Choice-Induced Preference Change under a Sequential Sampling Model Framework

Sequential sampling models of choice, such as the drift-diffusion model (DDM), are frequently fit to empirical data to account for a variety of effects related to accuracy/consistency, response time (RT), and sometimes confidence. However, no model in this class can account for the phenomenon known as choice-induced preference change, where decision makers tend to rate options higher after they choose them and lower after they reject them. Studies have reported choice-induced preference change for many decades, and the principal findings are robust. The resulting spreading of alternatives (SoA) in terms of their subjective value ratings is incompatible with traditional sequential sampling models, which consider the rated values of the options to be stationary throughout choice deliberation. Here, we propose an extension of the basic DDM that allows the drift rate to vary across deliberation time depending on which attributes are attended to at which points in time. Critically, the model assumes that choice deliberation commences based only on the more salient attributes of the options, and that additional attributes eventually come into consideration when the decision cannot be resolved based on the initial attributes alone. We show that this model can account for SoA (in addition to choice consistency and RT), as well as all previously reported relationships between SoA and choice difficulty, attribute disparity, and RT.