<ul><li>This study investigates dynamic multi-product selection and pricing using a censored multinomial logit (C-MNL) choice model.</li><li>The goal is to maximize seller revenue by adjusting product offerings and prices based on buyer preferences and purchase feedback.</li><li>The proposed approach combines a Lower Confidence Bound (LCB) pricing strategy with an Upper Confidence Bound (UCB) or Thompson Sampling (TS) product selection approach.</li><li>Simulations validate the effectiveness of the methods in maximizing seller revenue.</li></ul>

Dynamic Assortment Selection and Pricing with Censored Preference Feedback

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