Shared Positions on Divisive Beliefs Explain Interorganizational Collaboration: Evidence from Climate Change Policy Subsystems in 11 Countries

Abstract

Collaboration between public administration organizations and various stakeholders is often prescribed as a potential solution to the current complex problems of governance, such as climate change. According to the Advocacy Coalition Framework, shared beliefs are one of the most important drivers of collaboration. However, studies investigating the role of beliefs in collaboration show mixed results. Some argue that similarity of general normative and empirical policy beliefs elicits collaboration, while others focus on beliefs concerning policy instruments. Proposing a new divisive beliefs hypothesis, we suggest that agreeing on those beliefs over which there is substantial disagreement in the policy subsystem is what matters for collaboration. Testing our hypotheses using policy network analysis and data on climate policy subsystems in eleven countries (Australia, Brazil, the Czech Republic, Germany, Finland, Ireland, Japan, Korea, Portugal, Sweden, and Taiwan), we find belief similarity to be a stronger predictor of collaboration when the focus is divisive beliefs rather than normative and empirical policy beliefs or beliefs concerning policy instruments. This knowledge can be useful for managing collaborative governance networks because it helps to identify potential competing coalitions and to broker compromises between them.

Pathways to collaborative implementation: problems, decisions, persistence, progress, and consensus in collaborative implementation, studied through projects for integrated water resources management in Colombia

“…These findings are also consistent with those on the importance of policy preferences on specific problems, beyond the sharing of larger-order policy beliefs, to explaining decision-making and policy change from the perspective of the Advocacy Coalitions Framework (Leifeld, 2013). If there is growing evidence of the influence of similar beliefs in the formation of collaborations (Karimo et al, 2022), this research adds to it that similar decision criteria and judgments on knowledge validity influencing policy preferences may be relevant to understanding collaborative performance.…”

“…What these tools cannot explain is the frequent observation of consensus on decisions by actors with different frames/narratives/perceptions/understandings of the problems, as well as observations of dissensus and conflicts around decisions by actors who seem to share similar understandings of the problems at hand. Contemporary research on a different body of literature, the Advocacy Coalitions Framework, suggests that similar preferences on specific decisions regarding divisive issues are as good at predicting the formation of coalitions as similar beliefs regarding the core themes of the coalitions (Karimo et al, 2022). This research does not help us understand how this could happen, however.…”

Competition and cooperation in artificial intelligence standard setting: Explaining emergent patterns

“…For one, agreement on standards addressing public goods problems is easier to achieve if the benefits of the public good in question extend only to “like‐minded” countries that share the same values (Abbott & Snidal, 2001, p. 354) and are therefore seen as unlikely to cheat 8 . As Karimo et al (2022, p. 8) point out, “collaboration with like‐minded others makes it more likely that the collaborating organizations get to translate their beliefs into policies.” Working within smaller organizations consisting of like‐minded countries also facilitates cooperation because these countries are less likely to have complex histories with each other or feel mutual distrust that prevents agreement. Finally, like‐minded countries are likely to be countries with similar political arrangements and at least not completely incompatible notions of the role of markets (Cath et al, 2018, p. 10).…”

Mitigating conflict with collaboration: Reaching negotiated agreement amidst belief divergence in environmental governance

“…“learn”), and possibly alter their beliefs about a policy problem (Gerlak & Heikkila, 2011; Koebele, 2019b; Leach et al, 2014; Sabatier, 1988). Even if actors do not hold the same beliefs, they may learn about areas where some of their beliefs or goals are complementary (Koebele, 2020; Koontz, 2014; Kukkonen et al, 2017; Sotirov et al, 2017), providing a foundation for negotiation (Bandelow et al, 2019; Karimo et al, in press). Belief change (via learning) as a mechanism for reducing policy conflict is most directly tied to the ACF's assumptions that belief divergence is a key driver of conflict and belief convergence can mitigate conflict.…”