EXPRESS: Operations Management under Paradox of Choice

This paper examines how assortment size influences consumer purchasing behavior and retailer profits, focusing on the paradox of choice (PoC), where overly limited or excessive options can diminish purchase intent. Although PoC effects are well-documented in behavioral research, their impact on assortment and pricing strategies in retail remains underexplored. To bridge this gap, we formalize PoC mathematically by modeling the utility of the no-purchase option as a U-shaped function of assortment size. We integrate this PoC framework into several discrete choice models, using the multinomial logit (MNL) model as the focal model. By decomposing the assortment problem into subproblems with fixed assortment sizes, we develop efficient solutions for the assortment optimization and the joint assortment and price optimization problems under the MNL with PoC model. Additionally, we compare the optimal solutions of the classical MNL model and the MNL model with the PoC effect through theoretical analysis and numerical experiments, offering managerial insights to guide firms in optimizing their assortments. We further extend our approach to derive optimal assortment and pricing solutions for the nested logit model employing a linear programming approach. Moreover, we devise a Fully Polynomial Time Approximation Scheme (FPTAS) for the assortment optimization under the mixture of multinomial logit model with the PoC effect. This study advances the integration of behavioral insights into discrete choice models, illustrating how retailers can optimize product assortments and prices by balancing variety with cognitive effects linked to assortment size.