Modeling the Theory of Planned Behavior from Survey Data for Action Choice in Social Simulations

摘要

Current dialogues across a variety of disciplines from the social, behavioral and computer sciences have made clear the need for authentic, repeatable and actionable social simulations. Understanding how the individuals that comprise various populations (and segments of society) might respond to a given set of conditions provides the potential to better inform analysts and decision makers in a wide variety of settings. Here we examine the implications of applying a well-documented behavioral prediction theory, Icek Ajzen 's Theory of Planned Behavior (TPB), within a social simulation in the context of public policy decision making. We provide brief overviews of both TPB and the construction of artificial societies, a full description of the TPB implementation within an artificial society, and develop an argument for the benefits of informing action choice models such as TPB from representative survey data.