Impact of Attitude and Bounded Rationality on Collective Behavioral Transitions

2026-04-29

AI Summary

This study addresses a critical limitation of the Theory of Planned Behavior (TPB)—its lack of mathematical formalism to capture the dynamic evolution of core constructs—thereby hindering explanations of collective behavioral shifts. To bridge this gap, the work proposes the first explicit dynamic model of TPB by developing an agent-based framework that integrates attitude, subjective norms, and perceived behavioral control, augmented with a behavior–attitude feedback mechanism. Through systematic simulation, the model uncovers the regulatory roles of two key parameters: attitude influence strength and bounded rationality. It demonstrates quantitatively that strategic modulation of these factors can effectively steer populations toward adopting beneficial behaviors or resisting harmful ones. This approach establishes a novel paradigm for investigating the dynamics of social behavior evolution grounded in TPB principles.

Abstract

The theory of planned behavior (TPB) is one of the most influential frameworks in social psychology, stating that a person's behavior is driven by intention, which is primarily shaped by attitude, subjective norms, and perceived behavioral control. Despite its strong empirical support, TPB remains a static conceptual framework without explicit mathematical formulations that capture the temporal evolution of its components. To address this gap, we develop a dynamic agent-based modeling framework that integrates the core principles of TPB with a behavior-to-attitude feedback mechanism. Specifically, we define behaviors based on their feedback effects on attitude and examine when the population undergoes collective transitions by either adopting a beneficial behavior or rejecting a harmful one. Results from our model demonstrate that collective transitions can be effectively controlled by adjusting two key behavioral parameters that reflect agents' attitude influence and decision rationality. These findings provide quantitative insights on TPB, highlighting the key factors that drive collective behavioral transitions and the need for further socio-psychological case studies.

Problem

• Theory of Planned Behavior
• collective behavioral transitions
• attitude dynamics
• bounded rationality
• agent-based modeling

Innovation

• agent-based modeling
• theory of planned behavior
• behavior-to-attitude feedback
• collective behavioral transitions
• bounded rationality