Pricing and positioning of remanufactured products using a nested logit model

Abstract

Product line selection and pricing are two critical strategic decisions for a manufacturing firm in terms of profitability. Remanufacturing can also significantly contribute to the profitability of a firm by reusing the used products by capturing the residual value in them rather than discarding them. In this work, we consider these two concepts together and focus on selecting optimal products within a set of candidate remanufactured products to be offered by their existing counterparts in the same market as well as setting the optimal prices of existing products and their remanufactured versions simultaneously. We formulate a mixed-integer nonlinear programming model with a cost constraint in the aim of maximizing the profit function. The customer choice is assumed to be probabilistic in which the purchase probability is proportional to an increasing monotonic function of the utility which is a linear function of product quality and price for the product, and substitution is considered by a nested structure. A base model and an extension of it are proposed. In the extended model the optimal quality level of an offered remanufactured product is tried to be determined by taking its unit production cost of quality as another decision variable in the model. The resulting model is solved by decomposing it into two sub-problems. The pricing sub-problem is solved by a modified and restarted simplex search procedure whereas the product line selection problem is solved via complete enumeration. Some computational studies are made to identify the situations under which selling remanufactured products together with their existing counterparts is profitable.