Multivariate discrete choice with rational inattention: Model development, application, and calibration

The recent application of the rational inattention (RI) theory in transportation has shed light on a promising alternative way of understanding how information influences the travel choices of passengers. However, existing RI literature has not yet addressed the discrete choice problem with multiple variates. Thus, this study develops a multivariate rational inattention (MRI) discrete choice model. This assumes that acquiring information is costly and the unit information cost varies among variates, so decision-makers rationally choose the amount of information to acquire for each variate. We demonstrate that the MRI discrete choice model results in a probabilistic formulation similar to the logit model, but with the superiority of integrating unit information costs and the prior knowledge of decision-makers. Furthermore, we apply the MRI discrete choice model to the metro route choice problem and calibrate the model based on the revealed preference (RP) data collected from the Chengdu metro. It is found that the proposed model has satisfactory accuracy with better interpretability than the logit model and univariate rational inattention discrete choice model.