Network Governance as a Systems Construct

According to the Webster’s Unabridged Dictionary, to “govern” means “to rule by right of authority; to exercise a directing or restraining influence over; to hold in check; control” (Webster’s, 1989, p. 612). An etymology of the term reveals that it stems from the Latin guernator and Greek kybernan, meaning “to steer.” The term cybernetics shares the same root as govern. The development of systems theory in the early twentieth century was undertaken with an aim toward discovering complementarity between human, mechanical, and electrical systems (Hammond, 2003). For engineers and mechanics, a “governor “ is a “device used to maintain uniform speed, regardless of load.” In machines, governors play the role of comparators, regulating the flow of fuel or energy into the system.

As we consider the relationship between systems dynamics and governance, we find these parallels, as well as the overlapping meanings found in the roots of the words govern and governors to possess a certain eloquence. The definition of governance that we are prepared to use throughout the rest of this book is therefore very much rooted in a systems framework. In this sense, governance needs to be understood in terms of the range of systems dynamics discussed in this chapter. To understand how the governance of any social structure operates, we need to clarify borders and boundaries, as well as the characteristics of these borders and boundaries, e.g., are they open or closed, permeable or impermeable? We may also ask: What are the inputs, processes, outputs, and outcomes over which, and through which, governance occurs? Lastly, we are reminded of the fact that the study of governance at the systems level can be, essentially, understood in terms of the ranges of feedback loops, cycles, and mechanisms found within the system.

A. W. Rhodes (1997) was one of the first scholars to deeply consider the relationship between governance and interorganizational networks, arguing that governance occurs as a “self-organizing phenomenon” shaped by the following characteristics:

  • 1. Interdependence between organizations. Governance is broader than government, covering nonstate actors.
  • 2. Continuing interactions between network members, caused by the need to exchange resources and negotiate shared purposes.
  • 3. Game-like interactions, rooted in trust and regulated by the rules of the game negotiated and agreed upon by network participants.

We find elements of both classical network analysis and systems dynamics in this definition of governance. Governance is framed by the game-like interactions that give shape to the ongoing interactions of interdependent actors. These interactions are also shaped by the boundaries and borders constructed through them, inputs of resources, network-wide processes, outputs and outcomes ascribed to them, and various feedback mechanisms and loops that provide the network to self-correct and be corrected. We may construe that these three features of governance systems serve as a few of the simple rules that support the governance of complex governance networks.

Over the course of the remaining chapters, we explore governance through three frames of reference that have been advanced within the public administration and policy studies literature. We view governance in terms of the range of managerial and administrative roles and responsibilities found within the public administration field (Chapter 8). We explore how governance processes are shaped by certain sector characteristics and conclude that these characteristics need to be understood within the context of a robust accountability framework that is capable of accounting for the range of actors found within a governance network (Chapter 9). Lastly, we view governance in terms of expectations built up around performance by honing in on the potential role that performance data and performance management systems play in ensuring the governability of a governance network (Chapter 10).

Governance Networks as Complex Systems Dynamics ? 183

Systems, structures, and functions of whole networks

Figure 7.5 Systems, structures, and functions of whole networks.

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