A Systematic Review of Empirical Emergency Management Network Research: Formation and Development, Properties, and Performance

Published date01 May 2022
AuthorNaim Kapucu,Jungwon Yeo,Qian Hu
Date01 May 2022
DOI10.1177/02750740221077348
Subject MatterArticles
A Systematic Review of Empirical
Emergency Management Network
Research: Formation and Development,
Properties, and Performance
Qian Hu
1
, Jungwon Yeo
1
, and Naim Kapucu
1
Abstract
Although network analysis has gained much attention in emergency manageme nt studies, there are few systematic reviews of
emergency management network studies in public administration. After reviewing 44 journals, this article identied and
reviewed a total of 58 studies that conducted network analysis in the context of emergency management. Based on existing
literature, this article summarizes the common and unique factors driving network formation and development, describes the
structural characteristics of emergency management networks, and reports the performance measures that have been used to
evaluate network performance. It concludes by addressing research gaps, presenting propositions and recommendations for
future research, and highlighting implications for emergency management practice. The context of this review is emergency
management, but the three network research streams focused uponnetwork formation and development, network prop-
erties, and network performanceare relevant to all management and policy domains. This review also underscores the need
to further explore the dynamic process of network formation and outcomes of network relationships and structures.
Keywords
emergency management networks, network analysis, systematic review
Introduction
Over the past two decades, the number of network studies
and the use of network analysis have grown rapidly in the
elds of public administration and public policy (Berry
et al., 2004; Hu et al., 2016; Isett et al., 2011; Provan et al.,
2007; Siciliano et al., 2021). Public administration scholars
have conceptualized networks as collective interorganiza-
tional arrangements operating to achieve common manage-
ment or policy goals (Agranoff & McGuire, 2001; Isett
et al., 2011; Popp et al., 2014; Provan et al., 2007).
Networks have also been dened as a distinctive form of gov-
ernance that, when engaging in collective decision-making
and coordinated action, relies more on horizontal relation-
ships than hierarchical authorities and the chain of
command (Koliba et al., 2010; Nowell & Steelman, 2019;
OToole, 1997). A network approach to coordination encour-
ages organizations to strengthen existing relationships and
build new relationships with other organizations. Through
network arrangements, organizations can expand their
access to information, knowledge, and resources (Isett
et al., 2011; Provan & Lemaire, 2012). Interorganizational
networks can also contribute to the accumulation of social
capital and member organizationscommitment to shared
goals (Berardo & Scholz, 2010). Well-connected coordinated
networks are better able to integrate services and improve
service quality (Provan et al., 2005). Furthermore, such a
exible network approach fosters learning across unit bound-
aries, encourages innovation, and prepares organizations for
emergent situations (Provan & Lemaire, 2012).
Network arrangements are used to address various man-
agement and public policy issues such as human and social
service delivery, environmental management, and regional
economic development (Milward & Provan, 2003; Lee
et al., 2012; Robins et al., 2011). Emergency management
is an area abundant with network applications and research
(Comfort et al., 2012). The number of empirical network
studies is ranked third among all service domains (Kapucu
et al., 2014). Emergencies demand that organizations work
across organizational, sector, and jurisdictional boundaries
to form emergency management networks. Emergencies
1
School of Public Administration, University of Central Florida, Orlando, FL,
USA
Corresponding Author:
Qian Hu, School of Public Administration, University of Central Florida,
Orlando, 528 W Livingston St, Orlando, FL 32801, USA.
Email: qian.hu@ucf.edu
Article
American Review of Public Administration
2022, Vol. 52(4) 280297
© The Author(s) 2022
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/02750740221077348
journals.sagepub.com/home/arp
provide an important context for addressing and studying
public organization management and performance issues
(Bryson, 2021; OToole & Meier, 2015). Recent catastrophic
natural hazards such as hurricanes, earthquakes, and wildres
are constant reminders that emergency management
1
is the
quintessential government role(Waugh, 2000, p. 3) and
a central activity of public administration(Petak, 1985,
p. 3). How to improve interorganizational communication
and coordination in emergency management across sectors
and jurisdictions continues to be a fundamental question
for public administration (Waugh, 2007; Comfort et al.,
2012).
Unlike conventional statistical analyses that focus on
actorsattributes, network analysis refers to a wide range of
methods and tools employed to analyze relationships
among actors and examine relational processes and outcomes
(Scott, 2013; Wasserman & Faust, 1994). Network analysis
allows researchers to investigate the formation, development,
and consequences of dynamic interactions among actors
(Kapucu & Hu, 2020). The relational focus is crucial to
understanding and assessing the structure and process of
interorganizational communication and coordination among
the many actors involved in emergency management.
Network analysis has been used to identify key actors in
emergency response systems, measure the strength and
quality of relationships among organizational actors, describe
the structural and procedural patterns of interorganizational
relationships, and evaluate the impacts of such relations
(e.g., Comfort & Haase, 2006). Research has stressed build-
ing and sustaining relations and trust for better communica-
tion and coordination before disasters occur (e.g., Comfort,
2019; Kapucu & Garayev, 2013; Van Wart & Kapucu,
2011). Through network analysis, public administration
scholars and practitioners have begun to investigate the
importance of networks in coping with emergencies and
crises.
Although the network approach to emergency manage-
ment and the use of network analysis have received
growing attention from scholars and practitioners (Comfort
et al., 2012), there are few systematic reviews of emergency
management network literature. Existing reviews of network
literature have reected on the evolution of emergency man-
agement research in public administration (e.g., Comfort
et al., 2012) and examined broad research on collaborative
emergency management (e.g., Nohrstedt et al., 2018).
However, to our knowledge, there is a lack of systematic
review of empirical emergency management network
research applying network analysis to provide guidance for
scholars and practitioners in the eld.
The goal of this article is to synthesize key ndings from
the existing empirical emergency management network
research conducted via network analysis, identify potential
research gaps, and provide practical implications for emer-
gency management professionals to form and develop collab-
orative networks. This review summarizes ndings from
three network research streamsnetwork formation and
development, network properties, and network performance,
which are relevant for all management and policy domains.
Furthermore, the summary of ndings in emergency manage-
ment can be compared with network research in other con-
texts to identify and discuss common and unique patterns
of network relations, structures, and consequences. In the fol-
lowing sections, this study discusses emergency management
networks and the methods used for selecting the most rele-
vant literature. This study also introduces a conceptual
framework to present ndings, including: (a) how networks
are formed and developed, (b) what properties (attributes
and structures) characterize emergency management net-
works, and (c) how such networks are evaluated for
effectiveness. Finally, this article discusses the ndings and
suggests future directions for emergency management
network scholarship and practice in the eld of public
administration.
Emergency Management Networks
in Public Administration
Emergencies, especially large-scale disasters and extreme
events, require quick, well-coordinated responses across
jurisdictions, sectors, and organizational boundaries
(Waugh & Streib, 2006). Take the U.S. emergency manage-
ment as an example. The U.S. emergency management
system includes federal, state, regional, and local emergency
management agencies and other government agencies, as
well as nonprot organizations, faith-based organizations,
other community organizations, and businesses (Waugh,
2000). The system is a multilevel network that includes a
wide range of organizations and their multiple types of rela-
tions. Cross-sector and interorganizational collaboration is a
necessity for coping with transboundary disasters, regardless
of differences in governance systems across countries (Ansell
et al., 2010).
Emergency management networks are interorganizational
arrangements operating to prevent, protect, mitigate, respond
to, and recover from emergencies. Emergency management
networks consist of organizational actors (i.e., nodes) and
the relationships (i.e., ties) that connect actors. Such relations
can include either vertical or horizontal interactions among
organizations to exchange information or resources and
joint efforts of organizations in completing a specic task
or emergency support function pertaining to emergencies.
In a network diagram in Figure 1, the circles represent differ-
ent actors and the lines represent a diverse range of interac-
tions that occurred among these actors.
Actors in emergency management networks include a
wide range of government agencies, nonprots, and business
organizations. Examples of government agencies include
those responsible for emergency management, public
health, public safety, and emergency response. Examples of
Hu et al. 281

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