10.05 Sustainable inter-organizational networks for post-disaster recovery

Aim of the project
The aim of this project is to investigate whether and how post-disaster community recovery (operationalized as population change and restoration of buildings) can be explained by variations in the sustainability of collaborations in interorganizational networks. The project focuses on three different areas hit by earthquakes in Italy in 2009, 2012 and in 2016.

Theoretical background
Post-disaster recovery refers to the ability of an area affected by a major disaster to return to its pre-disaster condition. Recovery is an extended and nonlinear process that can take many years and it can be assessed in multiple ways. As an outcome, it can be measured as economic recovery, population change, restoration of buildings and infrastructure, or the return of regular behavioural routines (Aldrich, 2012; Vale & Campanella, 2005). Irrespective of the way in which the outcomes are measured, studies on community recovery across the globe show that there are several different factors that can explain why some regions, towns or neighborhoods recover more easily, while others, with similar characteristics, take much longer or never recover. Standard explanations mention quality of governance, aid received, and severity of the damage caused by the disaster, socioeconomic and demographic conditions, and variation in population as the most relevant factors used to explain variations in recovery rates. Other approaches stress the importance of social capital, operationalized as number of local voluntary organizations, voting rates and levels of trust (Aldrich, 2012). A third, and less explored, cluster of explanations refers to the role of networks of organizations involved in the management of the recovery phase.

Networks of collaborating organizations constitute the backbone of disaster management (Edwards, 2009) because of the necessity to involve multiple actors to deal with the complexity of disaster preparedness, emergency and recovery. Crisis management organizations are usually designed as “network organizations” (Ansell, Boin, Keller, 2010). But achieving and maintaining effective collaborations among multiple agencies that need to interact with each other synergistically and over time (Van Veelen, Storms, & van Aart, 2006) presents several challenges.

There is a large body of research on interorganizational collaborations in disaster preparedness and management across different countries (Jovita et al, 2018; Crow, Albright, 2019), but their effectiveness in post-disaster recovery is understudied. Given that disaster recovery is managed by networks of different organizations (municipalities, NGOs, first responders, governmental agencies – either existing or created ad hoc for a specific emergency), that need to face different demands, and to adapt in the course of the restoration phase (that can last for many years), it is very important to understand under which conditions these networks are sustainable and effective in promoting recovery.

Previous work has identified the conditions favoring the creation of interorganizational collaborations (Agranoff, McGuire, 2003; McGuire, Silvia, 2010), and several case studies explored the failures of previously established collaborations between multiple organizations in the course of a crisis (Kiefer, Montjoy, 2006). What makes these collaborative networks sustainable over time? What are the determinants of their ability to adapt to the changing needs of the recovery process and to the often-changing institutional landscapes? The theory of ‘collaborative resilience’ (Getha-Taylor, 2019) puts forward a set of characteristics that can be used to identify interorganizational partnerships that last, distinguishing between the individual, collaborative and systemic level. Collaborative resilience, as the ability of systems and partners to work together on shared goals despite disruptions, builds upon collaborative advantage, life cycle and adaptive capacity theories and develops a set of predictors of resilience. By comparing nineteen voluntary collaborations that worked on long term and generally intractable community issues, Getha-Taylor (2019) highlights a list of key factors that promote collaborative resilience (social capital, leadership, structure, etc.), along with factors that hamper it (stress, internal changes, and resources loss, among others).

This project will extend the framework of collaborative resilience in two ways. First, a network approach will be adopted, therefore going beyond dyadic relationships and using network explanations of cooperation. Second, in line with the SCOOP perspective on value creation, the project will investigate whether stable interorganizational networks can create value in post-disaster restoration for citizens, organizations and societies. Stable networks of organizations are necessary to manage the restoration phase effectively (meaning that the objectives are met in the desired period and that the affected area can return to the pre-disaster situation), but partnerships that last are not necessarily sustainable. Even if the organizations collaborate despite changes and disruptions, this does not necessarily mean that they will create value. For instance, corruption is not uncommon in the management of disaster mitigation, relief, and recovery (Alexander, 2017), regardless of the nature and the location of the disaster (Leeson, Sobel, 2007; Imperiale, Vanclay, 2019).

Distinguishing between lasting collaborations that create value and those that do not is important to understand when interorganizational network structures and processes are conducive to positive (or negative) consequences for individuals, organizations and society. This project will combine organizational sociology, social network theory and conceptual analysis with the aim of answering the following questions: “ “Under which conditions is cooperation between networks of organizations active in post-disaster recovery sustainable (i.e., it is stable and creates value) and to what extent can variation in the cooperation explain differences in post-disaster community recovery?"

Research design

Italy is one of the most exposed European countries in terms of natural hazards, and it is among the countries with the highest seismic risk in the Mediterranean, due to its geographical position in the zone of confluence between the African and Eurasian clusters. In the last 15 years, three major earthquakes (with a magnitude >5) hit the country, with a total death toll of 630 victims. The project will focus on the post-disaster reconstruction of different areas affected by these 3 events: L’Aquila in 2009, the Emilia earthquake in 2012 and a series of earthquakes that hit four regions in Central Italy in 2016. The case study disasters span a period of 10 years and cover different regions that vary with regard to their main economic activities. Most importantly for the project, different interorganizational network structures were designed for the reconstruction process in each of the disasters.

A mixed method approach will be applied to collect and analyze a variety of primary and secondary data sources. First, three different publicly available datasets provide quantitative indicators documenting the restoration process (L’Aquila, Emilia Romagna; Central Italy). Each dataset provides information about damage assessment and reconstruction at different time points (including the number of expected funding requests for rebuilding, the planned reconstruction process and the current situation). This data offers an updated overview of how much has been rebuilt. Second, these datasets will be linked to municipal records about the number of people who moved back to their homes as a proxy of community restoration. Third, information about the creation, change and dissolution of organizational collaboration structures will be acquired through the analysis of national and local policy documents (governmental decrees, regional and local legislation, local regulations) and through interviews with stakeholders from the involved organizations and communities. The project will require the acquisition and analysis of different kinds of data in Italian, therefore a good command (B2 and higher) of the language is an asset.

Literature
Braham, M., & van Hees, M. (2018). Voids or Fragmentation: Moral Responsibility For Collective Outcomes. The Economic Journal, 128(612), F95–F113.
Bodin, Ö., & Nohrstedt, D. (2016). Formation and performance of collaborative disaster management networks: Evidence from a Swedish wildfire response. Global Environmental Change, 41, 183-194.
Berthod, O., Grothe-Hammer, M., Müller-Seitz, G., Raab, J., & Sydow, J. (2017). From high-reliability organizations to high-reliability networks: the dynamics of network governance in the face of emergency. Journal of Public Administration Research and Theory, 27(2), 352-371.
Eiser, J. R., Bostrom, A., Burton, I., Johnston, D. M., McClure, J., Paton, D., ... & White, M. P. (2012). Risk interpretation and action: A conceptual framework for responses to natural hazards. International Journal of Disaster Risk Reduction, 1, 5-16.
Heyse, L., Morales, F. N., & Wittek, R. (2021). Evaluator perceptions of NGO performance in disasters: meeting multiple institutional demands in humanitarian aid projects. Disasters, 45(2), 324-354.
Mongin, P., & Pivato, M. (2016). Social evaluation under risk and uncertainty. In The Oxford Handbook of Well-Being and Public Policy.
Pescaroli, G., & Alexander, D. (2018). Understanding compound, interconnected, interacting, and cascading risks: a holistic framework. Risk Analysis, 38(11), 2245-2257.
Robinson, S. E., Eller, W. S., Gall, M., & Gerber, B. J. (2013). The core and periphery of emergency management networks. Public Management Review, 15(3), 344-362.
Stefanovic, I. L. (2003). The contribution of philosophy to hazards assessment and decision making. Natural Hazards, 28(2-3), 229-247.

Project initiators
prof. dr. Rafael Wittek (Sociology) 

dr. Francesca Giardini (Sociology) 

prof. dr. Martin van Hees (Philosophy)

Location
Groningen.

Expertise
Sociology, Philosophy