Transformative Development and Disaster Risk Management

Introduction

In light of the connection between development and disaster risk reduction, it is important to explore what constitutes transformative disaster risk management. This literature review summarises our current scientific knowledge on the transformative character of disaster risk management: what we know about the relationship between disaster risk management and development; how it has evolved over the past years; and where the research gaps are in our present knowledge. This report was commissioned by UNISDR to inform the 2015 Global Assessment Report on Disaster Risk Reduction, section on the Future of Disaster Risk Management. It builds on work conducted for the IRDR Assessment of Integrated Research on Disaster Risk (AIRDR) (IRDR AIRDR Publication No. 1).

Five key policy questions are addressed in this review*:

1. How does transformation relate conceptually to research on vulnerability and resilience?
2. What areas of disaster risk reduction have the potential to transform development?
3. Do incremental steps of improved disaster risk management lead to transformed policy and practice?
4. What are concrete development benefits of transformative disaster risk management?
5. How can progress in disaster risk reduction and development be measured?

The results section is divided into three central research themes that emerged from the reviewed literature. Each research theme – called a knowledge cluster – begins with a brief summary of the current state of knowledge and then moves to remaining challenges within the specific research domain. The results section concludes with knowledge gaps and systemic shortcomings in transformative disaster risk reduction research.

*Download from the right-hand column or via the link provided under Further Resources. The text below provides a brief overview of the methods, results and conclusions of the review; please see the full text for much more detail.

Methods and Tools (abridged)

For the purpose of this review, a subset of 63 transformation-related articles within the AIRDR database were supplemented with 182 additional articles based on a keyword search utilising the academic citation indexing and search service Web of Science. By using this combined approach it was possible to minimise two biases: focusing solely on indexed Œjournals and analysing only jŒournals that publish specifically on disaster risk. Some challenges remain and could not be overcome. Those are the exclusion of monographs, edited books, grey literature and non-English language publications because a) the quality of the peer-review process is not transparent, and b) the review and classification criteria (see below) could not be transferred. Furthermore, research on war or civil unrest, technological hazards (e.g. oil spills), climate (e.g. El Niño), and diseases (e.g. malaria) were also excluded to keep the focus on natural hazards.

The methodology and literature analytics involved content and cluster analysis. The goal was to identify key topics, study areas, methodological approaches, authorship, and changes in publication output over time. Additionally, a word count analysis (based on stemmed words, e.g. government, govern, governance) was performed on the full texts of all 245 publications to identify central themes in research on disaster governance. To group and classify similar research, publications were coded using 50 keywords derived from the initial content analysis as well as the word count analysis. Subsequent cluster analyses on these coded publications enabled the grouping of the publications into the prevalent knowledge domains discussed in the results section.

Results (in brief)

While increasingly pervasive in the development and sustainability literature, the concept and term transformation are additions to the vocabulary of disaster risk reduction. Consequently, most of the research reviewed in this background paper draws on research conducted on climate change adaptation, vulnerability and resilience, where the idea of transformation has more currency rather than explicit transformative disaster risk reduction work.

As Figure 2 (below) shows, publications on transformation-related disaster risk reduction research have significantly increased in recent years. The primary focus remains largely at a conceptual level and is driven by theoretical discussions surrounding drivers (e.g., social learning) and elements of change (e.g., participation and mainstreaming).

Knowledge Clusters

Broadly speaking, there are three research clusters constituting the current knowledge on transformative disaster risk management:

1. drivers of transformation;
2. technical and adaptive elements of social learning (e.g. participation, representation, and integration); and
3. case studies of transition.

The current state of knowledge and remaining challenges for each of these knowledge clusters are explained in detail the review (pages 7-12).

Knowledge Gaps

1. Learning Processes: Beyond the context of disaster governance, there is limited, explicit research on learning processes in disaster risk reduction (Amundsen 2012; Bierbaum et al. 2012; Eriksen et al. 2009), especially the processes leading to institutional change and social transformations.
2. Thresholds and Limits of Disaster Risk Reduction: There is a lack of knowledge and empirical evidence on thresholds to adaptation and disaster risk reduction. Much is known about tipping points, regime shifts and transformations in nature (Biggs et al. 2009; Scheffer 2009), but a similar understanding of the boundaries of the social system is absent (Alexander 2013). Some even argue that conventional assessment approaches are not equipped to capture these system dynamics adequately and instead call for new methodologies, which, for example, consider transformation barriers as well as social learning (Tschakert et al. 2013). Thus, our present knowledge is unlikely to enable monitoring or detection of transformation or regime shifts in community resilience.
3. Incentives, Barriers and Power Structures:reduction and climate change adaptation is not necessarily in the interest of powerful stakeholders since it challenges the practice (and winners) of development (Cannon and Müller-Mahn 2010). The consequence is that social systems are less amenable to rapid change and somewhat locked-in (Han and Kasperson 2011; Pelling and Manuel-Navarrete 2011). Furthermore, initiating deliberate transformation appears risky because the outcomes and benefits cannot be predicted with certainty.
4. Systemic Shortcomings in Transformative Disaster Risk Reduction Research: The focus on drivers of transformative disaster research is mirrored in the authorship of the 245 analysed journal articles. The disciplines of geography, environmental studies, planning and development, economics and engineering dominate the research landscape —similar to research on disaster governance (Gall, Cutter, et al. 2014a) and incentives in disaster risk management (Gall, Cutter, et al. 2014b). These disciplines engage predominately in assessing resilience and vulnerability and modeling impacts. Disciplines that could contribute knowledge on sector-specific transformation (e.g., business administration) or organisational and institutional learning (e.g., sociology, psychology) are far less involved.

Conclusions

Although knowledge on vulnerability, adaptation and resilience has ešxpanded significantly in recent years, a rift between knowledge and action/change persists. In fact, the combined effects of transformation barriers such as institutional structures that resist learning, lack of accountability, and rising vulnerabilities continue to thwart efforts for new ways to reduce the ešcessive disaster losses especially among the most vulnerable.

Transformative development and disaster risk reduction needs actionable research. However, transforming the status quo of development approaches and objectives is a tall order for disaster risk management, particularly in the absence of any measurable and significant progress toward sustainable development over the past decades (Dittmar 2014). Some argue that existing power relations have blocked a transformation of development over the past 40 years and that disaster risk reduction and climate change adaptation efforts should learn from these ešperiences (Cannon and Müller-Mahn 2010). Although disaster risk management has transformative potential, it is presently unclear what such a transformation should look like. What is the future direction or state that is desirable and for whom?

Thus far, observed transitions in, for example, the agricultural and tourism sectors are the product of forced transition and immediate threats to livelihoods. Incremental steps tend to be conservative. Comprehensive and radical transformations in high-risk areas such as coastal zones are missing and, as a result, conficting and competing adaptation strategies are omnipresent. Surprising is the lack of research on transformative efforts in rich countries, which should be well-resourced to develop innovative solutions. Notable exceptions are countries such as The Netherlands where transition management is part of a broader climate mitigation policy rather than disaster risk reduction (Rotmans et al. 2001; Smith and Kern 2009).

In order for transformation not to become the next buzzword, there must be some caution against the diminution of the term transformation in the context of disaster risk management by undermining its “radical potential” (Pelling 2014). However, maintaining an idealistic notion of transformation as radical change may exceed practicality and overstate what transformative disaster risk reduction can truly achieve. Shove (2010) even questions the suitability of social sciences research in tackling these issues given their focus on what she calls “the paradigm of ‘ABC’—attitude, behaviour, and choice.” Instead she advocates societal innovation and fundamental social changes.

What is needed are honest and comprehensive assessments providing concrete evidence of the capacity and advancements in disaster risk reduction at all scales to determine the current status along the adaptation continuum and the feasible progress toward transformation. The necessity is clear, but the barriers may be difficult to overcome.