Analysis of Multi-Actor Policy Contexts Using Perception Graphs

Policy making is a multi-actor process: it involves a variety of actors, each trying to further their own interests. How these actors decide and act largely depends on the way they perceive the policy problem. This paper describes dynamic actor network analysis (DANA), a graph-based method/tool to analyze a policy context by modeling how actors view a policy issue. Each actor view is modeled as a perception graph, a type of causal map that represents the (probabilistic) relations between goals, policy actions and external influences. Cross-comparison of these perception graphs reveals properties of the multi-actor policy network, such as factor relevance, resource dependency, conflict, and possible tradeoffs. Although DANA models technically have the potential for simulating policy scenarios, some interesting methodological problems remain.