Intuition in Decision Making: Insights From Drift Diffusion Modeling

Abstract

Research on intuition often produces conflicting results and suffers from reliability issues due to the lack of tools that can conclusively evaluate a person's latent intuitive position. It has been recently proposed that a decision maker's intuitive position can be evaluated by estimating parameters with sequential sampling models (SSMs), which provide a biologically plausible framework to measure how intuition affects decisions. In two studies, we use the drift diffusion model (DDM), as a type of SSM, to investigate topics where intuition is difficult to evaluate. In Study 1, we used the DDM to examine how the cognitive reflection test (CRT) scores relate to intuition in risky decision making and found that individuals with high CRT scores had superior performance and relied more on intuition. These findings challenge the conventional view that high CRT scores imply less reliance on intuition and that intuition is detrimental to decision performance. In Study 2, we examined the cross-domain stability of the preference for intuition and found that decision makers rely more on intuition in the social decision domain than in the risky decision domain and that these measures are not correlated across the two domains. The evidence for this unstable preference has hitherto primarily resulted from self-reports, which have a questionable ability to assess the preference for intuition. In both studies, we demonstrate that the DDM can accurately simulate the decision outcome and decision time patterns that are affected by intuition, providing evidence for the usefulness of DDM analysis in the study of intuition.