Module 5: Group Discussion

42. Network governance Robyn Keast

INTRODUCTION

Over the past few decades, in response to an array of ongoing societal challenges and changes, network governance has become a cornerstone of the institutional architecture across many fields of endeavor, jurisdictions and sectors. As this Handbook attests, conceptualizations and theories of governance encompass a broad framework that continues to grow. This chapter examines network governance as one of the foundational governance modes. It defines network governance, distills its defining characteristics and discusses theoretical concepts and related theories. It also elucidates some of the types, forms and functions of network govern­ ance. Finally, the chapter highlights ongoing and emergent challenges and their implications. It concludes by forecasting a continuing but increasingly complex and hybrid future in which network governance and theorizing will retain a central position.

NETWORK GOVERNANCE: BASIC ELEMENTS

As Castells (2000) contends, we live in a networked society. The turn to networks is evident in the numerous derivations that have emerged, including for example “networked organizations” (Miles and Snow 1986), “networked forms of organization” (Larson 1992), “inter-organizational networks” (Alter and Hage 1993), “global or virtual networks” (Holton 2008), “policy networks” (Rhodes 1990) and “service delivery networks” (Provan and Milward 1995).

Despite their differences (level, location and foci), these networked forms have in common a set of ideological assumptions and organizing principles based on ongoing social exchanges as the glue that binds individuals to collective action (Powell 1990). Network governance thus represents a social or communal form of social organization in which interpersonal relational aspects such as trust, reciprocity and the pursuit of mutual benefit interact to forge jointly agreed and achieved outcomes. As Powell (1990: 300) explains, “certain forms of exchange are more social, that is, more dependent on relationships, mutual interests and reputation - as well as less guided by a formal structure of authority.”

These characteristics and their benefits compete and contrast with, and sometimes comple­ ment, the other core governance modes of hierarchy and market,_characterized by command, authority and price competition, respectively (Bradach and Eccles 1989; Powell 1990). Thompson et al. (1991: 15) expand: “If it is price coordination that is the central coordinating mechanism of the market and administrative orders that of hierarchy, then it is trust and coop­ eration that centrally articulates networks.”

A sharper analytical differentiation of network governance is provided by comparing it against the state and market governance modes. See Table 42.1, which extends Powell’s 1990 classification.

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Table 42.1 Governance modes compared

Governance mode State Market Network

Service focus Public good Private good Social good

Locale Hierarchy, bureaucracy Firm Community

Decision-making Vertical, top down Horizontal (internal) Horizontal (broader)

Relationship focus Dependent Independent Interdependent_____________

Integration mechanisms Legal authority, formal rules, regulations, policies and procedures

Arm’s length contractual transactions, price structures, supply and demand

Social exchange, relationships, common vision or purpose, mutuality, reciprocity

Negotiation style Rule-based, procedural Bargaining, competitive, self-interested and short-term focus

Win-win,, interest-based, longer-term focus

Note: This table extends Powell’s (1990) governance mode comparison.

Despite the differences, there is rarely a clear-cut choice of state, market or network modes. Instead, social organization often comprises a mix of these modes (Borys and Jemison 1989; Bradach and Eccles 1989), leading to hybrid configurations and reconfigurations, the network implications of which are discussed later in this chapter.

Fundamentally, network governance represents horizontal over vertical approaches to decision-making and is characterized by systems of affect, communication, knowledge exchange and dialogue. It is argued that these characteristics enable greater adaptability and lower transaction costs, making network governance particularly viable in conditions of uncertainty, complexity and crisis (Kickert et al. 1997), as well as when there are unique issues which “require input from various experts, and must be solved creatively” (Baker 1992). While providing some insights into network governance, such a general description does not fully explain how these cooperative arrangements are formed and organized to deliver their outcomes.

NETWORK GOVERNANCE UNPACKED |

Networks are based on the relational. As Church et al. (2002) and others (Bradach and Eccles 1 1989; Powell 1990) stress, it is relationships that give networks their strength and their edge | over other governance forms. In networked arrangements members do not exist as independent | operators, but rather exist in relation to other entities (Bartels and Turnbull 2020). Through ongoing social and resource exchanges a relatively stable pattern of relationship is formed between previously separate bodies (Mitchell 1969). Interpersonal relationships based on trust, reciprocity and mutuality evolve and are strengthened through persistent interactions and become a powerful social lubricant to help overcome conflicts and difficulties (Powell 1990), helping to push past difficulties to achieve mutually derived results (Keast 2011). The network approach, therefore, is premised on notions of mutual goals and the realization of the need for interdependence between members to achieve these goals (Mandell 1994; Kickert et al. 1997, Sorensen and Torfing 2007); in other words, actors achieve their objectives with assistance from and in coordination with others.

To facilitate repeated and sustained exchanges, rules or “agreed ways of working” are established, coupled with processes to guide actors’ behavior and ensure an ongoing flow of

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resources as well as the level of cohesion necessary to work together (Klijn and Koppenjan 2000). Network management strategies (Agranoff and McGuire 2003) are also applied to leverage relationships for mutual outcomes. A shared orientation is achieved in which members come to know and appreciate each other and are better able and more willing to engage in “thicker” flows of information, share previously withheld resources and develop joint goals. Importantly, these network relationships possess the internal flexibility needed to handle and overcome difficult transactions, instead of resorting to the costs of monitoring work or legal contracts as for market and hierarchy forms (Powell 1990); that is, the coop­ erative give-and-take afforded by networks helps to overcome the incomplete and imperfect documents such as regulations and contracts (Macneil 1985). While trust, obligation and reputation become powerfill conduits for compliance they are not always sufficient, and other re-enforcing norms, such as a culture for cooperative working and/or rituals, may be needed to enhance accountability and achieve outcomes (Koppenjan and Klijn 2004).

TYPES, FORMS AND FUNCTIONS

The array of purposes for network governance—including, for example, policy formation and implication, service delivery and innovation development—has resulted in a diversity of types and forms with different operating functions, drawing upon different network ele­ ments. Network governance varies in whether it has goal-directed or serendipitous intentions (Kilduff and Tsai 2003), employs formal or informal arrangements (Agranoff 2006; Provan and Kenis 2008), or is tightly or loosely structured, with differentiated relationship strengths and dependency levels (Marcussen and Torfing 2003; Keast et al. 2007). Different types of governance arrangements can also be employed as integration mechanisms, including participant-governed, lead organization or network administrative organization (Provan and Kenis 2008; Vandeventer and Mandell 2011). Several typologies have been introduced, particularly in relation to policy (Marsh and Rhodes 1992) and service delivery networks (Agranoff 2006; Keast et al. 2007; Ferlie et al. 2010), categorizing the various network gov­ ernance elements and aligning them with purpose and effectiveness (Kilduff and Tsai 2003; Provan and Kenis 2008). Network governance is not static, and as has been suggested it can evolve from one form to another owing to the effects of life-cycle and goal changes and chang­ ing contexts (Lowndes and Skelcher 1998; Kilduff and Tsai 2003), as well as the actions of individual actors (Provan and Kenis 2008; Keast and Mandell 2013).

As the above elucidates, network governance is a complex undertaking, where optimal performance rests not just on the presence of network elements, but rather on the dynamic interactions that occur between them and network actors (Stout and Love 2019; Kapucu and Hu 2020).

DEFINITIONS AND THEORIES

The central characteristics or elements identified above led to a broad array of different con­ ceptualizations and definitions of network governance (see e.g. Miles and Snow 1986; Larson 1992; Alter and Hage 1993). However, Jones et al. (1997), in their review of network govern­ ance definitions, find two points of coalescence: the patterns of interaction in exchange and

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relationships, and flows of resources between independent units. Building from this finding, Jones et al. (1997: 914) developed the following definition: “Network governance involves a select, persistent, and structured set of autonomous firms engaged in creating products or ser- vices based on implicit and open-ended contracts to adapt to environmental contingencies and to coordinate and safeguard exchanges. These exchanges are socially—not legally—^binding.” j

Such a definition gives primacy to economic performance over relationships (Borgatti and Foster 2003), making it more attuned to a business transaction. Nonetheless, the authors considered that the dual emphasis on social exchange and efficiency, as outlined in the above definition, also applied to the non-profit sector. Others, however, argue that while the instru- j mental factors of exchange and efficiencies are important in shaping the decision to move ’ to a networked mode, they are often accompanied by altruistic motivations, particularly the notion of “doing the right thing” (Woolcock and Boorman 2003; Keast 2011). In this domain the relationship focus shifts from predominantly an individual mechanism for exchange, to more of a shared property of the network members to facilitate collective outcomes, highlight- j ing a subtle point of differentiation in conceptualization and application of network govern- i ance for the non-profit arena.

The public sector also capitalized on the advantages of network governance. The first efforts arose with the move away from the notion of narrow sets of “rational actors” shaping policy-making to the realization of the existence of a wider array of actors contributing to ; public decision-making (Heclo and Wildavsky 1974; Rhodes 1990) and implementation pro- ; cesses (Hjem and Porter 1981). Later, in response to heightened social, economic and political challenges, governments also turned to network principles to bring together diverse actors to i enhance governing capacity and public outcomes (Goldsmith and Eggers 2004). Within this | application there is a realization that policy development and service delivery are no longer the j sole responsibility of government, but occur through the interaction of different actors from different levels of operation, as well as across sectors (Kooiman 1993; Kickert et al. 1997; < Osborne 2006).

Thus, in the public context, network governance represents a shift from government to gov- ernance via decentralized social organization where society is no longer exclusively controlled • by central units but is distributed among a broader set of participants (Kenis and Schneider 1991: 26). Also known as governance networks, these entities generally comprise multi-level and often multi-sectoral parties involved in public policy deliberations, and are alternative ’ ways for connecting public policy-making to citizens and relevant stakeholders (Kickert et al. 1997; Provan and Kenis 2008; Sorensen and Torfing 2007; Stout and Love 2019).

RELATED GOVERNANCE CONCEPTS

Building on the relational foundations offered by the network governance mode, several other allied governance forms (and associated theories) have evolved, including New Public Governance (NPG) and relational and collaborative governance (discussed in more detail throughout this Handbook).

NPG (Osborne 2006; Koppenjan 2012) extends governance networks and acknowledges the “plural and pluralist complexities” of governing (Osborne 2006), particularly the multiple sets of people and processes shaping policy development and service provision. In this new governance reality, hybrid mixes are the norm, with networks combined with other modes in

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assorted ways to leverage the best aspects of individual governance modes, while minimizing less functional ones. As Koppenjan (2012: 32) noted, “Network governance does not function independently of hierarchical and N PM-like arrangements. Rather, it acts in concert with these arrangements, as a necessary and decisive component of a more encompassing, hybrid assembly.”

As well as better capturing the plurality of governance actors, NPG acknowledges the growing hybridity of governance modes, their tools and their processes, as well as the ongoing processes of deliberation and negotiation applied in the governance reconfigurations (Sorensen and Torfing 2007). ‘Smart hybridity’ (see Koopenjan et al. 2019) will combine existing governance instruments with more substantial data and information technology to develop the nuanced governance mixes needed for contexts predicted to be increasingly complex and dynamic.

Relational governance (Zaheer and Venkatraman 2007), relational contracting (Macneil 1985) and relational capital (McLaughlin et al. 2009) also have some similarity with the network governance mode. Although in different degrees, these forms rely on relationships as the mechanism to coordinate social and economic activities. Contracting based on building and sustaining longer-term exchange relationships over competition and adversarial contract­ ing not only reduces costs but also allows for risk and rewards to be shared equally (Walker and Hampson 2003). Within the longer-term exchanges, relational capital is built up, which can be leveraged for subsequent interactions and projects.

Extending this focus Gittell (2011) developed a theory of relational coordination, referring to “a mutually reinforcing process of communication and relating for the purpose of task integration.” Specifically, it is argued that highly interdependent work is most effectively coordinated through relationships of shared goals and mutual respect, and enacted through structured tools such as committees and taskforces.

Collaborative governance (discussed in greater detail in Chapter 43) is a related concept, which pushes beyond task integration to deliver breakthrough change. It draws upon stronger relational tools such as consensus, deliberation and interest-based negotiation (see e.g. Booher 2004; Emerson et al. 2011). Building on these distinctions, Ansell and Gash (2007: 544) define collaborative governance as: “A governing arrangement where one or more public agencies directly engage non-state stakeholders in a collective decision-making process that is formal, consensus-oriented, and deliberative and that aims to make or implement public policy or manage public programs or assets.”

Collaborative governance therefore presents as a higher-order form of network governance; one that moves beyond task integration to the synthesis of people and their resources for the broader good.

Such an array of definitions and conceptualizations can be both positive and negative: positive in that they can lead to new or deeper understandings of how network governance is operationalized in different contexts and disciplines; and negative, as the jumble of definitions can impede the isolation and distillation of key analytical features, making it difficult for anal­ ysis and theory development. Nonetheless, there has been considerable theorizing undertaken on network governance and networks generally.

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UNDERPINNING THEORIES

Several theories have been used to explain why network governance has emerged and thrives, as well as how and under what conditions it functions to deliver efficiency and innovative out­ comes (for reviews see Berry et al. 2004; Sorensen and Torfing 2007; Lewis 2011; Klijn and

* Koppenjan 2012; Kapucu and Hu 2020). In general these reviews cluster network governance research and theorizing into three broad traditions.

The sociology-anthropology standpoint adopts a structuralist approach to explaining network governance, positing that the nature and pattern of interactions and the position of actors enable or constrain outcomes (Borgatti and Foster 2003). Re-enforcing the findings of an earlier study (Borgatti and Foster 2003), Borgatti and Halgin (2011) note that network analysis theory continues to focus on issues of flow (exchanges) and bonding (cohesion), and point to the latter as an area requiring expanded theoretical and research attention.

The inter-organizational relations approach points to the importance of the external environment in shaping organizational behavior and highlights the exchanges that occur as organizations seek to overcome uncertainty in resource flows (see e.g. Benson 1975). In this approach attention is directed to the nature of the flows (exchanges) and the relationships between entities, especially power and dependency, as well as the types of strategies adopted.

The political science-public management view holds that the policy process is more effec­ tive when the key actors are involved in policy development and the focus is on policy change and implementation (Rhodes 1990). Two key research questions are addressed: how the growing plurality of policy actors achieve the policies they desire, focusing on the behaviors and interactions; and how roles and network structures themselves influence policy outcomes (Berry et al. 2004). Because of the public good concern, public management theorists adopt a practice orientation and direct their attention toward questions of how network structures and management affect performance (Agranoff and McGuire 2003; Agranoff 2006; Bryson et al. 2017).

Thus, despite early criticisms (Salancik 1995; Borzel 1998), network theorizing has pro­ gressed through individual discipline development as well as from cross-fertilization and synthesis across disciplines and fields (Oliver and Ebers 1998). As Agranoff (2014: 205) concludes, over time there has emerged “a distinctive program of public sector research and theorizing, with a core set of ideas or principles that are not directly borrowed or tacked on from inter-organisational relations or other foci.”

EMPIRICAL EVIDENCE

It has been argued that networks are merely metaphors that describe generalized connections between entities (Borzel 1998) or, as Kenis and Schneider (1991: 25) stated, are used to “capture the architecture of complexity.” Shaping these criticisms were difficulties in iden­ tifying key analytical network concepts (Uzzi 1996)—and therefore measurements (Stout and Love 2019; Voets et al. 2020)—coupled with an overreliance on the single case study approach (Isett et al. 2011). Public sector research has responded to these criticisms. In their seminal study. Provan and Milward (1995) undertook a comparative case study of mental health networks and found that an integrated structure through network centralization and direct mechanisms of external control has a positive effect on network performance, and

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further that system stability and resource munificence have a moderating effect (Provan and Milward 1995: 23).

Building from this early work a significant body of empirical research has been amassed that confirms the operation of networks as different forms of governance, and the central role of relationships as the conduit to improved outcomes. For example, Agranoff (2006) used grounded theory to examine 14 networks, confirming the relational contribution necessary to secure collective outcomes. Purdy’s (2012) and Yoshikawa et al.’s (2007) multi-level studies analysed power relations and hybrid governance, respectively, leading to a richer understand­ ing of processes and outcomes. Klijn et al. (2010) assessed network management strategies and their relation to outcomes; while and Keast and Mandel’s (2013) interrogation of six cases highlighted the highly dynamic nature of network properties and the impact of individual agency in shaping action and outcomes.

As new research tools and methodologies emerged it became possible to undertake large-scale studies of networks in order to unravel the relationships between structures, pro­ cesses and outcomes (Turrini et al. 2010; Raab et. al. 2015).

Studies using social network analysis (SNA) and qualitative comparative analysis (QCA) have led to a more nuanced knowledge of the relationship between network governance features and performance. Using SNA, Considine et al. (2009) studied the link between network governance properties, leadership positions and public sector innovation outcomes, while service delivery scholars identify factors including density, centralization, governance and configurations as related to integrated outcomes (see Lemaire and Raab, 2020). QCA proponents such as Cristofoli and Markovic (2016) showed how different combinations of governance elements (for example, context, structure, mechanisms and management) could equally produce positive results, re-enforcing network governance hybridity.

While current studies have contributed valuable insights into network governance char­ acteristics, antecedents, functioning mechanisms and performance, ongoing empirical work remains a priority to address prevailing and emergent gaps (Agranoff 2014; Kapucu and Hu 2020; Voets et al. 2020). This will be aided by ongoing advances in computational capacity and technologies able to interrogate and analyse massive data sets to uncover and represent the hybrid and dynamic nature of network governance (Chamberlain and Farr-Wharton 2020).

CHALLENGES AND IMPLICATIONS

Despite the advantages, network governance is not suitable for all problems or conditions, nor is it without its own problems or points of fallibility. People join networks to pursue particular interests, which can lead to exclusivity over inclusivity, limiting the range of expertise and resources that can be accessed and directed toward joint outcomes. Networks can create their own norms, becoming a “law unto themselves’’ (Granovetter 1992: 45), with relationships, decision-making and actions not always made visible or in the public good (Milward and Raab 2006; Lauchs et al. 2011; Bakker et al. 2012), leading to transparency and accountability concerns.

Network relationships also require a considerable investment of time and effort to build and sustain the interactions that are central to their functioning (Church et al. 2002), and can therefore incur hidden relationship development transaction costs (Keast 2011) which are difficult to capture and measure. Furthermore, the social investment and embedded social

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relations can constrain members’ actions and increase coordination requirements, and there­ fore it can take considerable time to achieve mutually agreeable directions and thus outcomes (Koppenjan 2012). Complexity is a feature of network governance and is evident in the nature of the problems to be addressed, the diversity of actors and their expectations, and the mix of institutional arrangements and procedures in place (Vandeventer and Mandell 2011; Klijn and Koppenjan 2014; Koppenjan et al. 2019). Sorensen (2005) and Sorensen and Torfing (2007, 2009) also question the ability of governance networks to adequately perform as a democratic structure, and prescribe the use of meta-govemance as an overarching form of monitoring and self-management. Accordingly, network governance can generate problems, such as goal incongruence, loss of oversight and direction, asymmetric information flows, opportunistic behaviors, increased and dispersed coordination points, and hidden accountabilities (Teubner 2009). Thus, as Taylor and Hoggett (1994: 138) caution, network governance can be “ineffi­ cient, inequitable and even unethical.”

The problems and challenges identified above are neither inevitable nor unresolvable. Instead they highlight the need for strategic relationship-building and monitoring, as well as judicious network leadership and management, to navigate the complex sets of relation­ ships and agendas and to bypass or overcome blockages to ensure public value is delivered (Agranoff and McGuire 2003; Klijn and Koppenjan 2014).

CONCLUSION

Network governance remains a central approach to organizing and mobilizing for the develop­ ment of policy, the provision of services and the generation of innovative ideas.

There is little doubt that the future will continue to rely on networks and networked govern­ ance; less certain is the form they will take. The inherent complexity of network governance and the growing hybrid experimentation taking place in response to this complexity are an ongoing challenge to the practice and management of network governance at multiple levels. New insights, mechanisms and tools are assisting those charged with the responsibility for designing, governing and managing public sector networks. Researchers also must remain vig­ ilant and open in their pursuit of greater knowledge of network governance and, as Agranoff (2014: 205) concluded, “establish a facilitating context that enables this new thinking and practice to flourish and grow.”

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