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Analyzing Policy Networks Using Valued Exponential Random Graph Models: Do Government-Sponsored Collaborative Groups Enhance Organizational Networks?

Tyler A Scott
Published in: Policy studies journal: the journal of the Policy Studies Organization (2015)
This paper examines collaborative management groups from the perspective of policymakers seeking to increase coordination within a policy network. While governments often support collaborative groups as a tool to address perceived network failures such as a lack of coordination, the net impact groups have is unclear. I use valued exponential random graph models (ERGMs) to model relationships of varying strength among a regional network of organizations involved in 57 collaborative groups. This provides a unique opportunity to study the interplay between numerous groups and organizations within a large-scale network. Valued ERGMs are a recently developed extension of standard ERGMs that model valued instead of binary ties; thus, this paper also makes a methodological contribution to the policy literature. Findings suggest that participation in collaborative groups does motivate coordination and cooperation amongst individual network organizations; however, this effect is strongest for: (i) organizations that are not already members of another group and (ii) organizations that do not have a preexisting tie. These results support a transaction-cost-based perspective of how government-sponsored collaborative groups can influence network coordination; further, they also provide an empirical example of the Ecology of Games, in which multiple collaborative institutions have interactive effects on one another within a policy network.
Keyphrases
  • quality improvement
  • public health
  • healthcare
  • mental health
  • systematic review
  • machine learning