Growing Collaborations: Forecasting Growth in Partnership Networks Using a Bottom-Up Approach

Both social and organizational networks change over time. Previous research has examined and documented the change in social networks using dynamic network analysis. However, limited research has examined mechanisms of change, leaving the mechanisms in a proverbial “black box.” We show how exponential random graph models can be used to measure the influence of some of the mechanisms that drive network development. Our mechanisms are derived from network theory and applied to a goal-directed organizational partnership network, the Vermont Farm to Plate Network. Our method uses an agent-based model to induce bottom-up network change. This approach allows us to offers some explanation of the underlying mechanisms for network change. Implications for forecasting network growth in a governance and policy context are discussed.