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Recent disasters have highlighted the need to better understand why communities recover differently from the same disaster. This research aims to study what pre- and post-disaster conditions lead to infrastructural and social recovery. We collected data from 15 villages in India that were affected by the 2004 Indian Ocean Tsunami through observations, interviews, and secondary sources on pre-disaster community conditions, post-disaster strategies, and infrastructural and social recovery outcomes. We examined conditions posited to affect recovery and analyzed the data using fuzzy-set qualitative comparative analysis. There were multiple pathways to infrastructural and social recovery, but strong access to government resources and good recovery agency coordination were necessary in all pathways. A lack of social vulnerability, recovery agency embeddedness, and contracting agency oversight were also important. Through this research, we extend theories of community resilience and vulnerability by linking both pre- and post-disaster conditions to multi-sector recovery outcomes. Using these findings, practitioners can target specific dimensions of community resilience prior to disasters and target successful post-disaster strategies to contribute to recovery.

Jordan, E., Javernick-Will, A., and Tierney, K. (2016). “.”&�Բ�����;Natural Hazards. 84 (2), 1327–1347. doi: 10.1007/s11069-016-2489-4

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As disaster losses continue to rise around the world, it has become increasingly important to understand the long-term outcomes of post-disaster recovery programmes. Often, disaster recovery projects have an abbreviated planning period, involve multiple NGOs, and lack long-term plans for evaluation. This article describes outcomes of the shelter reconstruction programme following the 2004 Indian Ocean tsunami in Nagapattinam, India. Quantitative and qualitative data were collected to assess the effect of the programme on housing, community infrastructure, and livelihoods. The study provides useful lessons for future reconstruction programmes and demonstrates the importance of evaluating post-disaster recovery programmes after projects end.

Jordan, E., Javernick-Will, A., and Amadei, B. (2015). “." Development in Practice. 25 (4), 518-534. doi: 10.1080/09614524.2015.1028334

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As the number and economic impact of disasters rise annually, additional information is required to understand the recovery process. Clearly, any theory of disaster recovery will require the identification of factors that cause vulnerability and resilience, as these can enable or impede successful recovery. The authors performed a content analysis of journal articles from 2000 to 2010 in four disaster-focused journals to identify the factors posited to influence vulnerability and resilience from multiple disciplinary perspectives. Factors were identified in the areas of infrastructural, social, economic, institutional and post-disaster recovery strategy. A panel of experts then validated these factors through a multi-round Delphi survey by rating the level of importance of each factor and providing reasoning on their ratings. All causal factors identified received median ratings of at least important, but not all came to consensus. This paper synthesizes findings related to resilience and vulnerability from many researchers in a variety of fields. This multi-disciplinary perspective may help propel future research to consider the interactions between these multiple factors and empirically examine the link between these factors and community recovery.

Jordan, E. and Javernick-Will, A. (2014).&�Բ�����;“.”&�Բ�����;International Journal of Mass Emergencies and Disasters. 32 (3), 405-427.

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Purpose

The purpose of this research is to examine why communities facing the same disaster recover differentially and determine pathways to successful disaster recovery in the research setting of New Orleans neighborhoods affected by Hurricane Katrina. While previous studies suggest that there are a variety of pathways to recovery, a broader cross-case comparison is necessary to generalize these pathways into a recovery framework. Specifically, this study seeks to determine what pre-disaster and post-disaster causal factors, alone or in combination, were important to recovery following Hurricane Katrina.

Design/methodology/approach

This paper presents a cross-case comparative study of neighborhood-level recovery. Based on prior work, which used the Delphi method to determine hypothesized causal factors and indicators of recovery, data was collected through publically available sources, including the US Census, the Greater New Orleans Community Data Center and previously completed studies for 18 damaged neighborhoods. Fuzzy-set qualitative comparative analysis was used due to its ability to analyze both quantitative and qualitative data for smaller case studies.

Findings

The results show that there are multiple pathways combining pre-disaster community factors and post-disaster actions that led to recovery, as measured by population return. For example, economic capacity is nearly sufficient for recovery, but a combination of low social vulnerability, post-disaster community participation, a high proportion of pre-World War II housing stock and high amounts of post-disaster funds also led to recovery.

Originality/value

This research uses a novel method to link pre-disaster measures of resilience and vulnerability to recovery outcomes and, through cross-case comparison, generates results that will enable researchers to develop a theory of sustainable community recovery.

Jordan, E., Javernick-Will, A., and Amadei, B. (2014). "." International Journal of Disaster Resilience in the Built Environment. 5 (4), 391-412. doi: 10.1108/IJDRBE-03-2013-0006

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Disaster recovery has been studied from a variety of perspectives including the fields of sociology, engineering, policy implementation, political-ecology, systems theory, geography, and urban planning, leading to a wide variety of definitions and indicators for measuring recovery. To assess what indicators can be used to measure both predisaster resilience and postdisaster recovery, an in-depth content analysis of recovery indicators in the existing literature was performed. Articles from 2000 to 2010 in four disaster-focused journals that include perspectives of engineers, social scientists, practitioners, and economists were analyzed. Articles were selected by a keyword search and analyzed for recovery indicators using an emergent coding scheme. Interestingly, many research articles never defined recovery. Recovery indicators were categorized as social, economic, environmental, and infrastructural. The indicators cited were analyzed based on the disciplinary affiliation of the author. Authors from different disciplines cited different indicators, suggesting that increased interdisciplinary collaboration may be needed. As a second step in this research, a multiround Delphi survey was used to obtain expert opinion on the recovery indicators. This process verified that the set of indicators identified through the content analysis were important and provided a rating of the importance of each indicator. Panelists also provided justifications for any ratings that differed from the median. Researchers can use these results as indicators of recovery in future studies. Similarly, practitioners will be able to use the condensed opinions of experts in the field of disaster recovery and planning.

Jordan, E. and Javernick-Will, A. (2013). “.”&�Բ�����;Natural Hazards Review. 14 (1), 21-28. doi: 10.1061/(ASCE)NH.1527-6996.0000087

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Research in construction is often confronted with a trade-off of selecting either in-depth studies of small-N cases, which may affect generalization of findings, or statistical large-N studies, which may limit examination of causal links. Qualitative comparative analysis (QCA) provides a middle ground between these options, allowing researchers to analytically determine different combinations of conditions that produce an outcome in comparative studies. QCA has been applied extensively in other fields; however, the method has only recently started to gain traction in construction research. Guidance on the implementation of QCA is provided, including: a description of the method and its variants; stages required for its application; its benefits and critiques; applications in the construction field; and recommendations for scholars employing the method. QCA is a promising approach for probing causal links via investigations between variable-based, large-N analyses and qualitative, case-based, small-N studies. However, researchers must not use the method in haste or simply to obtain quantitative results from qualitative data. It requires significant time and rigour to determine and justify the conditions, outcomes and cases used in its application. QCA is well suited for research where interactions between conditions and outcomes are not well understood and can be used to build theory in the complex environment of construction.

Jordan, E., Gross, M., Javernick-Will, A., and Garvin, M. (2011). “.”&�Բ�����;Construction Management and Economics. 29 (11), 159-1173. doi: 10.1080/01446193.2011.640339

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