An Agent-based Model For Simulating Collective Efficacy

Agent-based modeling and simulation of collective efficacy is useful to understand and study the relationship between community-related problems and individuals' cognitive process. This paper presents a design of collective efficacy simulation using an agent-based model. We integrate collective efficacy into the framework of Theory of Planned Behavior (TPB) and show how collective efficacy is updated based on individual agents' cognitive processes in response to occurrences of community-level events. Experiment results are provided to demonstrate the agent model and to show the spatial patterns of collective efficacy emerging at the community level.