Abstract
Problem definition: This paper focuses on subscription box services in which a provider selects the assortment of products to include in the box by taking into account the customer’s preferences. Customers interested in purchasing a product choose between engaging in active search (i.e., visit physical stores) or subscribing to a box delivery service. We study the subscription box company’s problem of selecting the optimal contents of the box to maximize expected revenue (by driving demand from customers). Methodology/results: Because a product may be both available at a store and included in the box, the assortment in a box affects the set of stores that a customer would visit under active search and, therefore, the customer’s subscription decision. We model such interaction by applying a cross-nested logit framework that correlates the contents in the box with the products available at the stores. We find that the box should include a collection of popular subsets of the store products for customers that experience a relatively low or relatively high search cost. If a preview of the box is available, we find that, for customers with intermediate values of the search cost, it may be optimal to include a so-called utility loss leader, that is, a product with relatively low valuation, to entice customers to subscribe to the box delivery service and therefore increase the likelihood of a sale. We use rational expectations to model a setting in which a preview of the box is not available. In such cases, it is never optimal to include a utility loss leader in the box. Managerial implications: Our model captures the impact of product overlap across different shopping channels on customer choice and the subscription box company assortment decision. We derive insights on how the subscription service provider should determine the contents of the box in anticipation of the customer’s search behavior. We also examine the decision of offering exclusive products in addition to branded items. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.1204 .
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