Association for Public Policy Analysis & Management

Effective decision making in disaster recovery involves both rapid scaling up of resources and personnel from external sources to rebuild a damaged community, and consequent scaling down of this influx of new actors, organizations, and resources as the community returns to daily operations. Integrating new concepts, technologies, and resources into communities to rebuild the social, economic, and political infrastructure in stronger, more sustainable ways, as well reconstructing the damaged technical infrastructure represents a challenging set of problems for any community. This problem is critical in environments exposed to recurring risk of interacting hazards that characterize metropolitan regions today. This analysis examines the process of decision making initiated at national, regional, district, and municipal levels in Nepal following the April 25 and May 12, 2015 earthquakes as a field study of this process in action. Drawing from organization theory, complex adaptive systems, and network theories, we examine the functions of scalability and sustainability in disaster risk reduction, mitigation, relief and recovery activities due to enhanced access to information that is vital for building trust and mobilizing resources and collective action.

We focus on how ICTs render their impact via multiple channels to support recognition of shared risk, dynamic information exchange, and double-loop learning in the process of collaborative decision making under stress. In addition, we explore the risks of rapid transmission of inaccurate information and rumors under highly stressful and volatile conditions. We build on findings from an initial brief reconnaissance trip to Nepal, June 30 – July 10, 2015, just as response operations were ending and the transition to recovery was beginning. This period captured the initial stage of the recovery process. We sought to identify the organizational structure through which transition activities operate and the communication and coordination processes that enhance or impede the development of sustainable, disaster-resilient communities as they recover from disaster. We will confirm this initial assessment during a second field trip in April 2016.

We have collected three types of data: documentary reports from professional organizations and government agencies, newspaper reports from electronic media, and qualitative data from semi-structured expert interviews. For documentary analysis, we trace the logic of governmental action for managing risk and recovering from disaster that is stated in public laws, policies, and documents, using process tracing. For electronic media, we use content analysis to identify key actors, organizations, transactions, and interactions among actors, and conduct a network analysis, using standard measures of centrality, distance, closeness, and clustering. We use expert interviews and satellite maps to validate findings from other methods of analysis. Using these data, we compare the formal plans to documented action by key actors and organizations through the transactions and interactions that we identify from content analysis of news media and situation reports. We will use analytic techniques appropriate to each type of data: social network analysis, Bayesian nets, and External/Internal Indices to identify the threshold points of change in information flow and consequent shifts in system performance. This study is supported by NSF RAPID grant #1559687.