How the qualities of actor-issue interdependencies influence collaboration patterns

Abstract

Environmental governance is complex because it addresses challenges anchored in different sectors and concerns multiple interdependent issues. Managing those complex interdependencies through collaboration is vital for efficient long-term environmental governance. However, because interdependencies between environmental issues are challenging to unravel and vastly complex, it is challenging for actors to account for them when deciding with whom to collaborate. I use the concept of social-ecological networks to study interdependencies among actors and environmental issues and ask how the quality of actor-issue interdependencies influences collaboration patterns. Based on the actor-issue network, I account for interdependencies based on three distinct qualities of actor-issue paths, i.e., (i) length of actor-issue paths: how closely actors are connected by environmental issues, (ii) multiplexity of actor-issue paths: if actors have multiple parallel paths connecting them through environmental issues, and (iii) similarity of actor-issue paths: whether actors’ environmental impact is similar to one of their potential collaboration partners. Using exponential random graph models and data on eight Swiss wetlands, a qualitative meta-regression analysis of the results reveals that the three qualities of actor-issue interdependencies influence collaboration patterns between actors. Whether the impact of actor-issue interdependencies on the probability of collaboration ties is positive or negative largely depends on the complexity of the governance situations. Only in situations with homogeneous case areas and under the absence of borders (low network exogenous governance complexity) as well as in the presence of many actors do the length, multiplexity, and similarity of actor-issue interdependencies have a clear, positive impact on the formation of collaboration ties. Although the comparative setting helps identify specific governance settings where the hypotheses are supported, it also reveals the importance of multi-case studies to compare contextual differences between cases.