transition from merely theoretical frameworks to empirical assessment of community resilience is ongoing.

Finding a standard procedure to develop indicators to measure community resilience as the first step is challenging. There are significant discrepancies in the conceptual orientations of different measurement approaches that view resilience as a process-oriented dynamic concept or a result-oriented, static concept. Another challenge is that each framework applies different procedure to composite indicator building with different data transformation and weighing for example. As a result, there is no universal procedure for operationalising the concept of community disaster resilience, and there is no quality assessment of composite indicators which has been accepted by a sufficient amount of scholars.

Therefore, this study deals with an ongoing challenge in the measurement of community disaster resilience. It compiles and introduces a synthesized procedure for composite indicator building to serve both as a guideline in operationalising community disaster resilience and a basis for developing a meta-level framework for quality assessment of existing measurement frameworks. The review aimed to understand the quality of current resilience measures that can be used to identify weaknesses and limitations of current disaster resilience measures and to improve them where needed, in order to meet the risk preparation and planning needs of stakeholders, decision-makers and urban planners.

The authors established an 8-step procedure for composite indicator building: theoretical comprehensiveness, data transformation, multivariate assessment, weighting, aggregation, visualisation, and validation. They also chose 17 indices and tools to establish the composite indicator building procedure. Most of these frameworks belong to the socio-ecological resilience topic since the focus of this study is on community disaster resilience approaches, while the remaining ones were connected to field of engineering. To assess the comprehensiveness of these frameworks, first it was necessary to define dimensions and sub-dimensions, like metrics for quality assessment. The authors agreed on 19 dimensions and 36 metrics based on their literature review. Then they scrutinised and reviewed the selected frameworks with these dimensions and metrics, and tried to answer the fundamental questions of why resilience, resilience for when, and resilience of what.

The review revealed answering the why question that engineering-based frameworks tend to view resilience as bouncing back to the same condition, being result-oriented and achieve a certain outcome, whereas most of socio-ecological based measures focus on adaptive capacity building or enhancement in order for effective response, adaptation to new conditions, and learning from previous events, being process-oriented. Rare were the cases where both approaches appeared.

Disaster resilience assessments can measure persistence and robustness, recovery and constancy, and adaptive and transformative capacity, answering the when question. The result-oriented approaches usually focus on quantifying short-term persistence levels of communities, the process-oriented frameworks concentrate on measuring long-term adaptive capacities of case study areas. When the primary goal is to build resilience to short-term disturbances, the focus is on the pre-event conditions of communities, like persistence and recovery levels. Whereas the objective in long-term analysis is post-event conditions and assessing the capacity of communities elements to learn from and respond to upcoming changes.

The review showed that the answer to the questions of resilience to or of what is mostly earthquakes and multiple hazards. While the dynamic tools measure the capacity or potential performance of communities, the static indices focus on evaluating the unique quantities or attributes within communities to bounce back rapidly from an adverse effect. It was also a question of resilience for whom. This often depended on the target layer of measures and whether the measures intend to enhance the resilience of individuals, specific groups or communities.

Moreover, the review also reveals considerable overlap between some of the indicator sets because the vast majority of these frameworks have been developed deductively and similar to hierarchically rather than inductively. Because deductive methods are based on teamwork skills, there is some initial collaboration among experts and group members and such, this overlap is ensued. In addition, it has been proved that the selected assessments have mainly been developed based on non-participatory and top-down methods. Those measures that employ a participatory, bottom-up approach for measuring resilience can subsequently develop a simple assessment as a benchmarking tool for better understanding of capacities and assets, and can also engage stakeholders. Interestingly, the investigated indices and tools utilise the validation step less frequently, becoming less reliable. Therefore, further measures need to test their results and examine how reliably a framework has measured the concept of disaster resilience in an empirical application.

A valid set of composite indicators should start with the development or application of a sound theoretical foundation for operationalising the term resilience as well as a basis for primary indicator building. The theoretical background of disaster resilience measure can be distinguished based on their answer to why resilience, resilience of when, resilience of what and for whom. The distinction between process-oriented dynamic and result-oriented static approaches characterise the literature to date. Resilience measure are also categorised as to whether they are measuring persistence and robustness, recovery and constancy, and adaptive and transformative capacity conditions, or on the timeframe of resilience. These are major challenges for disaster resilience measurements since the development of primary indicators for analysing resilience is heavily depend on assumptions about resilience for whom what and when.

Above all, we need to consider that we employ disaster resilience measures to deepen our perception of resilience as well as to understand the interventions that are needed to build and sustain it. We know that disaster resilience measurements cannot spontaneously make a community resilient, but they can be considered as the key step toward disaster risk reduction, planning and management.

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What was the most interesting part for you? What questions did arise for you? Do you have any follow up questions? Let me know on Twitter at WTF4Cities or on the wtf4cities.com website where the transcripts and show notes are available! Additionally, I will highly appreciate if you consider subscribing to the podcast or on the website. I hope this was an interesting paper for you as well, and thanks for tuning in!

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Finally, as the most important things, I would like to highlight 3 aspects:

1. Measuring community disaster resilience has its challenges, for example, based on its theoretical background, dynamic and static approaches, and answers to the fundamental questions of why resilience, and resilience of what, when and for whom.
2. It seems important to involve all stakeholders in the establishment of the measurements creating agency and empowerment over the measures themselves.
3. More measurements, frameworks, indices and metrics need to incorporate the validation phase to create reliable outcomes.

Additionally, it would be great to talk about the following questions:

1. What does resilience mean to you? Where do you put resilience? Is it independent? Is it connected to something? Is it part of something, like sustainability?
2. What do you think, how resilient are you as an individual?
3. What do you think, how resilient is your community?

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