What types and conditions foster active collaboration?: a theory-driven agent-based model

Abstract

Although collaborative governance frameworks have long been established in the literature, their systematic and process-oriented application remains limited because of the complexity of collaborative interactions. This study addresses this gap by developing an algorithmic model grounded in collaborative governance theory and the Korean administrative context. Using a theory-driven agent-based model, it compares three governance arrangements – collaboration, coordination, and cooperation – and examines how external pressure and internal readiness influence collaboration intensity through repeated interactions. The results show that both conditions generally strengthen collaborative networks, while internal readiness exhibits a stronger influence under several governance scenarios and model conditions.