*Names in bold indicate Presenter
Cain and Nelson (2012) argue that understanding citizen preferences and behavior is not enough to understand siting outcomes. Rather the interactions between stakeholder dynamics, infrastructure project attributes, and the institutional settings in which they are embedded, need to be simulated using organizational, political, economic, social psychological, and geospatial variables involved in siting decisions. This paper present results from a new agent based model (ABM) of infrastructure siting. Agents’ preferences are fed into the ABM model which uses game theory, bargaining dynamics, and network theory to predict agents’ actions and reactions in the policy process. The ABM model has three sequential submodels, a citizen module, a stakeholder lobbying module and a regulatory decision making module. Citizens react to transmission siting projects by forming opinions as well as attempting to shape others’ opinions. These behaviors can result in the formation of community based organizations (CBOs) that either support or oppose such projects. Next, using noncooperative game theory, organizational stakeholders seek to lobby not only citizen opinions and the emergent CBOs as well as other stakeholders in order to maximize their organizational interests. Finally, the regulatory decision making module simulates how regulators ultimately approve or deny siting activities given the constantly shifting techno-social landscape.
Using the Tehachapi project as a simulation example, we perform a quasi-global Monte Carlo sensitivity analysis of over 4000 simulations. Our research hypothesis investigates the efficacy of strong citizen opposition on agency and regulatory preferences. While political participation typically improves environmental decision making (ie Lubell, 2004), there is considerable evidence that Environmental Impact Assessment processes often are not receptive to citizen input (Jay et al, 2007). Our results indicate that the presence of strong community networks predicts stronger CBOs that are then able to get a “seat at the table” with agency stakeholders and can leverage strong citizen opposition into favorable agency and regulatory outcomes. The impacts of other “policy levers” in the model are also investigated, including risk communication strategies, policies to mitigate the disruption of the project, the perceived need for the project, as well as perceptions of the fairness of the siting project. Given these empirical results we can estimate the elasticities of policy change for a given change in citizen opposition, holding other variables constant.
- Nelson 21 Oct 2013 APPAM paper.pdf (731.1KB)