23 July 2012
WORKING PAPER Work Package 1 Systematization of Different Concepts, Quality Criteria, and Indicators Deliverable 1.2
Authors Joern Birkmann
UNU-EHS
Denis Chang Seng
UNU-EHS
Thomas Abeling
UNU-EHS
Nazmul Huq
UNU-EHS
Jan Wolfertz
UNU-EHS
Nuray Karanci
METU
Gözde İkizer
METU
Christian Kuhlicke
UFZ
Mark Pelling
KCL
John Forrester
SEI
Maureen Fordham
UoN
Hugh Deeming
UoN
Sylvia Kruse
WSL
Sebastian Jülich i
WSL
Contract Number: 283201 Project Acronym: emBRACE Title: Building Resilience Amongst Communities in Europe
Deliverable N°: 1.2 Due date: 2012-07-20 Delivery date:2012-07-31 Short Description: This paper deals with the systematization of different concepts, quality criteria and the identification of components as well as indicators of resilience. The central aim is to review how resilience is assessed and operationalized in existing studies of resilience. We showcase selected studies that have proposed frameworks and indicators to measure social-ecological, psychological, organizational and institutional, critical infrastructure and practical, community-based examples of resilience. A set of key components of resilience is presented.
Lead Beneficiary: United Nations University – Institute for Environment and Human Security (UNU-EHS) Partner/s contributed: UNU-EHS, METU, UFZ, KCL, SEI, UoN, WSL Made available to: 2012-07-25
Version Control Version
Date
Name, Affiliation
0.1
12-06-12
Joern Birkmann (UNU-EHS)
0.2
12-07-12
Denis Chang Seng (UNU-EHS)
0.3
20-07-12
Joern Birkmann (UNU-EHS)
Acknowledgements Funding for this report was made available by the European Commission under the 7 th Framework Programme – Grant Agreement No 283201.emBRACE
Contact:
Technical Coordination (Administration)
Centre for Research on the Epidemiology of Disasters (CRED) Institute of Health and Society Université catholique de Louvain 30 Clos Chapelle-aux-Champs, Bte 30.15 1200 Brussels Belgium T: +32-2-764.33.27 E:
[email protected] W: www.cred.be
Technical Coordination (Science)
School of the Built and Natural Environment, University of Northumbria Newcastle upon Tyne NE1 8ST, UK T: + 44 (0)191 232 6002 E:
[email protected] W: www.northumbria.ac.uk
Information given in this emBRACE Working Paper Series reflects the author’s views only. The Community is not liable for any use that may be made of the information contained therein.
3
About emBRACE The primary aim of the emBRACE project is to build resilience to disasters amongst communities in Europe. To achieve this, it is vital to merge research knowledge, networking and practices as a prerequisite for more coherent scientific approaches. We will do this in the most collaborative way possible.
Specific Objectives Identify the key dimensions of resilience across a range of disciplines and domains Develop indicators and indicator systems to measure resilience concerning natural disaster events Model societal resilience through simulation experiments Provide a general conceptual framework of resilience, tested and grounded in crosscultural contexts Build networks and share knowledge across a range of stakeholders Tailor communication products and project outputs and outcomes effectively to multiple collaborators, stakeholders and user groups
The emBRACE Methodology The emBRACE project is methodologically rich and draws on partner expertise across the research methods spectrum. It will apply these methods across scales from the very local to the European. emBRACE is structured around 9 Work Packages. WP1 will be a systematic evaluation of literature on resilience in the context of natural hazards and disasters. WP2 will develop a conceptual framework. WP3 comprises a disaster data review and needs assessment. WP4 will model societal resilience. WP5 will contextualise resilience using a series of Case studies (floods, heat waves, earthquakes and alpine hazards) across Europe (Czech Republic, Germany, Italy, Poland, Switzerland, Turkey and UK). WP6 will refine the framework: bridging theory, methods and practice. WP7 will exchange knowledge amongst a range of stakeholders. WP8 Policy and practice communication outputs to improve resilience-building in European societies.
4
Partners
Université catholique de Louvain (UCL) - Belgium University of Northumbria at Newcastle (UoN) - UK King’s College London (KCL) - UK United Nations University Institute for Environment and Human Security (UNU), Germany Accademia Europea per la Ricerca Applicata ed il Per-fezionamento Professionale Bolzano (EURAC) - Italy Helmholtz-Zentrum Fuer Umweltforschung GMBH - UFZ (UFZ) - Germany University of York (SEI-Y) - UK Stockholm Environment Institute - Oxford Office Limited (SEI-O) - UK Swiss Federal Institute for Forest, Snow and Landscape Research - WSL (WSL) Switzerland Middle East Technical University - Ankara (METU) - Turkey
5
Table of Contents 1.
Summary ............................................................................................................................. 7
2.
Introduction ....................................................................................................................... 12
3.
Finding Common Ground: The Systematization of Indicators and Criteria ..................... 15
4.
Examples of Indicators and Criteria Used to Assess Resilience ..................................... 16 4.1.
Ecological and Social-Ecological Resilience............................................................. 16
4.2.
Psychological Resilience ........................................................................................... 21
4.3.
Critical Infrastructure Resilience................................................................................ 29
4.4.
Organisational and Institutional Resilience ............................................................... 32
4.5.
Practical Perspectives of Resilience (Community) ................................................... 41
5.
Components of Resilience ................................................................................................ 50
6.
Discussion of Key Findings, Challenges and Gaps ......................................................... 53 6.1.
Key Insights from the Systematization ...................................................................... 53
6.2.
Gaps and Challenges ................................................................................................ 54
7.
Conclusion and Recommendations .................................................................................. 56
8.
References ........................................................................................................................ 58
6
1.
Summary
This Working Paper 1.2 of the emBRACE project deals with the systematization of different concepts, quality criteria and the identification of components as well as indicators of resilience. The key aim is to review how resilience is assessed and operationalized in existing studies by drawing on the literature review of resilience research provided in emBRACE Working Paper 1.1 (emBRACE, 2012), and additional recent sources and publications on frameworks and indicators for assessing community resilience. The development of criteria to assess indicators of resilience is guided by the objective of contextualizing indicators within the different schools of thought existent in the literature, such as social-ecological resilience or psychological resilience, to name but two. The systematization of different concepts and indicators is based on the following categories: a) hazard/phenomenon, b) dimension scale, c) phases/context, d) component (of resilience), e) indicator and measurement of resilience. A definition for each of these terms is provided in section two. We show selected examples of studies that have proposed frameworks and indicators to assess social-ecological, psychological, critical infrastructure, organizational and institutional and community-focused resilience. Key findings from the systematization of indicators from five different schools of thought suggest the following: Social-Ecological Resilience Indicators for understanding and assessing social-ecological resilience vary with regard to their hazard context. While some indicators are provided independent of a particular hazard, others are hazard dependent, focusing, for example, on heat stress. In a hazard independent context, the indicators were presented in four stages: (1) (re)organization, (2) growth, (3) conservation, and (4) release. These reflect the four phases of the adaptive cycle. Each of the stages has its own set of resilience components. The characteristics of each component are defined by a set of indicators. Although all the indicators are equally important in defining social-ecological resilience, some of the indicators occur more frequently in the literature. The most prominent indicators and characteristics are: learning, sharing, re-organization, preservation of knowledge and resources, diversity, human capacity, and information and networking. Apart from these indicators, context specific indicators are also available to assess specific characteristics of the resilience components. Traditional knowledge management, for example, is an important indicator for agro-ecosystem resilience while the availability of funds and experiments appear prominently in studies that measure resilience to heat stress. The spatial context of resilience indicators is as yet unaddressed in studies that measure socialecological resilience. This is surprising, as the spatiality of measurement approaches defines the intrinsic values of indicators. Psychological Resilience We provide thirteen examples of key indicators used for assessing psychological resilience. These are drawn from the studies of Gillard & Paton (1999), O’Leay (2004), Norris et al. (2008), Bonanno (2009), and Mancini & Bonanno (2009). The key indicators include: (1) individual socio-demography, (2) individual resources, (3) community resources, (4) preparedness and mitigation, (5) social support, (6) personality, (7) spirituality, (8) disaster impact se7
verity, (9) disaster experiences, (10) coping appraisals, (11) positive adjustment, and (12) positive emotions. Critical Infrastructures Resilience Studies trying to assess the resilience of critical infrastructure include the Bruneau et al. (2003), and Boin (2007). Key indicators that are closely linked to the discussion of infrastructure resilience in the literature include: robustness, rapidity, redundancy, and resourcefulness. It remains to be examined, however, how exactly critical infrastructure relates to the resilience of the communities. Organisational and Institutional Resilience Organizational and institutional resilience seems to be predominantly operationalised independently from a specific hazard or phenomenon. As a consequence, the accuracy of information on the scale of measurement and the stage/context of the measurement remains rather broad. The specific indicators reveal the conceptualization of organizations and institutions as limited, closed entities of a larger system. Most of the indicators attempt to describe the ability of individual organizations to withstand shocks and to re-organize and learn after a shock has occurred. This implicit definition of organizations as autonomous, individual elements in a larger system risks undermining a broader conceptualization of both organizations and institutions as spatially-unbound elements of a system as a whole. This rather significant gap in research deserves further exploration. Finally, the preoccupation of indicator approaches with preparedness seems to be prominent. Measurements and indicators of organizational and institutional resilience are predominantly trying to assess the preparedness of organizations and institutions. They thus risk overemphasizing the importance of preparing for disturbances, which inherently necessitates arbitrary assumptions on the magnitude and frequency of shocks. This undermines a focus on flexibility and the notion of living with uncertainties, which would reflect current resilience discourses in the literature more accurately. Practical Perspectives We focus our attention on four examples of practical perspectives on resilience, including two from grey literature, which was found to be focused more explicitly than academic literature on measuring community resilience. The frameworks and approaches presented in these studies can thus inspire the development of a framework for community resilience in the emBRACE project. The first example (Twigg 2009) explores dimensions of resilience, which are organized under the thematic headings of planning, regulation, integration, institutional systems, partnerships and accountability. These represent the main areas of Disaster Risk Reduction (DRR) interventions, based on a framework developed by the UN International Strategy for Disaster Reduction (UNISDR 2005): the Hyogo Framework for Action 2005-2015 (HFA). Characteristics set out in this study represent an ideal state of resilience in quite general terms, which therefore could be said to relate equally to developed and developing world contexts. The second practical example discussed in this Working Paper draws on the work of the International Federation of the Red Cross (IFRCRCS 2008). It outlines a framework for community safety and resilience. The Framework links closely with the 5 HFA priorities. The framework’s objective is to “establish a foundation on which all Red Cross Red Crescent programmes, projects and interventions in DRR and all actions which contribute to the building of safe and resilient communities can be created, developed and sustained” (IFRCRCS 8
2008: 2). Within this framework, resilient communities are perceived to: a) understand disaster risks, assess and monitor these and protect themselves to minimize losses and damage when a disaster strikes, b) be able to maintain basic community functions in times of disaster, c) build back after a disaster and work towards ensuring that vulnerabilities continue to be reduced for the future, d) understand that building safety and resilience is a long-term, continuous process that requires on-going commitment, and to e) be aware that being resilient increases chances to meet development goals. It is the IFRCRCS’s contention that more safety and resilience means less vulnerability. The framework is based on the understanding that building safety and resilience is a long-term, continuous process that requires ongoing commitment. In the face of such unknown factors as the effects of climate change, the degree of urban growth or environmental degradation, the study outlines that there is much that can be done to adapt to future problems and challenges by building on the current knowledge of communities. Interestingly, the IFRCRS emphasizes that resilient communities appreciate the fact that being safe and disaster resilient means that there is a greater chance of meeting development goals, which in themselves will greatly add to safety and resilience. The third practical example is drawn from the work of Cutter et al. (2010). The authors challenge Bruneau et al.’s (2003) critical-infrastructure focussed definition because the “operational framework ignores the dynamic social nature of communities and the process of enhancing and fostering resilience within and between communities” (Cutter et al., 2010: 2). The authors underline the importance of evaluating and benchmarking the baseline conditions that lead to community resilience and of measuring the factors contributing to adverse impacts and to the diminished capacity of a community to respond to and rebound from an event. In this example resilience is considered as a multifaceted concept, which includes social (e.g. age, transportation access, telephone access, language competency), economic (e.g. housing capital, employment, income and equality, health access), institutional (e.g. mitigation, insurance, experience), infrastructural (housing type, shelter capacity, medical capacity, evacuation potential’), ecological, and community (place attachment, political engagement, social capital, religion, civic involvement, advocacy) elements and indictors. However, a key weakness of the comprehensive and holistic approach by Cutter et al. (2010) is the reliance on national data sources, which are often out of date and inadequate for characterizing local resilience. Furthermore, Cutter at al. largely exclude environmental or placebased indicators and therefore fail to offer a comprehensive assessment of ecological dimensions of community resilience. The fourth practical example discussed in this Working Paper focuses on the work of Norris et al. (2008). The study finds that community resilience emerges from four primary sets of adaptive capacities or components: (1) economic development, (2) social capital, (3) information and communication, and (4) community competence. According to the authors, these capacities, when taken together, provide a strategy for disaster readiness. In the study, communities are perceived to be composed of built, natural, social, and economic environments that influence one another in complex ways. Norris et al. suggest that post-disaster community health depends in part on the effectiveness of organizational responses, and ultimately the purpose of disaster management is to ensure the safety and well-being of the public. The key indicators proposed in the study include: (1) resource volume and diversity, (2) resource equity and social vulnerability, (3) network structures and linkages, (4) social support, (5) community bonds, roots, and commitments, (6) systems and infrastructure for informing the public, (7) communication and narratives, (8) collective action and decisionmaking, and (9) collective efficacy and empowerment.
9
To identify key components of resilience and their associated sets of indicators, section three attempts to overcome the somewhat arbitrary divide of approaches to measure resilience between different disciplines and schools of thought. To identify key components of resilience, we draw on feedback from experts involved in the emBRACE case studies, on a systematic review of the prominence of individual components in the studies presented in this Working Paper as well as on the focus of individual components of community resilience, in particular. Overall, we have identified and listed 81 components of resilience. Out of these, fifteen main components of resilience have been synthesised. These are: 1. Governance (Actors, Institutional Arrangements, Organisations) 2. Education, Research, Awareness and Knowledge 3. Information and Communication 4. Culture and Diversity 5. Preparedness 6. Response 7. Protection 8. Exposure, Experience and Impact Severity 9. Resources 10. Infrastructure and Technical 11. Health and Well Being/ Livelihood 12. Economic 13. Adaptive Capacity 14. Coping Capacity 15. Innovation and Capital In section four we discuss the key insights as well as gaps and challenges arising from the assessment and systematization of indicators. We find that often different indicators are used to assess the same components of resilience. Furthermore, a large set of sub-components of resilience is situated in the governance (actors, institutions, organizations) component. Gaps and challenges include the complexity and ambiguity of the resilience concept, the disturbance–stress context which underlines the necessity to define the perturbation of interest (“resilience to what?”), the interaction between dimensions and components of resilience, the ambiguity of the community concept within resilience research, as well as the difficulties in identifying quantifiable measurements of resilience. Based on the assessment, systematization, and evaluation of this Working Paper, we formulate the following recommendations for the development of a theoretical framework within the emBRACE project: -
Elaborate on the concepts of community and community resilience. The five types of community outlined in emBRACE Working Paper 1.1 (geographical communities, communities of interest, communities of circumstance, communities of supporters, and communities of identity) can serve as a basis for such an endeavor.
-
Define guiding questions for the framework, for example on what the most important systems, subjects or objects at risk are. Moreover, also identify the key perturbations or stressors (e.g. natural hazards) the case study deals with. This process should al-
10
so be influenced by and reflected against the background of the empirical work to be conducted in the case-studies (WP5)1. -
Apply the core components of resilience identified in this Working Paper to the system, subject or object of analysis within the community.
-
Explore the interactions between and within the identified main and sub-components of resilience and their respective sets of criteria and indicators.
-
Reflect on the role of the key components of resilience, identified in this Working Paper, in developing the theoretical framework. Innovation, for example, is identified as a key component in resilience despite a lack of sufficient information and examples about the role of innovation in building resilience.
-
Focus on key components and indicators developed in a natural hazard context rather than on those drafted in non-natural hazard contexts.
-
Pay adequate attention to the interactions and impacts of the key components in order to facilitate and accommodate all the indicators according to their disciplinary merit and importance.
1
There are five case studies in the emBRACE project. These are river floods in Central Europe (Germany, Poland, Czech Republic), earthquakes in Turkey, multiple hazards in South Tyrol, Italy and Grisons, heat waves in London, and combined fluvial and pluvial floods in Morpeth. For further information see emBRACE website at http://embrace-eu.org/casestudies/casestudies.htm. 11
2.
Introduction
Can resilience be measured2? As emBRACE Working Paper 1.1 has shown, the concept of resilience is applied in various disciplines and contexts (see also different schools of thought shown above). In the literature review for this project, we have analyzed the conceptualization of resilience from psychological, ecological and social-ecological, organizational and institutional, critical infrastructure, as well as practical perspectives. It has been shown that, despite its popularity in political and policy cycles, the concept of resilience remains ambiguous. Its analytical usefulness often suffers from the terminological ambiguity that characterises its application in different contexts. Approaches to conceptualize resilience differ in particular with regard to their stated goals, their defined system of interest, the scale of analysis, the hazards or phenomena identified as triggering events, as well as to their proposed mechanisms to identify resilience (emBRACE 2012). What does this conceptual vagueness, identified in WP 1.1, mean for the application of resilience in practical terms? Is resilience a concept with empirical identity? If so, how is it operationalised and measured? And what can we learn from the applications that exist? This Working Paper 1.2 addresses these questions by examining indicators and criteria of resilience. Objectives of the Working Paper This paper aims to identify and systematize resilience indicators that have been used in the literature to assess resilience. To do so, the paper surveys existing approaches to measure and assess resilience with quantitative and qualitative indicators at various scales and through various tools, and compares them across a series of key dimensions. Given the definitional and contextual differences, a systematization of different indicators, quality criteria and components of resilience can serve as a useful heuristic tool to facilitate a comparison and common understanding of approaches across disciplines. Furthermore, the systematization of indicators of resilience across disciplines aims to provide first insights into key components of community resilience to natural disasters. Which characteristics of resilience appear frequently in the literature and in various disciplines? Which resilience indicators and criteria are particularly useful for a community perspective? Which indicators can potentially inform emBRACE case studies? Based on the comparison of concepts, quality criteria and indicators, this paper offers a first step towards overcoming the disciplinary divide that characterises resilience research. In filtering key components of resilience, the paper bridges emBRACE Work Packages 1 and 2 and provides key information for the development of a theoretical framework for community resilience to natural disasters. Challenges in Measuring Resilience The question “Can we measure resilience?” immediately raises another, more fundamental question: “What is resilience?” This latter question has been addressed in emBRACE Working Paper 1.1. As the literature review in Working Paper 1.1 has shown, resilience is a theoretical construct with various, often divergent conceptualizations. Therefore, the notion of 2
Throughout the document, the terminology of “measuring” and “assessing” resilience will be used interchangeably, referring broadly to all those approaches that attempt to give the concept an empirical meaning. The terminology used in this document is not intended to imply a definite answer to the question of whether resilience can be measured. This remains to be explored throughout the emBRACE project. 12
measuring resilience is contested. Due to its ambiguous character, it seems more appropriate to ascertain resilience by proxy properties that represent the processes and properties of the concept. This effort is complicated by the ambiguity that surrounds resilience research, which poses a series of challenges that make the concept particularly difficult to grasp empirically. The following section outlines some of these challenges. The ability to measure resilience critically depends on the underlying conceptualization and the epistemological background that guides the analysis. One of the most fundamental challenges in measuring resilience thus arises from the significant evolution of the concept. Current understandings of resilience focus on re-organization and learning and are much more dynamic than traditional, ecology-based approaches that merely consider the ability to withstand shocks. Perceiving resilience as a process rather than an outcome undermines some of the popular previous attempts to measure resilience. One of the most influential attempts to introduce a methodology for giving resilience an empirical identity is based on an outcome-focused understanding of resilience. The study of Carpenter et al. (2001) develops an approach that aims to define the system state of interest (resilience of what?) and the perturbations against which this system state might be resilient (resilience to what?). The focus on ecosystems allows for a rather accurate approximation of the resilience state and the stressor of interest and for a quantification of these. Drawing on these data, the authors demonstrate that it is possible to determine thresholds of different system states (e.g. clear water vs. turbid water state for agricultural lake systems) and to measure resilience as the distance between two attractor states. The cornerstone of this conceptualization is a static perspective that defines resilience as the ability to resist shocks and remain in the same state. This facilitates attempts to measure resilience, as it allows the researcher to focus on a clearly definable system with quantifiable boundaries and thresholds. The picture becomes more complicated when resilience is not primarily conceptualized as an outcome or characteristic, in the sense of a systems ability to absorb shocks without fundamentally changing state. Resilience theory is increasingly focusing on more dynamic conceptualizations of the concept, which highlight re-organization and learning in response to feedbacks as crucial elements of a resilient system. Heuristic tools such as the adaptive cycle, but also the notions of adaptive capacity and panarchy demonstrate the increasing process orientation of resilience thinking. This has fundamental consequences for operationalising the concept and giving it empirical identity. When resilience is primarily about change and transformation, then new challenges arise for assessing it. How can we measure and quantify change in systems if these systems are flexible and constantly re-shaped? Are transformations which affect resilience always observable? When dealing with social systems, such as communities, measuring resilience faces additional difficulties. Here, systems and system state often cannot be clearly identified. Even if this is possible, the approximation of resilience in social terms appears to be a very challenging task, with data availability being only one out of many problems. What constitutes a social system and on which grounds is it defined? What sub-systems are crucial elements of the social system? How do these sub-systems affect the resilience of the overall system? What does it mean if we make the pre-analytical decision to define society as a system and not as a group of actors sharing the same inter-subjective understanding of reality? Answering these questions is a challenging task and only a prerequisite for assessing any sort of societal resilience. 13
Moreover, when attempting to assess resilience, questions of temporal and spatial scale arise. When resilience is perceived as a process of change and transformation, it becomes apparent that the concept cannot be assessed at a certain point in time. Measuring resilience thus requires longitudinal data over a period of time. This challenges the researcher to define and justify timeframes in which the transformations of interests can be appropriately captured. The same holds for scalar analysis. If it is indeed possible to observe resilience, at what scale can we do so? Here, the interaction of subsystems across time and scales plays an important role. It has been shown that increasing the resilience of some parts of a system at a certain scale can reduce adaptive capacity at others (Harrison 2003). These scalar and temporal linkages are just some of the complexities that need to be considered when attempting to assess resilience. Finally, a fundamental challenge of assessing resilience is to answer the question of why this is intended in the first place. Assessing resilience can be motivated by academic as well as by normative purposes, for example. Depending on these, different approaches to the development and specification of indicators might be taken. For analytical reasons, researchers might be interested in gaining a better understanding of how different actors (e.g. individuals, organizations, and communities) frame, understand and define their resilience. The motivation for such an approach could stem from the assumption that gaining answers to these questions allows for a more comprehensive assessment of the system of interest. For drawing causally valid inference, this specific research interest would require robust and measurable indicators. However, if the interest in measuring resilience stems from normative reasons, qualitative indicators or even narratives might be more appropriate to assess resilience. These narratives could, for example, identify groups that are less resilient than desired by the subjective perception of the (activist) researcher, helping him to make the case for stronger support for them. Being explicit about the motivations for and objectives of measuring resilience is critically important for a scientifically valid approach.
14
3.
Finding Common Ground: The Systematization of Indicators and Criteria
This section outlines the descriptive pattern that is applied to the various indicators identified in the literature. The development of criteria to assess indicators of resilience is guided by the objective of contextualizing indicators that have already been developed and applied throughout the literature. The aim of applying a coherent structure to all indicators is to allow for their comparison. Table 1 outlines the systematization of resilience indicators across disciplines. Table 1: Overview of categories, their explanations and examples for the systematization of indicators
Explanation
Example
Hazard/ Phenomenon Specifies the phenomenon and the stressor that challenges resilience
Heat stress, flood, earthquake, trauma, etc.
Dimension
Scale
Phases/ Context
Component
Indicator/Criteria
Measurement
Specifies the disciplinary /thematic background of the indicator development for resilience. It classifies resilience approaches according to our themes/groups Psychological, socialecological, critical infrastructure, institutional and organizational
Specifies the spatial and/or temporal unit of analysis on which the indicator is used Often similar to the unit of analysis
Indicates the position of the indicator in different stages or phases within a given cycle and particularly the disaster management cycle (pre-or post disaster focus).
Classifies the indicandum, what should be assessed with the indicator, criteria
An indicator can be defined as the measurement of an indicandum. An indicator quantifies an element considered to be relevant to the measurement, monitoring or evaluation of resilience. Criteria indicate a qualitative assessment and measurement of a characteristic of resilience.
Defines the specific procedure of measurement used within the indicator
Regional, national, community, business, household, individual temporality of indicator, i.e. slow/rapid changes expected in indicator values
Disaster Management Cycle: mitigation, preparedness, response, and recovery Further options include a systematization of pre-and post disturbance/shock/disaster events
adaptive capacity, redundancy
For example, an indicator for heat stress resilience from an engineering dimension might be the extent of green space of a city, as green space often has a cooling effect. An example of a criterion of resilience is the ability of disaster risk management organizations to reflect on practice outcomes.
The measurement of green space in the city includes tree cover in percentage of the city, number of parks in the city and area of green roofs in the city
15
4.
Examples of Indicators and Criteria Used to Assess Resilience
In this section, we contextualize and systematize examples of indicators and criteria that have been used in the literature to measure resilience. The systematization builds on the different dimensions of resilience that have been reviewed in Working Paper 1.1 and the case studies of the emBRACE project. Moreover, it is important to acknowledge that some approaches and areas of resilience apply quantitative indicators to assess resilience, while in other areas, such as psychological resilience, issues such as emotions are captured using qualitative indicators or criteria. In this document we summarize qualitative criteria and quantitative measures as indicators.
4.1.
Ecological and Social-Ecological Resilience
In this section, we present some of the key indicators for understanding and assessing social -ecological resilience. The indicators are contextualized according to their specific hazard context, for example hazard independent (example 1), heat stress (examples 2&3) and flooding (example 4). Most of the studies reviewed in this section classify indicators in four stages associated with the adaptive cycle: (re)organization, growth, conservation and release. Although all the indicators are important to define social-ecological resilience, some of the indicators are frequently repeated in the studies under review here. For example, learning, sharing, organization, preservation of knowledge and resources, diversity, human capacity, information and networking are common indicators. Apart from these, context specific indicators define specific characteristics of resilience components. Traditional knowledge management, for example, is an important indicator for agro-ecosystem resilience, whereas availability of funds and experiments are important indicators for heat stress. The studies reviewed in this section seem to neglect, however, the spatial context of resilience indicators. This context is particularly relevant as it defines the intrinsic values of indicators (Cumming 2011). Developing a spatial set of resilience indicators presents a key challenge for future approaches to measure resilience.
16
Example 1: Cabell, J. F. &Oelofse, M. (2012): An Indicator Framework for Assessing Agroecosystem Resilience. Ecology and Society 17(1) Hazard/ Phenomenon Hazard independent
Dimension
Scale
Phases/ Context
SocialEcological Resilience
Community: village and surrounding agricultural production sites (Agro-ecosystem)
Reorganization – anticipatory and in response to a hazard
Component
Indicator/Criteria
Measurement
Socially SelfOrganized
-Ability to organize
Not provided
Coupled with Local Natural Capital
-Building organic matter
Not provided
-Recharge of natural resources
Not provided
-Collaboration and knowledge sharing -Existence of learning groups, institutes -Proper maintenance of the resource
Not provided Not provided
-Providing habitat for predators and parasitoids
Not provided
-Production with local ecological parameters -Collaboration with multiple suppliers, outlets, and fellow people -Crops are planted in polycultures -Patchiness on the farm and across the landscape -Mosaic pattern of managed and unmanaged resources -Diverse production and management practices -Little reliance on commodity markets
Not provided
-Strong sales to local markets -Reliance on local resources -Heterogeneity of features
Not provided Not provided Not provided
-Diversity of inputs, outputs, income
Not provided
Reflective and Shared Learning -Ecologically SelfRegulated Growth/ Exploitation to Conservation
Appropriately Connected
Spatial and Temporal Heterogeneity Globally autonomous/ locally interdependent
High Degree of Functional and Response Diversity Conservation/
17
Not provided
Not provided Not provided Not provided Not provided
Not provided
Throughout
Builds Human Capital
Reasonably Profitable
Optimally Redundant Hazard independent
SocialEcological Resilience
Community: village and surrounding agricultural production sites (Agro-ecosystem)
Release
Carefully Exposed to Disturbances Honours Legacy
18
sources, markets etc. -Programs for preservation of local knowledge -Investments in infrastructure and institutions for the education of children and adults -Support for social events among communities -Farmers and Workers earn a liveable wage -Sectors does not rely on distorted subsidies Farmers maintain plant cover
Not provided Not provided
Not provided Not provided Not provided Not provided
-Capturing resources (soil, water) from various sources
Not provided
-Keeping equipment for various crops (Y/N) -Planting multiple varieties of crops rather than one -Getting nutrients from various sources -Mosaic of plant and animal communities in various stages of succession -Maintaining and use of traditional knowledge -Incorporation of traditional techniques with modern knowledge
Not provided Not provided Not provided Not provided Not provided Not provided
Example 2: Mayor of London (2010): The Draft Climate Change Adaptation Strategy for London. Public Consultation Draft. Greater London Authority Hazard/ Phenomenon Heat Stress
Dimension
Scale
SocialEcological Resilience
Community: City of London
Phases/ Context
Component
Indicator/Criteria
Not specified
Not specified
-Detailed Information on Micro-Climate
-Network of weather stations across the city
-Green Space
-Tree cover in % of the city -Number of hectares of green space in the city Green roofs in m -Published design guide for architects and developers to reduce risk of overheating -Not specified
-Public Advise
-Stable Energy Supply
Social learning
Measurement
-Heatwave Refuges
-Number of publicly accessible cooled buildings
-Ability of Policy and Implementing Agencies to Reflect on Practice Outcome
-Presence of mechanisms to update and improve practices
Example 3: Zaidi, R. and Pelling, M. (2011): Vulnerability to Drought and Heat Wave in London: Revealing Institutionally Configured Risks. Handbook of Vulnerability Assessment in Europe. MOVE handbook compendium Hazard/ Phenomenon Heat Stress
Dimension
Scale
Phases/ Context
SocialEcological Resilience
Community: City of London
Adaptive Governance
Component
Indicator/Criteria
Social learning
-Support for Experiments
Self-organization
-Availbility of resources (Funds) for Flexible Vulnerability Management
Measurement
-Degree of flexibility within the risk management system to support adaptive learning and experimentation -Shifts in budget allocation to risk management system
Example 4: J. Forrester, Liz Oughton, Chris Spray , Louise Bracken (under review): “Why Multi-level, multi-method, participatory understandings are necessary for managing complex environmental problems” 19
Brian Cook et al (under review): “Competing paradigms of flood management in the Scottish/English border: grappling with sustainability” Bracken et al (forthcoming): “Adaptive flood management: practices in borderlands” Hazard/ Phenomenon
Dimension
Scale
Flooding (fluvial)
Socialecological resilience with economic sustainability
Multi-level & maybe legislation (needs planning by individual land managers and also up/downstream catchment coordination)
Coastal Flooding / Ecosystem Service
Socialecological resilience
Flooding / Ecosystem Service
Socialecological resilience
Coastal Flooding (but applies elsewhere)
Social and economic
multi-level (needs planning by individual littoral land owners and land managers but also a higher-level planning/understanding) multi-level (needs planning by individual riparian land owners and land managers but also a higher-level planning/understanding) multi-level (cannot be instituted by individual communities but only possible with higherlevel intervention)
Phases/ Context
Measurement
Component
Indicator/Criteria
Planning for flood adaptation
-Coordination, compensation
-There is a system in place whereby those who put Natural Flood Management (NFM) measures in place upstream are not economically penalised for protecting others downstream
Planning for flooding
-Coordination
-Appropriate land, coastal land usage for flood protection (e.g. in Indian Ocean mangroves and their roles as a flood barrier but other examples are possible, e.g. with certain types of alpine land usage)
Planning for flooding
-Coordination
-The appropriateness of riverside land usage for flood protection
-Agreement between neighbouring land owners and land managers. High-level planning.
Flood preparedness
-Insurance
-Insurance – or lack of it – is a major problem for those who suffer flooding, often leading to people inappropriately staying in situ to protect property
-Realistic, affordable insurance for those in need.
20
-Area of land under NFM measures but also whether there is a (single) coordination body responsible (e.g. see http://www.tweedforum. org/). Ultimately, though, the measure is whether there is a drop in the hydrograph. -Agreement between coastal and neighbouring land owners and land managers. Highlevel planning.
4.2.
Psychological Resilience
In this section we provide thirteen examples of approaches to measure psychological resilience. Psychological resilience has traditionally been assessed at an individual level; however more recent assessments tend to pay more attention to the community level (e.g. Paton 2001, Bonanno & Mancini 2008). Additionally, the psychology related assessments are mainly focused on pre- and post-disturbance situations. This highlights the importance of further exploring psychological perspectives throughout the disaster management cycle. Example 1: References provided in table. Hazard/ Phenomenon
Dimension
Scale
Phases/Context
Component
Indicator/Criteria
Measurement
Disasters, war and terrorism
Psychological Resilience
Individual
Pre-disaster
Social
-Individual Sociodemographic Individual characteristics associated with psychological resilience
-Age (Bonanno et al., 2006; Bonanno et al., 2007; Mancini and Bonanno, 2009; Johnson et al., 2009)
-Gender -Race Educational achievements
Example 2: References provided in table. Hazard/ Phenomenon Terrorism and war
Dimension
Scale
Phases/Context
Component
Indicator/Criteria
Measurement
Psychological Resilience
Individual to community, regional
Pre-disaster
Social
-Individual Resources (Psychosocial and material resources ) Availability, conservation and sustainability
-Objects
-Social ties personal money/income (Johnson et el. 2009) -Cognitive abilities -Intelligence
21
Example 3: References provided in table.
Hazard/ Phenomenon Natural Disasters (e.g., volcanoes, earthquakes, floods)
Dimension
Scale
Phases/Context
Component
Indicator/Criteria
Psychological Resilience
Local to national
Pre-disaster
Socio-economictechnological
-Community Resources Availability, conservation and sustainability
Measurement
-Economic development, information and communication, social capital, and community competence (Norris et al., 2008).
-Shared community values, aspirations and goals, established social infrastructure, positive social and economic trends, sustainability of social and economic life, partnerships, communities of interest, established networks, resources and skills are elements supporting resilience (Buckle et al., 2000). -Affordable housing, income equality, home Internet access, educational attainment, elected leadership diversity, rates of recovery of healthy functioning following illness, rank on United Way “State of Caring Index”, access to health care, public space, including public park acreage, bike and walking paths, open space, etc., air quality, recidivism rates, perceptions of social trust and cohesion (Hall & Zautra, 2010: 368) - Normative development, and social cohesion and the development of social capital (Lepore & Revenson, 2010) -Change in beliefs and knowledge, adjustment adoption (Paton et al., 2001)
22
Example 4: References provided in table.
Hazard/ Phenomenon Natural Disasters (e.g., volcanoes, earthquakes, floods)
Dimension
Scale
Phases/Context
Psychological Resilience
Individual to community, local , regional to national
Pre-disaster
Component
Indicator/Criteria
Measurement
-Preparedness and Mitigation
-Factual risk assessments
Risk awareness and perception, planning, actions of preparedness and mitigation, presence of civil society groups for preparedness and mitigation -Action plans, preparedness and mitigation efforts and actions -Public education, drills and simulation exercises, storage of food household evacuation plans -Hazard, vulnerability, risk information and scenarios describing changes and opportunities, threats -Hazard analysis, surveillance, warning, rehearsal, and logistics (O’Leary, 2004).
Example 5: References provided in table.
Hazard/ Phenomenon Various contexts including stressful and traumatic life events
Dimension
Scale
Phases/Context
Component
Indicator/Criteria
Measurement
Psychological Resilience
Individual to community
Pre- and postdisaster
Social
-Social Support
-Support from different sources (e.g., family, community, societal), social networks (Sumer et al., 2005, DeTerte et al., 2009, Mancini and Bonanno, 2009, Hoijtink et al., 2011 )
Received and perceived social support Availability of social ties
23
Example 6: References provided in table.
Hazard/ Phenomenon Disasters, bereavement, loss, psychological wellbeing
Dimension
Scale
Phases/Context
Component
Indicator/Criteria
Measurement
Psychological Resilience
Individual
Pre- and postdisaster
Social
-Personality Personality, dispositions, variables of self
-Locus of control, low neuroticism, sense of coherence (Paton et al., 2001)
-Value of self and life and personal competence (Hoijtink, the Brake & Dückers, 2011) -Personal competence, affect tolerance, positive acceptance of change and secure relationships, sense of internal control, and spirituality (Connor & Davidson 2003) -Sense of coherence, hardiness, and dispositional optimism (Lepore & Revenson, 2006) -Self-enhancing biases, repressive coping, dismissive attachment, and optimism were considered as personality variables by Mancini and Bonanno (2009) -Self-esteem, self-confidence/self-efficacy, selfunderstanding, positive future orientation, control of negative behavior and emotion, hardiness, ego resilience, and defense mechanisms), and interpersonal skills (sociability, emotional expressiveness, and interpersonal understanding) (Skodol, 2010)
24
Example 7: References provided in table.
Hazards/ Phenomenon Pre- and post-disaster Violent trauma (Madsen & Abell, 2010), earthquake (Jang & Wang, 2009), hurricane (Gillard & Paton 1999).
Dimension
Scale
Phases/Context
Component
Indicator/Criteria
Measurement
Psychological Resilience
Individual
Pre- and postdisaster
Social
-Spirituality
-Having a sense of meaningful life (purpose),
Spiritual beliefs and practices
-Perseverance -Self reliance -Equanimity - existential aloneness
Example 8: References provided in table.
Hazard/ Phenomenon
Dimension
Scale
Phases/Context
Pre- and postdisaster Violent trauma (Madsen & Abell, 2010), earthquake, hurricane (Gillard & Paton, 1999).
Psychological Resilience
Individual to community
Pre- and postdisaster
Component
Indicator/Criteria
Measurement
-Disaster Impact Severity
-Type, duration, and intensity of exposure;
Proximal and distal disaster exposure impact variables
-Objective/perceived life threat -Proximal exposure is consistently linked to distress and psychopathology. However, even in higher levels of proximal exposure, resilience is common.
25
Example 9: References provided in table. Hazard/ Phenomenon Disasters
Dimension
Scale
Phases/Context
Component
Indicator/Criteria
Measurement
Psychological Resilience
Individual to community
Pre-disaster
Social
-Disaster Experiences
-Prior exposure to disasters
Experience, perception, interpretation of previous disaster experiences -Resilience to past stressors (Bonanno & Mancini 2008)
Example 10: References provided in table. Hazard/ Phenomenon
Dimension
Scale
Phases/Context
Disasters, loss, stressful situations
Psychological Resilience
Individual
Post-disaster
Component
Indicator/Criteria
Measurement
-Coping Coping with adverse circumstances
-Positive reappraisal, problem solving, and positive distraction) (NolenHoeksema, 2000). -Flexible and pragmatic coping, and repressive coping (Mancini & Bonanno, 2009) -Approach/active problem solving/coping (Agaibi & Wilson, 2005)
26
Example 11: References provided in table.
Hazard/ Phenomenon
Dimension
Scale
Phases/ Context
Component
Indicator/Criteria
Measurement
Disasters (e.g., earthquakes), bereavement, loss, chronic diseases
Psychological Resilience
Individual
Pre & postdisaster
Social
-Appraisals Cognitive appraisals, cognitions
-Benign or malign appraisals (Mancini & Bonanno, 2009)
-Threat and fear appeals (Mulilis & Lippa, 1990) -Damage anticipation, disaster expectation (Rüstemli & Karanci, 1999) -Appraisals of low control, low predictability, and high threat (Freedy, Resnick, & Kilpatrick, 1992). -Hazard appraisals and coping
Example 12: References provided in table.
Hazard/ Phenomenon
Dimension
Scale
Phases/ Context
Component
Indicator/Criteria
Measurement
Disasters; terrorism (Bonanno et al. 2007); violent trauma (Connor, Davidson & Lee 2003).
Psychological Resilience
Individual
Post-disaster
Social
-Positive Adjustment Positive adaptation (Luthar & Cichetti, 2000) Maintaining relatively stable and healthy levels of psychological and physical functioning (Bonanno, 2004) Flexible adaptation (Bonanno & Mancini, 2008)
-Having zero or one post-traumatic stress symptoms, and low levels of depression and substance use (Bonanno et al., 2007)
27
-Minimal impairment in daily functioning Showing initial impairment followed by returning to previous levels of functioning
Example 13: References provided in table. Hazard/ Phenomenon Terrorism, loss, bereavement, chronic diseases
Dimension
Scale
Phases/ Context
Component
Indicator/Criteria
Measurement
Psychological Resilience
Individual
Post-disaster
Social
-Positive Emotions Experience and expression of positive emotions
-Gratitude, interest, love (Frederickson & Tugade, 2003)
28
-Positive emotional granularity, engage more strongly with positive events, show elevated responsiveness to positive events, and exhibit greater positive mood savoring (Ong, et al., 2010: 87).
4.3.
Critical Infrastructure Resilience
In this section, we outline three examples employed to measure critical infrastructure resilience (Bruneau et al., 2003; Boin, 2007; Fritzon, 2007). Critical infrastructure resilience has mainly been assessed in the context of natural hazards and other threats, e.g. earthquake and terrorism, at a national to regional scale. The assessment of resilience, for example, in the case of Bruneau et al., (2003) covers the complete continuum of the disaster management cycle, with key indicators of robustness, rapidity, resourcefulness and redundancy relating to technical, organizational, social and economic dimensions. In contrast, Boin (2007) and Fritzon (2007) pay attention to the preparedness of critical infrastructures and their respective coping capacities, namely preparing respondents, business continuity planning, working with communities and private owners, joint preparations and training operations, and developing real-life simulation exercises, training leaders, and the setting up of appropriate institutions as well as common surveillance programmes to deal with natural hazards, disasters and catastrophes.
29
Example 1: Bruneau, M., Chang, S., Eguchi, R., Lee, G., O'Rourke, T., Reinhorn, A., et al. (2003). A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra 19 (4), 733-752. Hazard/ Phenomenon Natural Hazards, terrorism
Dimension
Scale
Critical Infrastructure Resilience
National to regional
Phases/ Context
Component
Indicator/ Criteria
Mitigation
Technical
-Robustness
Measurement
-Rapidity -Resourcefulness -Redundancy
-Building codes and construction procedures for new and retrofitted structures -System downtime, restoration time -Availability of equipment and materials for restoration and repair -Capacity for technical substitutions and ‘work around’
Preparedness
Social
-Robustness -Rapidity -Resourcefulness -Redundancy
-Social vulnerability and degree of community preparedness -Time to restore lifeline services -Capacity to address human needs -Availability of housing options for disaster victims
All
Organizational
-Robustness -Rapidity -Resourcefulness -Redundancy
-Emergency operations planning -Time between impact and early recovery -Capacity to improvise , innovate, and expand operations -Alternate sites for managing disaster operations
Response and recovery
Economic
-Robustness -Rapidity -Resourcefulness -Redundancy
-Extent of regional economic diversification -Time to regain capacity, lost revenue -Business and Industry capacity to improvise -Ability to substitute and conserve needed inputs
30
Example 2: Boin, A., & McConnell, A. (2007). Preparing for Critical Infrastructure Breakdowns: The Limits of Crisis Management and the Need for Resilience. Journal of Contingencies and Crisis Management 15 (1), 50-59. Hazard/ Phenomenon
Dimension
Scale
Phases/ Context
Natural Hazards, ,disasters and catastrophes
Critical Infrastructure Resilience
All
Preparedness
Component Coping and Adaptive Capacity
Indicator/ Criteria
Measurement
-Preparedness
-Preparing respondents -Business continuity planning -Working with communities and private owners -Joint preparations -Joint training operations and developing real-life simulation exercises -Training leaders (creating expert networks, train for situational and information assessment, Organise outside forces, Working with the media)
Example 3: Fritzon, Å., Ljungkvist, K., Boin, A., &Rhinard, M. (2007). Protecting Europe's Critical Infrastructures: Problems and Prospects. Journal of Contingencies and Crisis Management 15 (1), 30-41. Hazard/ Phenomenon Natural Hazards, pandemic, disasters and catastrophes
Dimension
Scale
Phases/ Context
Component
Indicator/ Criteria
Critical Infrastructure Resilience
National to regional
Institutions and Governance
Coping and Adaptive Capacity
-Prevention and control -Institutions
-New agencies formed
-Common surveillance programs
-Preparedness and crisis management
Preparedness
31
Measurement
-Guidelines
4.4.
Organisational and Institutional Resilience
The following section outlines selected examples of studies that have proposed indicators to measure organizational and institutional resilience. Although there is substantial variety in the studies according to their specific research focus, some similarities arise. These will be briefly highlighted in the following. Organizational and institutional resilience seem to be predominantly operationalised independently from a specific hazard or phenomenon. Some studies restrict themselves to either natural or man-made disasters, but remain unspecific with regards to an exact nomination of the hazard. As a consequence, the accuracy of information on the scale of measurement and the stage/context of the measurement remains rather broad. As organizations and institutions are often intuitively assigned a spatial identity, they mostly serve as the scale of analysis. The specific indicators reveal the conceptualization of organizations and institutions as limited, closed entities of a larger system. Most of the indicators attempt to describe the ability of individual organizations to withstand shocks and to re-organize and learn after a shock has occurred. This implicit definition of organizations as autonomous, individual elements operating in a larger system risks undermining a broader conceptualization of both organizations and institutions as spatially-unbound elements of a system as a whole. This significant gap in research deserves further exploration. Finally, the preoccupation of indicator approaches with preparedness seems to be prominent. Resilience measurements and indicators are predominantly attempting to assess the preparedness of organizations and institutions. They thus risk overemphasizing the importance of preparing for disturbances, which inherently necessitates arbitrary assumptions on the magnitude and frequency of shocks. This undermines a focus on flexibility and the notion of living with uncertainties, which would reflect current resilience discourses in the literature more accurately.
32
Example 1: Weick, K. E., Sutcliffe, K. M. (2007): Managing the unexpected: Resilient performance in the age of uncertainty, John Wiley & Sons, Inc.: USA. Hazard/ Phenomenon
Dimension
Scale
Stages/Context
Component
Indicator/Criteria
Measurement
Hazard-invariant (applicable to natural and man-made disasters)
Organisational
Organisational
Preparedness
Preoccupation with failure
-Encouragement of reporting errors
not provided
-Elaborate experiences of nearcatastrophic events
not provided
-Wary of potential liabilities of success
not provided
-Articulation of mistakes that need to be avoided
not provided
-Assessment of likelihood that strategies increase the risk of mistakes
not provided
-Welcome diverse experience
not provided
-Skepticism towards wisdom
not provided
-Negotiation of tactics that reconcile while appreciating diversity
not provided
Reluctance to simplify
33
Sensitivity to operations
not provided
Commitment to resilience
not provided
Deference to expertise
not provided
Example 2: McManus, S., Seville, E., Brunsdon, D., & Vargo, J. (2007). Resilience Management: A Framework for Assessing and Improving the Resilience of Organisations. Resilient Organization Research Report No. 2007/01. Resilient Organisations: New Zealand Hazard/ Phenomenon Hazard-invariant (Natural hazards)
Dimension
Scale
Stages/Context
Component
Indicator/Criteria
Measurement
Organisational
Organisational
Preparedness
Situation awareness
-Awareness of its entire operating system, including threats, connectivity and internal and external stakeholders
not provided
-Understanding of hazards and consequences
not provided
-Organizational recovery priorities
not provided
Connectivity awareness
-Awareness and understanding of their immediate operating environment, awareness of organization’s connectivity with the entire community of stakeholders
not provided
Insurance awareness
-Knowledge of levels of business interruption insurance
not provided
Management of keystone vulnerability
-Planning strategies
not provided
-Participation in exercises
not provided
-Capability and capacity of internal resources
not provided
-Capability and capacity of external resources
not provided
-Organisational connectivity
not provided
-Silo mentality
not provided
-Communication and partnerships
not provided
-Strategic vision and outcome expectancy
not provided
-Information and knowledge
not provided
-Leadership management and governance structures
not provided
Response
Recovery
Adaptive capacity
34
Example 3: Pariès, J. (2006): Complexity, emergence, resilience. In: Hollnagel, E., Woods, D.D., and N. Leveson: Resilience Engineering: Concepts and Precepts. Aldershot: Ashgate. Hazard/ Phenomenon
Hazard-invariant (Natural hazards)
Dimension
Scale
Stages/Context
Component
Organisational
Organisational
Throughout the risk cycle
Preparedness
35
Indicator/Criteria
Measurement
-Complex emergent properties (e.g. consciousness, risk awareness, etc.)
-not provided
-Safety management system
-not provided
-Local couplings between individual agents and their environment (e.g. facilitation of collective resilience at different scales – role definition, shared procedures, communication, leadership, delegation, crossmonitoring, etc.)
-not provided
-Individual human features (e.g. individual cognition, error management, surprise management, stress management)
-not rovided
-Organisational measures (e.g. the design of error tolerant environments).
-not provided
Example 4: Adapted from: Woods, D. D., Wreathall, J. (2003): Managing risk proactively: The emergence of resilience engineering 3. Wreathall, J. (2006): Properties of resilient organisations: An initial view. In Hollnagel , E., Woods. D. D., Leveson, N. (eds.) (2006): Resilience engineering: Concepts and precepts, Ashgate: England Woods, D. D. (2003): Creating foresight: How resilience engineering can transform NASA’s approach to risky decision making. Testimony on The Future for NASA for the Committee on Commerce, Science and Transportation 4. Hazard/ Phenomenon Hazard-invariant (Natural hazards)
Dimension
Scale
Stages/Context
Component
Organisational
Organisational
Throughout the risk cycle
Management commitment
-Commitment of the management to balance the acute pressures of production with the chronic pressures of protection
Reporting culture
-Degree to which the reporting of safety concerns and problems is open and encouraged
Learning culture
-How much does the organisation respond to events with denial versus repair or true reform?
Panticipation
-Proactively picking up on evidence of developing problems versus only reacting after problems become significant.
Flexibility
-Ability of the organisation to adapt to new problems. It requires flexibility in decision-making for people at the working level
Opacity (and its corollary, observability)
-Monitors safety boundaries and recognises how close it is to ‘the edge’ in terms of degraded defences and barriers. -How does the organisation update its model of vulnerabilities and effectiveness of countermeasures over time?
Revise/Fixated
3
Indicator/Criteria
Measurement
http://csel.eng.ohio-state.edu/woods/error/working%20descript%20res%20eng.pdf http://history.nasa.gov/columbia/Troxell/Columbia%2520Web%2520Site/Documents/Congress/Senate/OCTOBE~1/Dr.%2520Woods.pdf&sa=U&ei=rWzoT6nvJcqigbu_dWxAw&ved=0CAUQFjAA&client=internal-uds-cse&usg=AFQjCNHY7Q0Uh46znzHCnrMLT6V298NW5g 4
36
Example 5: Woods, D. D. (2006): How to design a safety organisation: Test case for resilience engineering. In: Hollnagel, E., Woods, D.D., and N. Leveson (eds): Resilience Engineering: Concepts and Precepts. Aldershot: Ashgate. Hazard/ Phenomenon Hazard-invariant (applicable to natural and man-made disasters)
Dimension
Scale
Organisational
Organisational
Stages/ Context Throughout the risk cycle
Component Independent
Involved
Indicator/Criteria
Measurement -Provides an independent voice that challenges conventional assumptions about safety risks within senior management - Constructive involvement in targeted but everyday organisational decision making (e.g. ownership of technical standards, waiver granting, readiness reviews, and anomaly definition)
Informed
-Actively generate information about how the organisation is actually operating and the vectors of change that influence how it will operate
Informative
-Use information about weaknesses in the organisation and the gap between work as imagined and work as practised in the organisation to reframe and direct interventions
37
Example 6: Allen, J. H., Davis, N. (2010): Measuring operational resilience using the CERT resilience management model. Pittsburgh: Carnegie mellon University Hazard/ Phenomenon Risk that affects core operational capacities
Dimension
Scale
Stage/Context
Organisational
Organisational
Preparedness
Component
Indicator/Criteria
Measurement
-Derives its authority from and directly traces to organizational drivers (senior, high-level executives)
-Number of operational resilience management program activities that do not directly support organizational drivers
-Satisfies enterprise resilience requirements that are assigned to high-value services and their associated assets
-Number of enterprise resilience requirements
-Number of high-value services -Percentage of high-value services and associated assets that do not satisfy their allocated enterprise resilience requirements -Satisfies high-value asset resilience requirements
-Number of asset resilience requirements -Percentage of asset resilience requirements that have been (have not been) assigned to one or more assets
38
-Via the internal control system, ensures that controls for protecting and sustaining highvalue services and their associated assets operate as intended
-Percentage of control objectives that are satisfied (not satisfied) by controls (enterprise-level, by service, by asset category)
-Manages (identifies, analyzes, mitigates) operational risks to high-value assets that could adversely affect the operation and delivery of high-value services
-Extent to which current risks with a “mitigate or control” disposition are effectively mitigated by their mitigation plans
-In the face of realized risk, ensures the continuity of essential operations of high-value services and their associated assets
-Number and percentage of disrupted, high-value services without a service continuity plan
Example 7: Tierney, K. & Bruneau, M. (2007). Conceptualizing and Measuring Resilience. A Key to Disaster Loss Reduction. TR News May-June 2007, pp. 14-17. Hazard/ Phenomenon
Dimension
Scale
Stage/Context
Component
Indicator/ Criteria
Multi-hazard
Organisational
Organisational
Preparedness, Response, Recovery
Robustness (maintaining its functioning and performance in times of disturbances/ disasters)
-Extensiveness of emergency operations planning
Redundancy (extent to which organizations or specific units are substitutable, i.e. capable of satisfying functional requirements)
-Presence of alternate sites for managing disaster operations
Resourcefulness diagnose and prioritize problems, initiate solutions by identifying and mobilizing material, monetary, informational, technological, and human resources)
-Ability to be flexible, to improvise, innovate, expand
Rapidity (restore functionality in a timely way, containing losses and avoiding disruptions)
-Time needed to regain functionality
39
Measurement
Example 8: Whitacre, J. M. and A. Bender (2010). "Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems." Theoretical Biology and Medical Modelling 7 (1): 20. Hazard/ Phenomenon
Dimension
Scale
Stage/Context
Component
Hazard-invariant
Organizational
Complex Adaptive System
Mitigation, Preparedness, Response
Functional plasticity (Agent has multiple qualitatively different functions)
Capability overlap between agents (Pure redundancy can only generate a local buffer, partial overlap / degeneracy leads to a global buffer against perturbations)
Functional redundancy (Two agents have a single, same function)
Ibid.
Degeneracy (Agents are functionally plastic and functionally redundant, i.e. agents share similarities in only some of their functions but are different in others, leading to conditions where agents can compensate for each other)
Number of possible reconfigurations of the task network
Network buffering (Agents form a network of tasks/functions, each node represents a task capability.)
Not provided
(external perturbations in general, unpredictable environmental conditions with high uncertainty)
40
Indicator/Criteria
Measurement
4.5.
Practical Perspectives of Resilience (Community)
In this section, we present four practical perspectives of measuring community resilience. The review of studies builds on the literature discussed in emBRACE Working Paper 1.1. The first example (Twigg, 2009) organizes dimensions of resilience under five thematic headings, representing the main areas of DRR intervention as outlined in the UN ISDR Hyogo Framework for Action 2005-2015. Particular attention should be paid to the first dimension (Governance), which is a cross-cutting theme underlying all other dimensions. Planning, regulation, integration, institutional systems, partnerships and accountability are relevant to everyone, because they are issues likely to affect any initiative in DRR, development or relief. The characteristics set out in the tables are not conventional project indicators. Rather they characterize an ideal state of resilience in quite general terms. For the development of the emBRACE theoretical framework, emBRACE case studies will therefore need to include their own specific and more detailed indicators at the appropriate stages in the project cycle. The framework provided by the Red Cross (example 2) aims to establish a foundation for all Red Cross Red Crescent programmes working to increase community resilience. It outlines several key characteristics of resilient communities which are closely related to the 5 HFA priorities. In particular, resilient communities are perceived to a) understand disaster risks, assess and monitor these and protect themselves to minimize losses and damage when a disaster strikes, b) be able to maintain basic community functions in times of disaster, c) rebuild back after a disaster and work towards ensuring that vulnerabilities continue to be reduced for the future, d) understand that building safety and resilience is a long-term, continuous process that requires ongoing commitment, and to e) be aware that being resilient increases chances to meet development goals. The study by Cutter et al. (2001) (example 3) conceptualizes resilience as a set of capacities rather than a characteristic of systems. According to the authors, resilience can therefore be facilitated through policy interventions. However, a comprehensive understanding of how disasters affect systems requires including the assessment of vulnerabilities and factors that undermine resilience. In their explicitly social-centered approach, Cutter et al. differ from previous studies, notably the work of Bruneau (2003), which largely ignored the social dynamics of communities. The approach to measure resilience is intended to be as holistic as possible and relies to a large extent on composite indicators. These are, according to the authors, best suited to produce aggregate measures of resilience. The selection of specific variables in the study is based on a review of existing indicators and measures of resilience in the literature and guided by the availability of data from national sources. As the authors point out, there is a consensus in the academic literature regarding the multidimensionality of resilience (the concept can refer to, for example, social, political, economic, institutional, infrastructural, ecological, and community dimensions). However, despite their claim to present a comprehensive and holistic approach to measuring community resilience, Cutter et al. employ national datasets, which could well be obsolete, to provide 36 indicators to measure community resilience. Whilst there is certainlysome value in this “Building Resilience Indicators for Communities” (BRIC) approach, it has obvious limitations. For example, in order to differentiate areas where social or infrastructural drivers for resilience are apparently lacking (according to the selected indicators), the assumption that a variable like “Percent vacant rental units” is an indicator of infrastructure resilience leads to a very parameterised understanding of what resilience is. These approaches fail to look at the social context as to why these rental units are empty (i.e. an empty rental unit may indicate a potential shelter, but it may also indicate a depressed local economy). It could also be argued that variables such as “percentage employed” might fail to capture issues like job security and 41
wage level that have equally significant effects on an individual or household’s capacity to withstand hazard effects. Additionally, BRIC excludes environmental or place-based indicators and therefore lacks an assessment of ecological dimensions of community resilience. The last example provided in this section presents the measurement approach of Norris et al. (2008). The study also explicitly focuses on community resilience, which is conceptualized as emerging from four primary sets of adaptive capacities: a) economic development, b) social capital, c) information and communication, and d) community competence. The authors apply a definition of resilience that focuses on the process of linking resources and outcomes. It identifies resilience as a set of adaptive capacities to a positive trajectory of functioning and adaptation after a disturbance. Unlike other studies, which often uncritically adopt the concept of community without a clear conceptualization, Norris et al. argue that communities should be seen as complex systems composed of built, natural, social and economic environments that mutually influence each other.
42
Example 1: Twigg, J. (2009): Characteristics of a Disaster Resilient Community. A Guidance Note. London: Aon Benfield UCL Hazard Research Center. Hazard/ Phenomenon All hazards and threats inc. ClimateChange Adaptation, (CCA)
Dimension
Scale
Governance
National, Local and Community (on the assumption that the community will be embedded within a wider “enabling environment”)
Risk Assessment
Phases/ Context DRM cycle, however, the indicators present characteristics of an ideal state, not project indicators in the conventional sense
Component
Indicator/Criteria
Measurement
Policy, planning, priorities & political commitment
-Political consensus on importance of DRR (At all political levels and with local-level support for community vision
Legal & regulatory systems
-Community understands relevant legislation, regulations and procedures, and their importance. Community aware of its rights and the legal obligations of government & other stakeholders to provide protection.
Integration with development policies & planning
-Community DRR seen by all local stakeholders as integral part of plans and actions to achieve wider community goals (e.g. poverty alleviation, quality of life).
Hazards/risk data and assessment
. -Fully participatory community hazard/risk assessments carried out and results shared -On-going monitoring + support and training
Vulnerability/capacity and impact data and assessment
-Comprehensive participatory community Vulnerability and Capacity Assessments (VCAs) carried out
-The Indicators / Characteristics are not a model for every situation. They are a resource, not a checklist to be ticked off. Each characteristic should stimulate and facilitate discussion and be adapted to the context in which it is being used and the needs and capacities of those who use it.
Scientific and technical capacities and innovation
-Community members and organisations trained in hazards, risk and VCA techniques and supported to carry out assessments. -Use of indigenous knowledge and local perceptions of risk as well as other scientific knowledge, data and assessment methods.
43
Example 1 (cont’d): Twigg, J. (2009): Characteristics of a Disaster Resilient Community. A Guidance Note. London: Aon Benfield UCL Hazard Research Center. Hazard/ Phenomenon All hazards and threats (inc. CCA)
Dimension
Scale
Phases/ Context
Knowledge and Education
National, Local and Community (on the assumption that the community will be embedded within a wider “enabling environment”)
DRM cycle, however, the indicators present characteristics of an ideal state, not project indicators in the conventional sense
Risk Management and Vulnerability Reduction
Component
Indicator/Criteria
Measurement
Public awareness, knowledge and skills
-Community knowledge of hazards, vulnerability, risks and risk reduction actions sufficient for effective action by community (alone and in collaboration with other stakeholders).
Information management and sharing
-Information on risk, vulnerability, disaster management practices, etc., shared among those at risk. -Community understanding of characteristics and functioning of local natural environment and ecosystems and the potential risks associated with these natural features and human interventions that affect them. -High levels of personal security and freedom from physical and psychological threats. -Community access to basic social services (including registration for social protection and safety-net services).
-The Indicators / Characteristics are not a model for every situation. They are a resource, not a checklist to be ticked off. Each characteristic should stimulate and facilitate discussion and be adapted to the context in which it is being used and the needs and capacities of those who use it.
Environmental and natural resource management
Health and well being
Social protection
-Established social information and communication channels; vulnerable people not isolated .
44
Example 1 (cont’d): Twigg, J. (2009): Characteristics of a Disaster Resilient Community. A Guidance Note. London: Aon Benfield UCL Hazard Research Center Hazard/ Phenomenon All hazards and threats (inc. CCA)
Dimension
Scale
Disaster Preparedness and Response
National, Local and Community (on the assumption that the community will be embedded within a wider “enabling environment”)
Phases/ Context DRM cycle, however, the indicators present characteristics of an ideal state, not project indicators in the conventional sense
Component
Indicator/Criteria
Measurement
Organizational capacities and coordination
-Local and community DP/response capacities assessed by communities
-The Indicators / Characteristics are not a model for every situation. They are a resource, not a checklist to be ticked off. Each characteristic should stimulate and facilitate discussion and be adapted to the context in which it is being used and the needs and capacities of those who use it.
-Local organisational structures for DP/emergency response -Local DP/response organisations are community managed and representative. Early warning systems
-Community-based and people-centred EWS at local level. -EWS capable of reaching whole
Preparedness and contingency planning
-A community DP or contingency plan exists for all major risks -DP/contingency plans developed through participatory methods, and understood and supported by all members of community. -Community organisations capable of managing crises and disasters, alone and/or in partnership with other organisations. -Safe evacuation routes identified and maintained, known to community members. -Community capacity to provide effective an
Emergency resources and infrastructure
Emergency response and recovery Participation, voluntarism, accountability
45
-Local leadership of development and delivery of contingency, response, recovery plans. -
Example 2: A Framework for Community Safety and Resilience: in the Face of Disaster Risk (IFRCRCS, 2008)
Hazard/ Phenomenon All hazards
Dimension
Scale
Phases/ Context
Component
Indicator/Criteria
Measurement
Institutional / organisational
National, Local, Community
DRM cycle
Risk assessment and identification and the establishment of community-based early warning and prediction
-Ability to conduct systematic vulnerability and capacity assessment processes
-None offered
-Community empowerment for action -Information management and dissemination for timely response and for developing medium- to longer-term programming to anticipate future risks (inc. climate change and new risks) -Advocacy for community action -Construction of databases to inform programme baselines -Developing links with preparedness Capacity-building for early warning
46
Example 2 (cont’d): A Framework for Community Safety and Resilience: in the Face of Disaster Risk (IFRCRCS, 2008) Hazard/ Phenomenon All hazards
Dimension
Scale
Phases/ Context
Component
Indicator/Criteria
Measurement
Institutional / organisational
National, Local, Community
DRM cycle
Community-based disaster preparedness
-Building from the priorities of the VCA
-None offered
-Developing preparedness at community and household levels -Building community infrastructure -Contingency planning -Community organization through branches -Establishing branch disaster response teams -Skills training -Identification of target groups – schools, home, workplace -Developing partnerships with knowledge centres -Programming to link disaster preparedness with longer-term disaster risk reduction
47
Example 3: Disaster Resilience Indicators for Benchmarking Baseline Conditions (Cutter et al. 2010) Hazard/ Phenomenon All-Hazards
Dimension
Scale
Community Resilience, (Disaster Resilience of Place (DROP))
National; Local (i.e. Countyscale, across US south east region)
Phases/ Context Baseline resilience assessment
Component
Indicator/Criteria
Social
-Education -Age -Transportation access -Telephone access -Language competency
Economic
-Housing capital -Employment -Income and equality -Employment -Health access -Mitigation -Insurance -Experience
Institutional
Infrastructural
Community
48
Measurement -Ratio of the % pop with college education to the % pop with no high school diploma % non-elderly pop. -% pop with vehicle -% pop with telephone -% pop not speaking -English as a second language -% home ownership -% employed -GINI coefficient -% female labour force -physicians per 10,000 population -% covered by hazard mitigation plan) -(% covered by NFIP) -no. of previous disaster declarations
-Housing type -Shelter capacity -Medical capacity -Access / evacuation potential ‘Recovery’
% housing units that are not mobile homes % vacant rental units Hospital beds per 10,000 population 2 principal arterial route per mile Number of public schools per squaremile
-Place attachment -Political engagement -Social Capital – Religion -Social Capital – Civic involvement -Social Capital - Advocacy
-Net international migration -% voter participation in the 2004 election -No. of religious adherents per -10,000 population -No. of civic organisations per -10,000 population -No. of social advocacy -organisations per 10,000 population
Example 4: Community Resilience as a Metaphor, Theory, Set of Capacities and Strategy for Disaster (Norris et al., 2008) Hazard/ Phenomenon
All-hazards and threats
Dimension
Scale
Psychological, community, institutional and organisational
National, Local, Community
Phases/ Context
Whole DRM cycle with a focus on promoting well-being in the community
Component
Indicator/Criteria
Measurement
Economic development
- Resource volume and diversity
-“It should be readily apparent […] that the network of adaptive capacities that yields community resilience is not a singular condition that can be measured or monitored simply. … Our primary hope is to foster creative thinking about how various pathways between Economic Development, Social Capital, Information and Communication, and Community Competence shape disaster readiness and recovery” (p.144)
-Resource Equity and Social Vulnerability
Social Capital
-Network Structures and Linkages -Social Support -Community Bonds, Roots, and Commitments
Information & Communication
-Systems and Infrastructure for Informing the Public -Communication and Narrative
Community Competence
-Collective Action and Decisionmaking -Collective Efficacy and Empowerment
49
5.
Components of Resilience
In order to draw meaningful insights from our comparison of studies that attempt to assess resilience, this section summarises the review by drawing on the components of resilience that different studies address. Our goal is to identify, from a wide range of components of resilience proposed in the literature, a set of key components that are essential for most of the studies under review and that reflect the predominant focus of studies that measure resilience. The list of key components is provided in Table 2. We apply a threefold identification process that takes into account a) the prominence of components in the studies reviewed in this Working Paper, b) the focus and applicability of components to community resilience, and c) relevance of components for the case studies of the emBRACE research project. Rather than being a rigorous methodology for the selection of resilience components, this approach thus reflects a necessarily subjective attempt to synthesize the systematization of indicator approaches presented above. Therefore, it is important to note that the list of resilience components identified through this approach reflects the specific needs of the emBRACE project. It is not necessarily intended to serve as a generalisable outcome of a comprehensive analysis.
50
Table 2: Identification of main components of resilience independent of school of thought NB: In certain cases, the main components may also be reflected or shared as the sub-components
THEMES/ DIMENSIONS of RESILIENCE
ALL IDENTIFIED RESILIENCE COMPONENTS
SUB-COMPONENTS
(Based on tables in section 3)
1. 2. 3. 4. 5. 6.
7.
Different Schools of Thought
MAIN COMPONENTS
8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27.
Accountability Adaptive capacity Advocacy Appraisals Adjustment Assessments (Hazard, Vulnerability, impact, Capacity and Risks) Autonomous and interdependent Awareness Capital Capacities and structures Connected Competence Community-based Systems Coping Coordination Compensation Culture Development Degeneracy Education and training Economic Emotions Exposure Experience Financial instruments Flexibility Functional and Response Diversity
44. Impact Severity 45. Integration with development 46. Organizational capacities 47. Participation, 48. Partnerships 49. Policies & Planning 50. Protection 51. knowledge 52. Learning Culture 53. Legal and regulatory systems 54. Livelihoods 55. Management 56. Mitigation 57. Motivation 58. Network 59. Observability 60. Opacity 61. Organized 62. Partnerships 63. Participation 64. Personality 65. Preparedness 66. Profitable 67. Policy & planning 68. Priorities & political commitment 69. Rapidity 70. Relationship 71. Reporting cul-
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.
Accountability Adjustment Appraisals Advocacy Coordination, Degeneracy Flexibility Participation, Functional Heterogeneity Plasticity/redundancy
12. 13. 14. 15. 16.
1.
4. 5. 6.
2. 3.
Assessments (Hazard, Vulnerability, impact, Capacity and Risks) Education and training Experience
3.Information and Communication
1. 2.
Reporting culture Informed/Informative
4.Culture and Diversity
Community-based systems
5.Preparedness
1.
Observability
6.Response
1.
Functional and Response Diversity
1.Governance (Actors, Institutional Arrangements, Organizations)-Crosscutting
2.Education, Research, Awareness and Knowledge
7.Protection
51
17. 18. 19. 20.
7. 8. 3.
Support Relationship Responsibilities Voluntarism Autonomous and interdependent Organizational capacities Independent Organized Structural measures Skills Competence Honours Legacy Learning Culture Research Information management and sharing
21. Motivation/Incentive 22. Partnerships 23. Policies and Planning 24. Legal and regulatory systems 25. Policy and planning 26. Priorities and political commitment 27. Regulated
28. 29. 30. 31.
Involved Insurance Structures/ Network and Connected 32. Management 33. Integration with development
28. Functional plasticity 29. Functional redundancy 30. Health and well being 31. Heterogeneity 32. Honours Legacy 33. Institutional 34. Infrastructural 35. Informed/Informative 36. Innovation 37. Information & Communication 38. Information management and sharing 39. Involved 40. Independent 41. Institutional mechanisms 42. Infrastructure 43. Insurance
ture 72. Regulated 73. Responsibilities 74. Response 75. Resources 76. Robustness 77. Redundancy 78. Research 79. Resourcefulness 80. Revise/Fixated 81. Structural measures 82. Support 83. Spirituality 84. Skills 85. Technical measures 86. Voluntarism
8.Exposure, Experience and Impact Severity 9.Resources
10.Health and Well Being/ Livelihood
11.Economic
1. 2. 3. 4. 1. 2.
Spirituality Personality Compensation Emotions Profitable Financial instruments
12.Adaptive capacity 13.Coping Capacity 14.Innovation and Capital/s 15.Infrastrastructure and Technical
1. 2. 3. 4.
52
Rapidity Redundancy Resourcefulness Robustness
6.
Discussion of Key Findings, Challenges and Gaps
This section discusses key insights and gaps and challenges that arise from the assessment and systematization of indicators presented above.
6.1.
Key Insights from the Systematization
The systematization of indicators, criteria, and components of resilience across various disciplines has shown that despite the epistemological differences between academic disciplines, there is a desire among all of the different approaches to operationalise resilience. This common ground manifests itself not so much in the specific indicators chosen to grasp the resilience of individuals, organizations, social-ecological systems or infrastructure, but rather in the more general characteristics of a resilient entity. Across all studies reviewed for this systematization of indicators, we observe that often different indicators are used to measure the same characteristics or components of resilience. Our re-categorisation of resilience indicators, independently of the different schools of thought identified in emBRACE Working Paper 1.1, has allowed for the identification of fifteen main component of resilience. These are: (1) Governance (Actors, Institutional Arrangements, and Organisations) (2) Education, Research, Awareness and Knowledge (3) Information and Communication (4) Culture and Diversity (5) Preparedness (6) Response (7) Protection (8) Exposure, Experience and Impact Severity (9) Resources (10) Health and Well Being/ Livelihood (11) Economic (12) Adaptive capacity (13) Coping Capacity (14) Innovation and Capital (15) Infrastructure and Technical. A large set of sub-components of resilience have been grouped under the governance component. These are relevant for most of the studies under review here and thus present crosscutting issues of resilience. This is an interesting and important outcome of the systematization, particularly with regards to dealing with complex, ambiguous and uncertain risks such as climate change in the area of DRR. Another key insight that can be drawn from the systematization of indicators is the apparent focus of many approaches on preparedness. This can be observed in particular in measurements of organisational and institutional resilience, which predominantly focus on the preparedness of institutions, underlining a rather proactive approach to disaster risk reduction. Existing studies in this area reveal their underlying assumption that the resilience of organizations necessitates planning for a range of adversities and to prepare to them beforehand. Despite this seemingly traditional approach to resilience as coping (“engineering resilience”), the components and indicators of organizational resilience are predominantly dynamic in character. Their focus on flexibility through learning, awareness, and constant critical reflection reveals a progressive conceptualization of resilience as a transformative process. Based on the non-representative selection of studies evaluated in this Working Paper, it is apparent that non-academic studies and reports are ahead of peer-reviewed literature in proposing frameworks to measure resilience. The picture differs, however, across dimensions of resilience. While an impressive number of grey literature studies on community resilience demonstrate the progress in practitioner literature, academic studies are wellrepresented in research on measuring organizational and institutional resilience. This might be due to the strong theoretical background provided by organizational and institutional theo53
ry, which sheds light on the internal dynamics and processes that shape the output of organizations. It allows for a theorized operationalization of organizational resilience and an identification of indicators based on existing research. Nevertheless, non-peer-reviewed studies seem to dominate the literature on measuring resilience. It seems that the terminological ambiguity of the resilience concepts puts boundaries to its use and operationalization in academic studies that might not be of great concern in practically-oriented studies.
6.2. Gaps and Challenges Multi-Dimensional and Trans-Disciplinary Character of Resilience The systematization of indicators, criteria, and components of resilience confirms the findings from the emBRACE literature review (emBRACE, 2012), which pointed to the complexity and ambiguity of the concept. Within each of the different schools of thought and disciplines, approaches to measure resilience face the challenge of multidimensionality. While taken together, the various conceptualizations and measurements of resilience might create the impression that resilience is a comprehensive and robust concept, the diversity also points to some of the challenges that arise when trying to operationalise the concept. In particular, it seems difficult to develop a holistic conceptualization of resilience that can accommodate all the dimensions and indicators according to their disciplinary merit and importance. Disturbance –Stress Context An important aspect of resilience is the particular disturbance or stress context that is considered. This context has been prominently highlighted by Carpenter et al. (2001), who underlined the necessity to define the perturbation of interest (“resilience to what?”). While their approach was driven by an explicit focus on social-ecological resilience, which focused on short-term changes in the bio-chemical composition of ecosystems, the systematization of indicators above demonstrates that adversities and shocks are defined very broadly in the wider literature. While the emBRACE project has a particular focus on community resilience to natural hazards, many of the studies reviewed in this Working Paper assume quite different stressors. For example, research on organisational, institutional, and psychological resilience does not tend to take place in a natural disaster context. Hence, the disturbance context remains largely unspecified. This might reflect a general transition in the research agenda of resilience thinking, which seems to be increasingly focusing on how social-ecological systems are dealing with different forms of change. Overall, general issues such as rapid or slow, radical, and unexpected transformations seem to attract more interest than specific disturbance. Interaction between Different Dimensions and Components of Resilience In this Working Paper and in the emBRACE literature review (emBRACE, 2012), we have analysed different schools of thought in a rather isolated context. This stems from the fact that most studies that conceptualize and measure resilience take place in a specific discipline and are guided by different epistemological research interests. In the literature review, we have found few studies that attempt to bridge the disciplinary divide in resilience research. Even fewer studies address the interaction between different dimensions of resilience. Exploring this interaction, however, is a fundamental prerequisite for understanding how the different dimensions and components shape community resilience. This remains a central question for the development of a theoretical framework for measuring community resilience, which will be the main purpose of emBRACE deliverable 2.1. 54
Focus on Community Despite a certain focus on different reference objects of resilience (e.g. individuals, organizations, buildings, etc.), many of the approaches reviewed in the systematization above implicitly relate to the resilience of communities. The specific studies are either located below (psychological, critical infrastructure) or above (social-ecological systems, organizations and institutions) the community scale, applying both “worms-eye” or “birds-eye” perspectives on the community. Considering the cross-scale interaction of system components and nested systems (Holling, 1986), the resilience of individuals, organizations and social-ecological systems all combine to shape resilience at the community scale. The prominence of community resilience in studies under review in this paper necessitates a thorough conceptualization of the term. As the discussion of community resilience in emBRACE Working Paper 1.1 has shown, the concept of community is far from well understood in the academic literature. In Working Paper 1.1, a typology of five community types has been put forward: (1) geographical communities, (2) communities of interest, (3) communities of circumstance, (4) communities of supporters, and (5) communities of identity 5. However, this typology represents only one of many attempts to conceptualize the notion of community. The conceptual ambiguity is reflected in those studies that explicitly attempt to measure community resilience. They present different, often substantially divergent definitions of community, which altogether can only offer an incoherent conceptualization. For example, the role of organizations and institutions as integral elements of communities is not as yet sufficiently addressed. An important question that remains to be answered concerns the impact that key organizations have for community resilience as a whole. Can we grasp the extent to which specific organizations facilitate or undermine community resilience? These and similar questions remain to be addressed in future studies. Difficulties in Quantifying Resilience A striking feature of most of the approaches that were reviewed in this Working Paper is the lack of information on measurements. Only very few of the studies under review here presented information on how to quantitatively measure the indicators of resilience that they identified. This observation presents interesting insights into the question raised at the beginning of this document: Can resilience be measured? The results of the review in this paper suggest that measuring resilience in a traditional way (hence by retrieving quantifiable information) presents a fundamental challenge to most researchers, as most of the indicators proposed to measure resilience are not operationalised. Whether or not measuring resilience is a challenge that can and should be overcome depends heavily on the underlying conceptualization of the concept, which will be further elaborated in the course of the emBRACE project.
5
For further information see emBRACE Working Paper 1.1 (emBRACE 2012). 55
7.
Conclusion and Recommendations
In this Working Paper 1.2 of the emBRACE project we carried out a systematization of different concepts, criteria, and indicators of resilience. Our central aim was to review how resilience is assessed in existing studies by drawing on the literature review of resilience research provided in Working Paper 1.1, and on additional recent sources and publications on frameworks and indicators for measuring community resilience. To achieve our goal we systematised all studies under consideration according to the source of disturbance (i.e. hazard), to the dimension, scale, phases/context, component, indicator and measurement of resilience through a descriptive approach. We showcase selected examples of studies that have proposed frameworks and indicators to measure social-ecological, psychological, critical infrastructure, organizational and institutional and practical community-based examples of resilience. One of our interests was to identify, from a wide range of components of resilience proposed in the literature, a set of key components, which are essential for most of the studies under review and that reflect the predominant focus of studies that measure resilience. Based on their prominence in the studies reviewed in this Working Paper, their focus and applicability to community resilience, and their relevance for the case studies of the emBRACE research project, our analysis of resilience independent of the different schools of thought has enabled the identification of fifteen main components of resilience. Surprisingly, we find that a larger set of sub-components of resilience has been grouped under the governance component, signifying the importance of cross-cutting issues associated with resilience. This particular outcome is encouraging, particularly with regards to building resilience of communities from complex, ambiguous and uncertain risk associated with climate change. Another interesting observation is the increasing interest in non-peer-reviewed literature to measure resilience, particularly in the area of DRR. In the discussion (chapter 6) we have highlighted the gaps and challenges encompassing the multi-dimensional and trans-disciplinary aspect of resilience, the disturbance–stress context, the interaction between different dimensions and components of resilience, the ambiguous notion of community, and the difficulties in quantifying resilience. Additionally, a key challenge and gap to be filled is the need to combine single indicators in order to measure resilience, as well as the need for a more explicitly community focus of resilience research. Based on the assessment, systematization, and evaluation of this Working Paper, we propose the following recommendations for the development of a theoretical framework in the emBRACE research project: -
Elaborate on the concepts of community and community resilience. The five types of community outlined in emBRACE Working Paper 1.1 (geographical communities, communities of interest, communities of circumstance, communities of supporters, and communities of identity) can serve as a basis for such an endeavor.
-
Define guiding questions for the framework, for example on what the most important systems, subjects or objects at risk are. Moreover, also identify the key perturbations or stressors (e.g. natural hazards) the case study deals with. This process should al-
56
so be influenced by and reflected against the background of the empirical work to be conducted in the case-studies (WP5)6.
6
-
Apply the core components of resilience identified in this Working Paper to the system, subject or object of analysis within the community.
-
Explore the interactions between and within the identified main and sub-components of resilience and their respective sets of criteria and indicators.
-
Reflect on the role of the key components of resilience, identified in this Working Paper, in developing the theoretical framework. Innovation, for example, is identified as a key component in resilience although we still lack sufficient information and examples about the role of innovation in building resilience.
-
Focus on key components and indicators developed in a natural hazard context rather than on those drafted in non-natural hazard contexts.
-
Pay adequate attention to the interactions and impacts of the key components in order to facilitate and accommodate all the indicators according to their disciplinary merit and importance.
There are five case studies in the emBRACE project. These are river floods in Central Europe (Germany, Poland, Czech Republic), earthquakes in Turkey, multiple hazards in South Tyrol, Italy and Grisons, heat waves in London, and combined fluvial and pluvial floods in Morpeth. For further information see emBRACE website at http://embrace-eu.org/casestudies/casestudies.htm. 57
8. References Agaibi, C. E., & Wilson, J. P. (2005). Trauma, PTSD, and Resilience. Trauma, Violence, & Abuse , 6 (3), 195-216. Allen, J. H., & Davis, N. (2010). Measuring operational resilience using the CERT resilience management model. Pittsburgh: Carnegie Mellon University. Boin, A., & McConnell, A. (2007). Preparing for Critical Infrastructure Breakdowns: The Limits of Crisis Management and the Need for Resilience. Journal of Contingencies and Crisis Management , 15 (1), 50-59. Bonanno, G. A. (2004). Loss, Trauma, and Human Resilience: Have We Underestimated the Human Capacity to Thrive After Extremely Aversive Events? American Psychologist , 59 (1), 20-28. Bonanno, G. A., Galea, S., Bucciarelli, A., & Vlahov, D. (2007). What Predicts Psychological Resilience After Disaster? The Role of Demographics, Resources, and Life Stress. Journal of Consulting and Clinical Psychology , 75 (5), 671-682. Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O'Rourke, T. D., Reinhorn, A. M., et al. (2003). A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities. Earthquake Spectra , 19 (4), 733-752. Buckle, P., Mars, G., & Smale, S. (2000). New Approaches to Assessing Vulnerability and Resilience. Australian Journal of Emergency Management, The , 15 (2), 8-14. Cabell, J. F., & Oelofse, M. (2012). An Indicator Framework for Assessing Agroecosystem Resilience. Ecology and Society , 17 (1). Cabinet_Office. (2011). Keeping the Country Running: Natural Hazards and Infrastructure. London: Cabinet Office. Cabinet_Office. (2012). National Risk Register of Civil Emergencies: 2012 Edition. London: HMG. Cabinet_Office. (2011). Strategic National Framework on Community Resilience. London: HMG. Carpenter, S., Walker, B., Anderies, J. M., & Abel, N. (2001). From Metaphor to Measurement: Resilience of What to What? Ecosystems , 4 (8), 765-781. Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC). Depression and Anxiety , 18 (2), 76-82. Cumming.S.G. (2011). Spatial Resilience in Socio-Ecological Systems. Wiesbaden: Springer. 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), 1-22. 58
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), 339-355. emBRACE. (2012). Early Discussion and Gap Analysis on Resilience. emBRACE Deliverable 1.1. Fredrickson, B. L., Tugade, M. M., Waugh, C. E., & Larkin, G. R. (2003). What Good Are Positive Emotions in Crises? A Prospective Study of Resilience and Emotions Following the Terrorist Attacks on the United States on September 11th, 2001. Journal of Personality and Social Psychology , 84 (2), 365-376. Freedy, J. R., Resnick, H. S., & Kilkpatrick, D. G. (1992). Responding to disaster: A guide for mental health professionals. In L. S. Austin (Hrsg.). American Psychiatric Press, Inc. Fritzon, Å., Ljungkvist, K., Boin, A., & Rhinard, M. (2007). Protecting Europe's Critical Infrastructures: Problems and Prospects. Journal of Contingencies and Crisis Management , 15 (1), 30-41. Gillard, M., & Paton, D. (1999). Disaster Stress Following a Hurricane: The role of religious differences in the Fijian Islands. The Australasian Journal of Disaster and Trauma Studies , 3 (2). Harrison, N. (2003). Good Governance: Complexity, Institutions, and Resilience. Paper Prepared for Presentation at the Open Meeting of the Global Environmental Change Research Community Montreal, Canada, 16-18 October, 2003. Tech. rep. HM_Government. (2005). Emergency Preparedness: Guidance on Part 1 of the Civil Contingencies Act 2004. London: Cabinet Office. Holling, C. (1986). The resilience of terrestrial exosystems, local surprises and global change. In W. Clark, & R. Munn (Eds.), Sustainable development of the biosphere. Cambridge: Cambridge Univ. Press. IFRCRCS. (2008). A Framework for Community Safety and Resilience: In the Face of Disaster Risk. Geneva: International Federation of Red Cross and Red Crescent Societies. Johnson, R. J., Canetti, D., Palmieri, P. A., Galea, S., Varley, J., & Hobfoll, S. E. (2009). A Prospective Study of Risk and Resilience Factors Associated With Posttraumatic Stress Symptoms and Depression Symptoms Among Jews and Arabs Exposed to Repeated Acts of Terrorism in Israel. Psychological Trauma: Theory, Research, Practice, and Policy , 1 (4), 291-311. Lepore, S. J., & Revenson, T. A. (2006). Resilience & posttraumatic growth: Recovery, resistance, and reconfiguration. In L. G. Calhoun, & R. G. Tedeschi (Eds.), Handbook of Posttraumatic Growth: Research and Practices (pp. 24-46). Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Lutha, S. S., & Cicchetti, D. (2000). The construct of resilience: implications for interventions and social policies. Development and psychopathology , 12 (4), 857.
59
Madsen, M. D., & Abell, N. (2010). Trauma Resilience Scale: Validation of Protective Factors Associated With Adaptation Following Violence. Research on Social Work Practice , 20 (2), 223-233. Mancini, A. D., & Bonanno, G. A. (2009). Predictors and Parameters of Resilience to Loss: Toward an Individual Differences Model. Journal of Personality , 77 (6), 1805-1832. Mayor_of_London. (2010). The Draft Climate Change Adaptation Strategy for London. Public Consultation Draft. London: Greater London Authority. McManus, S., Seville, E., Brunsdon, D., & Vargo, J. (2007). Resilience Management: A Framework for Assessing and Improving the Resilience of Organisations. New Zealand: Resilient Organisations. Mulilis, J.-P., & Lippa, R. (1990). Behavioral Change in Earthquake Preparedness Due to Negative Threat Appeals: A Test of Protection Motivation Theory. Journal of Applied Social Psychology , 20 (8), 619-638. Nolen-Hoeksema, S. (2000). Growth and resilience among bereaved people. In J. E. Gillham (Ed.), The science of optimism & hope: research essays in honor of Martin E. P. Seligman (pp. 107-128). Pennsylvania, PA: Templeton Foundation Press. Norris, F., Stevens, S., Pfefferbaum, B., Wyche, K., & Pfefferbaum, R. (2008). Community Resilience as a Metaphor, Theory, Set of Capacities, and Strategy for Disaster Readiness. American Journal of Community Psychology , 41, 127-150. O’Leary, M. (2004). Measuring disaster preparedness: a practical guide to indicator development and application. Lincoln, NE: iUniverse, Inc. Ong, A. D., Bergeman, C. S., Bisconti, T. L., & Wallace, K. A. (2006). Psychological resilience, positive emotions, and successful adaptation to stress in later life. Journal of personality and social psychology , 91 (4), 730-749. Pariès, J. (2006). Complexity, emergence, resilience. In E. Hollnagel, D. Woods, & N. Leveson (Hrsg.), Resilience engineering : concepts and precepts. Aldershot: Ashgate. Paton, D., Johnston, D., Smith, L., & Miller, M. (2001). Responding to Hazard Effects: Promoting Resilience and Adjustment Adoption. Australian Journal of Emergency Management, The , 16 (1), 47-52. Rüstemli, A., & Karanci, A. N. (1999). Correlates of Earthquake Cognitions and Preparedness Behavior in a Victimized Population. The Journal of Social Psychology , 139 (1), 91-101. Skodol, A. (2010). The resilient personality. In J. Reich, A. Zautra, & J. Hall (Eds.), Handbook of Adult Resilience (pp. 112-125). New York: The Guilford Press. Sumer, N., Karanci, A. N., Berument, S. K., & Gunes, H. (2005). Personal resources, coping self-efficacy, and quake exposure as predictors of psychological distress following the 1999 earthquake in Turkey. Journal of traumatic stress , 18 (4), 331-342.
60
Terte, I. d., Becker, J., & Stephens, C. (2009). An Integrated Model for Understanding and Developing Resilience in the Face of Adverse Events. Journal of Pacific Rim Psychology , 3 (1), 20-26. Tierney, K., & Bruneau, M. (2007). Conceptualizing and Measuring Resilience. A Key to Disaster Loss Reduction. TR News May-June , 14-17. Twigg, J. (2009). Characteristics of a Disaster Resilient Community: A Guidance Note. London: Aon Benfield UCL Hazard Research Centre. UNISDR. (2005). Hyogo Framework for Action 2005-2015. Building the Resilience of Nations and Communities to Disasters. Kobe, Hyogo: UNISDR. Weick, K. E., & Sutcliffe, K. M. (2007). Managing the unexpected : resilient performance in an age of uncertainty. San Francisco, Calif.: Jossey-Bass. Whitacre, J., & Bender, A. (2010). Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems. Theoretical Biology and Medical Modelling , 7 (1), 20. Woods, D. D. (2003). Creating foresight: How resilience engineering can transform NASA’s approach to risky decision making. unpublished. Woods, D. D. (2006). How to design a safety organisation: Test case for resilience engineering. In E. Hollnagel, D. Woods, & N. Leveson (Eds.), Resilience engineering : concepts and precepts. Aldershot: Ashgate. Woods, D. D., & Wreathall, J. (2003). Managing risk proactively: The emergence of resilience engineering. unpublished. Wreathall, J. (2006). Properties of resilient organisations: An initial view. In E. Hollnagel, D. Woods, & N. Leveson (Eds.), Resilience engineering : concepts and precepts. Aldershot: Ashgate. Zaidi, R., & Pelling, M. (2011). Vulnerability to Drought and Heat Wave in London: Revealing Institutionally Configured Risks. Handbook of Vulnerability Assessment in Europe. MOVE handbook compendium.
61
This study has been funded by the th
European Commission on the 7 Framework Programme
Centre for Research on the Epidemiology of Disasters (CRED) Catholic University of Louvain School of Public Health 30.94 Clos Chapelle-aux-Champs 1200 Brussels, Belgium
T: +32 (0)2 7643327 F: +32 (0)2 7643441 E:
[email protected] W: http://www.cred.be
Northumbria University School of the Built and Natural Environment, Newcastle upon Tyne NE1 8ST, UK T: + 44 (0)191 232 6002 W: www.northumbria.ac.uk
62
