Investigating the effect of cognitive bias influences on sustainable decision-making in complex systems

Abstract

This study investigates the role of cognitive biases in decision-making within the Circular Economy and explores how these biases can be validated and addressed through empirical survey data. By developing a Conceptual Causal Loop Diagram and merging it with a foundational CLD, a comprehensive model was created to simulate the dynamics of CE systems. Key variables such as media influence, response to information, and behaviour change were incorporated into the Stock and Flow Diagram, enhancing the model's ability to represent real-world sustainability challenges. The principal results show that variations in biases and other factors can significantly impact CE outcomes, including individual actions, business priorities, and environmental responsibilities. The study highlights key variables, including media influence, response to information, behaviour change, and their roles in shaping CE outcomes. These components contextualize the study within the broader challenge of understanding and mitigating biases to foster sustainability, framing the research within the CE's ongoing efforts to achieve sustainable economic and environmental outcomes. Noteworthy conclusions include the identification of leverage points for promoting sustainability and the importance of understanding biases to improve decision-making processes in CE. The findings reveal biases saturate within approximately 100 months, while the perceived urgency for sustainability declines sharply within 50 months unless actively reinforced. This research contributes to the broader understanding of human factors influencing the transition to a sustainable economy.