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In this article, we utilize the Collaborative Governance Databank to empirically explore core theoretical assumptions about collaborative governance in the context of crisis management. By selecting a subset of cases involving episodes or situations characterized by the combination of urgency, threat, and uncertainty, we conduct a plausibility probe to garner insights into a number of central assumptions and dynamics fundamental to understanding collaborative crisis management. Although there is broad agreement among academics and practitioners that collaboration is essential for managing complex risks and events that no single actor can handle alone, in the literature, there are several unresolved claims and uncertainties regarding many critical aspects of collaborative crisis management. Assumptions investigated in the article relate to starting-points and triggers for collaboration, level of collaboration, goal-formulation, adaptation, involvement and role of non-state actors, and the prevalence and impact of political infighting. The results confirm that crises represent rapidly moving and dynamic events that raise the need for adaptation, adjustment, and innovation by diverse sets of participants. We also find examples of successful behaviours where actors managed, despite challenging conditions, to effectively contain conflict, formulate and achieve shared goals, adapt to rapidly changing situations and emergent structures, and innovate in response to unforeseen problems.

Studying collaborative governance has become abooming business. However, the empirical literature still struggles to produce robust generalizations and cumulative knowledge that link contextual, situational and institutional design factors to processes and outcomes. We still have not mustered the broad and deep evidence base that will really help us sort fact from fiction and identify more and less productive approaches to collaboration. The current empirical evidence in the study of collaborative governance consists chiefly of small-N case studies or large-N surveys. The challenge is to move from case-based, mid-range theory building to more largeN-driven systematic theory-testing, while also retaining the rich contextual and process insights that only small-N studies tend to yield. This article, and the articles in the accompanying special issue, introduces an attempt to provide this middle ground– the Collaborative Governance Case Database. The database has been developed to serve as afree common pool resource for researchers to systematically collect and compare high-quality collaborative governance case studies. This article is an introduction to the database, exploring its design, opportunities and limitations. This article is also an invitation; inviting all researchers to freely use the cases in the database for their own research interest and to help strengthening the database by adding new cases there are eager to share with colleagues.

AbstractStudying collaborative governance has become a booming business. However, the empirical literature still struggles to produce robust generalizations and cumulative knowledge that link contextual, situational and institutional design factors to processes and outcomes. We still have not mustered the broad and deep evidence base that will really help us sort fact from fiction and identify more and less productive approaches to collaboration. The current empirical evidence in the study of collaborative governance consists chiefly of small-N case studies or large-N surveys. The challenge is to move from case- based, mid- range theory building to more largeN- driven systematic theory- testing, while also retaining the rich contextual and process insights that only small-N studies tend to yield. This article, and the articles in the accompanying special issue, introduces an attempt to provide this middle ground – the Collaborative Governance Case Database. The database has been developed to serve as a free common pool resource for researchers to systematically collect and compare high- quality collaborative governance case studies. This article is an introduction to the database, exploring its design, opportunities and limitations. This article is also an invitation; inviting all researchers to freely use the cases in the database for their own research interest and to help strengthening the database by adding new cases there are eager to share with colleagues.

Studying collaborative governance has become a booming business. However, the empirical literature still struggles to produce robust generalizations and cumulative knowledge that link contextual, situational and institutional design factors to processes and outcomes. We still have not mustered the broad and deep evidence base that will really help us sort fact from fiction and identify more and less productive approaches to collaboration. The current empirical evidence in the study of collaborative governance consists chiefly of small-N case studies or large-N surveys. The challenge is to move from case-based, mid-range theory building to more largeN-driven systematic theory-testing, while also retaining the rich contextual and process insights that only small-N studies tend to yield. This article, and the articles in the accompanying special issue, introduces an attempt to provide this middle ground– the Collaborative Governance Case Database. The database has been developed to serve as a free common pool resource for researchers to systematically collect and compare high-quality collaborative governance case studies. This article is an introduction to the database, exploring its design, opportunities and limitations. This article is also an invitation; inviting all researchers to freely use the cases in the database for their own research interest and to help strengthening the database by adding new cases they are eager to share with colleagues.