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The purpose of this paper is to focus on the large-scale flood response coordination across sectors and jurisdictions, investigating the characteristics and gaps of the 2011 Thailand flood response operations.

The large-scale flood response coordination was measured as an inter-organizational network. An extensive content analysis of news reports was conducted to identify the participating organizations and relationships among them that emerged during the initial flood response operations. Social network analysis was used to examine the patterns and gaps of coordination among the organizations.

The research identified three major gaps that might weaken the response coordination. First, the coordination structure was highly fragmented with many isolated actors. Second, the benefit of inter-sector relationships was not well leveraged in the system due to weak reciprocal relationships across sectors. Third, provincial level organizations did not serve as a strong liaison between local actors (cities) and national actors.

Based on the findings, the research offers suggestions to improve the performance of response coordination in recurring flood disasters.

This study is distinctive in its examination of structural characteristics of large-scale, inter-sector and multi-jurisdictional flood response coordination in Thailand. Previous studies have explored how citizens were organized and responded to flood disasters at the local level, and measured indicators or causes of response resilience at the provincial level system. Yet, studies examining the patterns of coordination structure among response organizations across all affected-jurisdictional authorities and sectors have been lacking.

This study aims to examine and understand South Korea’s (S. Korea) COVID-19 response operations, a notable case for other countries to emulate, and suggest some practical implications for other countries struggling with coping with the current pandemic.

To examine the case, the authors propose a new theoretical framework based on concepts of the whole community approach in the emergency management field and on co-production in public administration studies, and use the theoretical framework to analyze the details of S. Korea’s whole community co-production for COVID-19 response.

The findings demonstrate that the successful pandemic response in S. Korea is attributable to a nationwide whole community co-production among multiple actors, including government, various industries, sectors, jurisdictions and even individual citizens, within and across relevant public service and public policy domains.

This study suggests a new theoretical framework, whole community co-production, which contributes to the conceptual advancement of co-production in the field of public administration and a whole community approach in the field of emergency and crisis management. The framework also suggests practical implications for other countries to integrate whole community coproduction that may transform current response operations to cope with COVID-19.

The purpose of this paper is to elaborate pros and cons of two coding methods: the rapid network assessment (RNA) and the manual content analysis (MCA). In particular, it focuses on the applicability of a new rapid data extraction and utilization method, which can contribute to the timely coordination of disaster and emergency response operations.

Utilizing the data set of textual information on the Superstorm Sandy response in 2012, retrieved from the LexisNexis Academic news archive, the two coding methods, MCA and RNA, are subjected to social network analysis.

The analysis results indicate a significant level of similarity between the data collected using these two methods. The findings indicate that the RNA method could be effectively used to extract megabytes of electronic data, characterize the emerging disaster response network and suggest timely policy implications for managers and practitioners during actual emergency response operations and coordination processes.

Considering the growing needs for the timely assessment of real-time disaster response systems and the emerging doubts regarding the effectiveness of the RNA method, this study contributes to uncovering the potential of the RNA method to extract relevant data from the megabytes of digitally available information. Also this research illustrates the applicability of MCA for assessing real-time disaster response networks by comparing network analysis results from data sets built by both the RNA and the MCA.