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Public policymakers and managers use collaborative governance processes strategically to involve relevant stakeholders in developing plans, designing programs, and implementing policies. Although intuitive and normatively popular, such deliberative processes pose a tension between the prospective benefits of broader involvement (both instrumental benefits such as information and support for implementation and normative benefits related to representation) and the challenges of reaching agreements amongst disparate stakeholders. This paper builds upon empirical studies of complex policy networks to explore what happens when a public official initiates a collaborative governance process within a policy network. We use agent-based modeling (ABM) to simulate the impact of process attributes, such as how many people are involved, how invitees are selected, and the presence of difficult participants, within different network contexts, including network size, policy uncertainty, and preference distributions. This simulation-based approach does not rely upon survey instruments or subjective responses, and thereby complements existing empirical studies of collaborative governance. ABM provides a platform to explore the implications of key network assumptions, test different initiation strategies, model emergent properties resulting from inter-actor deliberation, and simulate long-run outcomes. Our results show how network and system conditions modulate the impact of group convening and design strategies. More generally, we demonstrate how ABM can be used to examine potential collaborative governance outputs under different design choices and network contexts when large data sets are unavailable.
Scott et al. (Tue,) studied this question.