The Cognitive Bias-Informed Latent Class Choice Model: A Novel Approach to Predicting Human Behavior

Economic policies aimed at achieving a sustainable society have been formulated in several countries. To choose effective policies, individuals' behavior must be guided in line with policymakers' intentions. Therefore, policy makers often explore models designed to predict people's behavior. However, it is difficult for existing models to accurately predict human behavior, such as cognitive biases and individual differences, while maintaining a clear interpretation of the mechanisms behind this behavior. In this study, we propose a new method that can predict actual human behavior while ensuring the interpretability of behavioral choices by integrating knowledge from cumulative prospect theory and latent class choice models into an advanced multinomial logit model. This model has better predictive performance than conventional models and it can predict human behavior more precisely.