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Interest in networks in the fields of public management and policy has grown to encompass a wide array of phenomena. However, we lack a stable and empirically verifiable taxonomy for delineating one network class from another. The authors propose all networks and multi-organizational collaborative entities can be sorted into three taxonomic classes: structural-oriented, system-oriented, and purpose-oriented. This Element reviews the intellectual disciplinary histories that have informed our understanding of each of the three classes of networks. It then offers a taxonomic description of each of the three classes of networks. Finally, it provides a field guide for empirically classifying networks. The authors hope is the taxonomy presented will serve as a tool to allow the field to quicken the pace of learning both within and across classes. When we are able to compare apples to apples and avoid inadvertent comparison of apples and oranges, we all get smarter faster.

AbstractState‐level mediation associations (SMAs) in more than twenty states may play an important role in the further development of community mediation by addressing many of the prevailing needs in the field regarding networking, access to resources, and quality control. This chapter is a qualitative exploration into the function and range of activities of SMAs and factors facilitating or challenging their development.

AbstractIn light of the burgeoning literature in whole, goal-directed networks for managing wicked problems in public management, it is timely to examine the theoretical evolution that has both shaped and constrained our understanding of these networks. In this article, we argue that contemporary study of whole networks has been dominated by an internal theoretical lens aimed at understanding how internal characteristics influence network functioning and effectiveness. This perspective assumes networks operate in differentiated environments rather than emphasizing interdependence as part of a broader ecology—networks of networks. In this article, we draw from population ecology to introduce the concept of network domains and offer evidence drawn from a population of 60 health-oriented networks in three counties to illustrate domain level characteristics. Using an inductive mode of theorizing, we leverage insights from these domains to consider population dynamics and pose propositions for advancing a program of study into domain level characteristics that may shape and constrain whole networks and their members.

Public management scholars have long sought to understand design principles that can promote the adaptability and resilience of complex organizational systems operating in uncertain and turbulent environments. Perhaps nowhere is this need more acute than in developing systems for responding to complex disasters. One concept that has received significant attention in discussion of resilient systems design is the notion of redundancy; however, existing literatures offer contradictory theories as to whether redundant designs enhance or undermine system resilience. Using case study data from three large‐scale wildfire events, this article extends the theoretical discussion of redundancy by developing a typology of redundancy strategies and investigating their application and associated consequences in incident response. Our findings reveal four principal ways redundancy can be integrated into system design: backup, cross‐functionality, duplication and cross‐checking. Further, each redundancy type is associated with its own capabilities for enhancing system resilience as well as its own set of risk factors that, if left unmanaged, could undermine system functioning. Findings demonstrate how understanding both the potential value and risk portfolio associated with each type of redundancy clarifies the management challenge for responders when employing these strategies.

We leverage economic theory, network theory, and social network analytical techniques to bring greater conceptual and methodological rigor to understand how information is exchanged during disasters. We ask, "How can information relationships be evaluated more systematically during a disaster response?" "Infocentric analysis"—a term and approach we develop here—can (a) define an information market and information needs, (b) identify suppliers of information and mechanisms for information exchange, (c) map the information exchange network, and (d) diagnose information exchange failures. These steps are essential for describing how information flows, diagnosing complications, and positing solutions to rectify information problems during a disaster.

AbstractGovernance systems reconcile diverse interests to enable collective decision-making and action. Questions related to representation in the governance of networks are addressed in the literature; underexplored is the empirical variation in governance arrangements and pathways of representation. Complex, multi-jurisdictional disasters provide a robust theoretical and empirical context in which to investigate network governance pathways due to the tensions between democratic principles of representation and the need for timely, expert-informed response actions. In this article, we address three questions related to network governance, representation, and complex disasters: what governance structures allow for a representation of diverse interests? What governance structures provide a perception of voice to key affected parties? And where do we see variation in the kinds of structures that give voice to these entities? Using an inductive, grounded theory approach along with mixed methods that include case studies, interviews, and archival data in the form ICS 209 incident reports, we provide evidence from 10 of the most jurisdictionally complex wildfires that took place in 2017. In doing so, we introduce the distinction between macro and micro structures of network governance for understanding more precisely the pathways by which representation occurs and how representation functions in disaster networks. There is no singular normative goal when we think about network governance and representation in disasters; rather there are competing contingencies that emerge out of complex contexts. We propose four key propositions to guide further work in this arena.

Public management scholars have suggested that employee motivation can be accentuated by organizational cultures and contexts. One of the most researched topics in this regard is the concept of public service motivation (PSM). Research shows that PSM works to direct applicants toward public service careers and, once hired, can be linked to motivated activity within public-sector organizations. Similarly, like PSM, a sense of community (SOC) and a sense of community responsibility (SOC-R) have also been posited to act as powerful predictors of employee well-being and engagement. The present study demonstrates that SOC-R is a more powerful predictor of employee engagement compared with PSM and SOC. Concurrently, SOC more strongly predicts employee well-being compared with PSM and SOC-R. The findings bring additional light and clarification to the predictive power of PSM on employee perceptions and behavior, and they demonstrate that community experiences have utility in public service settings.

There is significant debate about the appropriate governance structure in a disaster response. Complex disasters exhibit both networked and hierarchical characteristics. One challenge in the field of disaster management is how to structure a response that reconciles the need for centralized coordination among varied responders while retaining flexibility to mutually adjust operations to quickly changing conditions. A key question with both practical and theoretical relevance is, "are there patterns of relationships that are more robust, efficient and effective?" Missing from the current literature is empirical evidence and theory building concerning what actual network structures and characteristics might be associated with effective incident response to complex disasters. In this article, we collected network cognition data from 25 elite, Type 1 Incident Commanders to construct an ideal-type theoretical social network of an effective incident response network. We then analyzed this model to identify a set of propositions concerning the network structure and governance of effective incident response relative to four key network capabilities: (a) rapid adaptation in response to changing conditions, (b) management of distributed information, (c) bilateral coordination, and (d) emergent collective action. Our data suggest that the structure is neither highly integrated nor rigidly centralized. Rather, it is best characterized as a moderate core–periphery structure. Greater theoretical clarity concerning the capabilities associated with this structure is critical for advancing both research and practice in network governance of complex disasters.

Governance systems reconcile diverse interests to enable collective decision-making and action. Questions related to representation in the governance of networks are addressed in the literature; underexplored is the empirical variation in governance arrangements and pathways of representation. Complex, multi-jurisdictional disasters provide a robust theoretical and empirical context in which to investigate network governance pathways due to the tensions between democratic principles of representation and the need for timely, expert-informed response actions. In this article, we address three questions related to network governance, representation, and complex disasters: what governance structures allow for a representation of diverse interests? What governance structures provide a perception of voice to key affected parties? And where do we see variation in the kinds of structures that give voice to these entities? Using an inductive, grounded theory approach along with mixed methods that include case studies, interviews, and archival data in the form ICS 209 incident reports, we provide evidence from 10 of the most jurisdictionally complex wildfires that took place in 2017. In doing so, we introduce the distinction between macro and micro structures of network governance for understanding more precisely the pathways by which representation occurs and how representation functions in disaster networks. There is no singular normative goal when we think about network governance and representation in disasters; rather there are competing contingencies that emerge out of complex contexts. We propose four key propositions to guide further work in this arena. ; Published version