Growth Matters: Identifying Best Practices in Growing Civic Collaborations.

Abstract

The recently introduced Health Children and Families Act represents a potential $15B investment in promoting community health by legislating the implementation of the Nurse-Family Partnerships (NFP) program in all 50 states. Although legislation does not mandate the implementation strategy, civic collaboration has been found to be uniquely successful. To fully leverage the value of civic collaboration, this study aims to identify and formalize one important aspect of collaborative activity the growth process during the initial stages of collaboration. By comparing field observations from several community health programs, we have identified the features of civic collaborations most associated with favorable program outcomes. Specifically, successful collaborations have started with small initial groups, proceeded to engage in high quality planning processes, and have slowly included new members. Using a coordination game model from experimental economics, we formalize strategic behaviors in civic collaboration as a minimum-effort coordination game with Pareto ranked equilibria. Three best practices (small initial group, planning, and growth) observed from the field are interpreted as interventions in coordination failures within the game. This coordination game framework is incorporated into an agent-based model. A series of experiments in the agent-based model offer an in-depth understanding of the separate and combined effects of the three best practices and how their contributions change over the lifecycle of a civic collaboration program. Findings from this study not only inform the program implementation of Healthy Children and Families Act, but also help stakeholders in other civic collaboration programs to understand and adopt the best practices and achieve optimal outcomes.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/55673/1/erikwj_1.pd