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Torfing et al. (2012) defines interactive governance as a complex process where multiple actors with different, and sometimes conflicting, interests have a common objective; they interact to formulate, promote and accomplish said objective. Governance networks can include private and public actors and different layers of government (local, regional, national, supranational) (Klijn 2016). Policy-making is moving from top-down to a system where each actor depends on the others, and not one of them has enough power to manage alone (Bovaird and Löffler 2016).
Because each actor is autonomous, has unique resources and a different perception of how to solve the problem at hand, networks present a extraordinary level of interdependency (Klijn 2016). As a result, networks are at risk of uncertainty. Not being able to control how actors are going to act and if they’re going to act in a way that will only benefit them. In this essay, we’ll focus on some of the concepts that cause this uncertainty, specifically, the power asymmetry and the level of trust between organizations. Additionally, the uncertainty and complexity of interactive governance networks can’t be managed the traditional way, as their relationship is not vertical but horizontal. Consequently, we’ll also examine some problems that may arise in the management of the process.
The objective of this essay is to consider the opportunities and challenges of implementing public policy in interactive governance networks. This essay is organized as follows: At the outset, we’ll discuss the challenges of power asymmetry, concentrating in agency and government, with examples of abortion legislation and gold mining and its environmental repercussions in the Dominican Republic. Subsequently, we’ll analyse the importance of trust as a promoter of efficiency, as well as challenges presented in the measurement of this relation, additionally, we’ll consider the role of the boundary spanner. Then, we’ll examine the difficulties to assess what makes networks accountable and what is considered efficient in interactive governance. Finally, the last section will conclude the essay with some recommendations.
I. Power asymmetry
Complex societal problems result in a necessity to include multiple public and private organizations in the policy process. Each institution taking part of the process has different reasons and different objectives to get involved; this together with the power asymmetry in the network can turn decision-making more complicated. This asymmetry exists because of differences in availability of resources as well as dependencies (Klijn 2016), where the resources an organization can have available might be knowledge, authority, incentives to affect interests of others and reputation (Dowding 1995). In order to be a part of the network, the actor must possess at least one of these resources. The institution that holds more power can have more influence and tilt the balance in their favour. The less powerful organizations have to give in provided that they don’t have as much negotiating power and their relation is based in interdependency. Frequently, one actor can keep problems off the agenda and withhold support or resources in order to seek autonomy and control (McGuire and Agranoff 2011). In this section we’ll talk about agencies and the government, in order to explore the opportunities and challenges of the existing power asymmetry in networks, using examples to illustrate the problem.
The role of agency in a network is to give voice to the people. They can allow themselves to think differently as they can separate themselves from political influence. Additionally, they have the opportunity to be more honest and autonomous since they don’t have to worry about a hierarchical order or being punished for being against their ideas. We could argue that giving more power to agencies might prove to be rewarding, giving power to the people that would end up receiving or being affected by the policies being discussed. Then again, the autonomy that agencies posses can backfire as it can be abused. One challenge presented in networks with power asymmetries is that certain actors might be denied access. Even though agency organizations are free from political interference, they are not free from being influenced by certain groups. This was the case of abortion legislation in the Dominican Republic. In 2016, the President proposed a reform to decriminalize abortion in cases of rape, malformation or if the life of the mother was in danger. Feminist groups in the country, international organizations and the Ministry of Health supported this proposal. However, the proposal was rejected after a strong opposition from the church. The church has always been very powerful in this country, with a 40% of the population been practising Catholics and 29% non-practising.
Klijn (2016) explains how parties care more about winning than about finding the truth. He also argues that they will find experts to support their allegations in an attempt to discredit other findings. This can result in other parties bringing their own findings and subsequently creating confusion as to what is true. Another example of power abuse is the decision taken regarding a Canadian-owned gold-mining company called Pueblo Viejo in the Dominican Republic, which began production in 2012. Since that year, there have been countless protests against the company for polluting the river, harming agriculture and noise contamination. According to law 64-00 of Environment and Natural Resources, the communities affected by the mining should have received 5% of the profits from Barrick Gold, which has not been the case. The communities directly affected were not consulted in the decision process and their complaints about health complications have been put aside. The state and the mining corporation assure that the pollution was caused by the previous mine and that it has been re-mediated by Barrick (Pueblo Viejo 2013). This has been regarded as a move by the state to fulfil their interests, considering that the mining plays a crucial role in income collection.
The literature available has yet to come with a solution to the problem described above (Agranoff and McGuire 2001; Torfing et al. 2012). What do we do make sure that no actor will use their dominant position without any consideration of the effects their decision can have in other actors? Klijn (2016) proposes the formulation of ‘don’ts’ by the government in order to make sure the process is smooth. This disregards the fact that the government is the most powerful actor in this game, which makes questionable the proposal to make it responsible for managing the ‘don’ts’ in network governance. Regardless of the inclusion of more participants in the policy process, the government still has the power to steer the network and retains control (Bache 2000).
Explanations in power relations in networks could be advanced by the incorporation of bargaining models and game theory (Dowding 1995; Agranoff and McGuire 2004). But the authors recognize that there isn’t enough data available to deeply understand how this could be solved. Then again, this would be helpful to understand why this unbalance exists but not how to manage it. There is a lack of empirical research on the role of power in governance networks and how power disparity can affect network outcomes, developing trust and future collaboration (Isett et al. 2011). Similarly, we couldn’t find any research testing the impact of management in networks with power asymmetry. We consider the topic could benefit from this quantitative or qualitative research, as well as evidence of which network management strategy is more effective in resolving conflicts. This is also a problem with trust, as we’ll explore in the next section.
Developing and measurement of trust
First, let’s define what we mean by trust. Trust implies assuming a vulnerable position, expecting that other actors won’t incur in opportunistic behaviour (Edelenbos and Klijn 2007; Klijn et al. 2010). In the absence of contractual obligations and vertical accountability, a high level of trust is considered essential to sustain the relations between the network actors, facilitate knowledge sharing and to ensure smooth interaction in the future (Hartley and Benington 2006; Mandell and Keast 2008; Klijn 2016). Because networks are born from complex or wicked problems, trust can help compensate for the uncertainty and unpredictability of the issue at hand. It can create stability and therefore motivate actors to invest their knowledge and funds in favour of the cooperation (Klijn et al. 2010). Accordingly, we expect trust to have a favourable impact on network performance. Where more trust between the participants translates into outcomes with higher quality. This has been tested to be true for the case of environmental network projects (Klijn et al. 2010; Edelenbos et al. 2011) and urban projects (Meerkerk and Edelenbos 2014) in the Netherlands.
These studies have the limitation that in the surveys, they present relations as one-on-one. Asking the respondents to rate their trust in all the other participants, not differentiating by the actor. This can bias the result, as we can’t expect one actor to hold the same level of trust for each actor. This corresponds to the belief that trust depends on reputation, knowledge and competence and these vary depending on the actor. Song (2017) tried to fill this gap analysing inter-firm relations and their trust distribution for four case studies. Regardless, for none of the studies available, we can affirm the direction of the causality for the variables; we can only affirm that they are correlated. In other words, we don’t know if more desirable results generated an increase in trust or if the increase in trust caused quality outcomes. Additionally, we can’t assume that the results would be the same for non-environmental projects in interactive governance or for other countries, as samples were not chosen randomly and are not generalizable; the authors also recognize this. Surprisingly, trust remains an under-developed concept in governance literature (Edelenbos and Klijn 2007; Isett et al. 2011; Song et al. 2017). There is only one study available that compares this relation in different countries (Klijn et al. 2015) that could be considered generalizable. For Spain, the Netherlands and Taiwan, trust explained positive network outcomes for different sectors. Moreover, another limitation for the measurement of trust is that it can only be captured through interviews or surveys of participants’ perception. The nature of the variable doesn’t allow for a more objective measurement methodology. Consequently, we’re at risk of counting with actors that would hesitate or be unwilling to share their candid opinion (Klijn 2016). If we can’t measure trust correctly, how can we identify if it is the reason why the network is working correctly?
The problem with networks is that even though trust is believed to be fundamental, it isn’t easy to develop. According to the literature (Sabel 1993; Edelenbos and Klijn 2007), trust can only be developed spontaneously or by constant interaction between the actors, and this period will have to be free from incidents that will make actors doubt about the intentions of the other actors. But currently, not many quantitative studies exist that test that an increase in trust in governance networks is the result of an increase of time spent interacting. Similarly, there are currently no studies testing out what has a positive impact on trust. As an illustration, despite the fact that for Spain, Taiwan and the Netherlands there is a positive relation between trust and outcomes, there are differences between the strength of the coefficient for each country. With trust having a weaker impact on the outcome for Taiwan than for the rest. What can explain that some networks are more dependent on trust than others? This is an important question that could give insight on how to manage and devise rules for trust enhancing.
A facilitator or manager will be necessary to mediate and establish the rules that limit opportunistic behaviour, in order to assure that the trust gained isn’t lost in situations of conflict resolution (Edelenbos and Klijn 2007). Klijn (2016, p.299) argues that trust can be built through ‘institutional regulations such as the introduction of a certification system, conflict regulating institutions, and regulators’. Management strategies and intensity seem to have a positive relation with the level of trust (Klijn et al. 2010; Edelenbos et al. 2011; Klijn et al. 2015). The literature mentioned above does not specify what would be the rules that would incentivize the increase of trust or if participants that breach the group trust should be punished or taken out from the network. What is the management strategy for when a powerful participant that has indispensable resources is incurring in opportunistic behaviour? How do you make sure that participants won’t lose interest in working in the network hen the developing of trust is being delayed?
Research has also been conducted on the role of boundary spanners for developing trust and how that affects network performance. Boundary spanners collect information and transmit it internally and externally, they’re useful in fragmented networks as a consequence of specialization (Meerkerk and Edelenbos 2014). They manage to understand both sides of the boundary, given the need to translate information from one side to the other. They need to have empathy, interpersonal skills, be good listeners, persuasive and competent translators (Williams 2002). Meerkerk and Edelenbos (2014) verify the hypothesis that as a result of their role as relationship builders, they can influence trust and that this, in turn, results in better performance. This hypothesis was tested for boundary spanners in urban projects in the four biggest cities in the Netherlands. They conclude that the presence of boundary spanners is positively correlated with trust and network performance. More work on the importance of boundary spanners is necessary. It is important to highlight that, equally to the studies presented above, this work has some limitations that need to be analyzed more deeply.
Accountability and network effectiveness
Klijn (2016, p.223) defines accountability as ‘the extent to which actors (accounters: those rendering accounts) are held accountable for their behaviour and performance by other actors (accountees: those to whom account is rendered)’. One critique to networks is that while we decentralize and get farther away from top-down systems, we also move away from a clear accountability system with results that differ from those of elected officials (Agranoff and McGuire 2001). Who is in charge of overseeing that everyone is completing their job and that goals are being met? Agranoff and McGuire (2011) raise the worry that when everyone is in charge and everyone is responsible, nobody is accountable. For example, in the case of Barrick Gold, is the government or the gold mining company responsible for the environmental damage? What about the other actors that were involved in the contract negotiation? Can the Customs Office or the Internal Revenue Office be held accountable for the environmental damage resulting from Barrick’s operations? Who has to answer to the citizens from the affected zone?
Furthermore, democracy can be a form of accountability. In a traditional democracy, people feel represented because they voted for the candidate they expected to respond better to their will, but the lack of a hierarchical structure in networks has called into question their contribution or lack thereof to democracy. In an effort to evaluate the democratic legitimacy of networks, Klijn (2016) highlights three sources of legitimacy: 1) simple and clear accountability, 2) giving voice to different groups and 3) a specific set of rules for conduct and an organized deliberation process. For the first point, one criterion of communication between actors of the network and their parents organizations is recommended as a measure of performance (Voets et al. 2008). But because each parent organization will have different rules and measurements of how to assess performance, we disagree with this statement; it would be preferable for explicit rules from the network facilitator that establish what each actor is accountable for and how to measure the resulting outcome.
Interactive networks certainly help with the second point as they include more participants on the output side of the process (Torfing et al. 2012). But this access to a ‘voice’ might not come equally for everyone. As we mentioned before, the asymmetry of power between the actors will benefit some citizens more than others. There might also exist a trade-off between democracy and effectiveness, as more actors are included to make the group more inclusive, it would be more troublesome to agree on formulation and implementation of policies. Moreover, it is more burdensome to differentiate who is in charge of what and, consequently, who is accountable for it. As for the last one, Torfing et al. (2012) argue that elected politicians can’t be undermined and their monitoring of the network is necessary in order for decisions to be in line with popular will. There isn’t a clear conclusion of the effect of interactive governance in democracy. It is necessary that networks managers increase individuals’ sense of impact to restrict them from distancing themselves from the responsibility (Toole 1997).
The media can be a helpful instrument in network accountability as it provides transparency and can make information available to a more substantial audience, this is also known as public accountability (Klijn 2016). An increase of knowledge about what’s going on with the process can promote trust in the government (Torfing et al. 2012). A downside of more media involvement is that media can also be dramatic and biased and this can result in blame games and reluctance to share their stories. It can also result in politicians worrying more about creating an image than in the policy process (Klijn 2016). Media bias can result in only reporting ‘bad’ or controversial news and focusing more on elected actors in order to capture the public attention (Hasler 2016). Hasler finds that media occupies a critical role in democratic accountability. They report accurately about policy-making in the European metropolitan areas studied, but they also can’t reject the hypothesis of bias towards elected actors, presenting them ‘over-responsibilised’ and ‘over-blamed’. In sensitive stages of the policy process, media reporting can be more detrimental to governance, which is why Torfing et al. (2012) argues that there can be transparency in outcomes and seclusion in the process. Additionally, the media can portray an important role for researchers. It can provide an alternative to traditional survey methods with all the information accessible and technology to organize and analyse the data (Yi and Scholz 2016).
Additionally, there are disagreements about if the effectiveness of the network should be measured by a successful interaction or by the outcomes. It is argued that because actors can have different goals and these can change over time it would be problematic to use the completion of goals for evaluation (Koppenjan 2004). We argue that a process that was conducted without conflicts in its formation and formulation process but failed to implement their policy shouldn’t be considered successful. It is important to point out that there is a positive relation between managerial strategies and network performance (Klijn et al. 2010; Klijn et al. 2015). But there is no information available concerning what strategies have the most considerable impact on outcomes or what can explain that effect.
Networks are fundamental in a complex world with problems that depend on more than one actor’s knowledge and resources. Consequently, it is imperative to have research to understand these problems better and that is able to foresee conflicts that can result from the different perspectives and resources of the participants. This could be helpful to perceive the differences in trust between the actors and what has an impact on it, as well as management strategies and the difference in power resources.
It is surprising that there isn’t enough empirical research that supports the vast theory existent in the topic. For the concepts analysed in this essay, there was only cross-sectional research, there weren’t studies with a collection of time series data or data panel. This prevents the examination of the evolution of power relations and the evolution of the developing of inter-organizational trust. We could evaluate the effect of different management strategies in each these variables and the impact of each one in the outcome of the network. More research needs to be conducted on these specific topics that theory points as very important for a smooth and prolonged cooperation between organizations. The collection of this type of data could also help explain the direction of causality that the existing research hasn’t been able to answer. Does trust improve network outcomes or is the quality of the outcomes that increases trust in each other? It is also indispensable to expand the empirical research to more sectors, as most of the existent research has focused in environmental and urban projects, we don’t have evidence that this could translate to other types of networks. Additionally, cross-sectional data from different countries and explanations for the differences will be an important expansion of the literature.
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