Strategic resource allocation in competitive markets: an agent-based simulation of behavioral drivers of ambidexterity

This study investigates how behavioral factors, grounded in the Theory of Planned Behavior (TPB), influence CEOs’ resource allocation decisions between exploration and exploitation, and how these decisions impact organizational performance. An agent-based simulation model replicates the Iranian pharmaceutical market, incorporating three agent types: company agents (modeled using TPB), competitor agents (based on the Miles and Snow typology), and a market agent (structured around Porter’s Five Forces). Strategy effectiveness is evaluated through the Fuzzy Delphi Method, and the model is calibrated using eight years of real-world data through a genetic algorithm. The results show that CEOs who rely more heavily on personal attitude and perceived behavioral control (PBC)—rather than subjective norms—achieve greater market share, even without increasing resources. Furthermore, adapting CEO behavior based on competitor performance (i.e. dynamic learning) significantly enhances strategic outcomes. These findings highlight the role of behavioral adaptability in fostering exploration within dynamic markets. Further empirical validation across different organizational settings is needed to enhance the model’s generalizability. The study provides actionable insights for managers aiming to improve strategic agility by integrating behavioral traits and environmental dynamics into resource allocation decisions.