Decision Making under Dual-System Thinking

2026-05-26

AI Summary

This study addresses the challenge that traditional economic decision models struggle to capture systematic biases in human discrete choice behavior by proposing a novel decision framework grounded in the psychological dual-process theory (DST). The model formalizes the interaction between intuitive-automatic and deliberative-analytic cognitive processes through a single cognitive weight parameter, thereby operationalizing dual-process theory into a quantifiable and estimable discrete choice model for the first time. Empirical results demonstrate that, with only one additional parameter, the model successfully replicates multiple behavioral anomalies and significantly outperforms classical models across diverse experimental settings. Furthermore, it extends naturally to optimal menu design and rational analysis under stochastic environments, underscoring its superior explanatory power and predictive performance.

Abstract

This paper introduces the Dual-System Thinking (DST) model, a decision-theoretic framework that integrates psychological dual-process theories into economic modeling. A single cognitive weight parameter governs the relative influence of the automatic and deliberate cognitive systems. Even the simplest form of DST exhibits distinct behavioral patterns, suggesting that the psychological insights of dual-system theory offer a distinct and valuable approach to modeling choice behavior. Empirically, we show that the model can accommodate several empirical findings and outperform well-known models in discrete choice analysis across various contexts. We also apply the model to study optimal list design and rationality in stochastic environments.

Problem

• Dual-System Thinking
• Decision Making
• Choice Behavior
• Cognitive Systems
• Discrete Choice

Innovation

• Dual-System Thinking
• cognitive weight parameter
• discrete choice analysis
• dual-process theory
• decision-theoretic framework