Determining assortments of used products for B2B transactions in reverse supply chain

Abstract

The reverse supply chain – in which used products are collected from end-users and remanufactured for resale – includes a consolidator, broker, and remanufacturer. The used products entering the reverse supply chain tend to be of heterogeneous quality levels and require different amounts of remanufacturing effort and cost. The consolidator collects these products from the end-users and sells them in unsorted form to the broker; the broker sorts them into different grades and offers the graded units to the remanufacturer. This article analyzes the business-to-business transaction between the broker and the remanufacturer. We determine the broker’s optimal assortment in terms of the optimal number of grades, their expected remanufacturing costs, and selling prices. We show that: (i) the optimal grades created by the broker and their prices depend on the distribution of the remanufacturing costs for the used products acquired by the broker and the remanufacturer’s demand distribution; and (ii) the expected remanufacturing costs and selling prices for each grade follow a specific ordering and constitute a convex hull. Comparative statics analyses show the malleability of the grading process to the changes in the broker’s exogenous parameters. A numerical study using data from prior research on reverse channels shows that the optimal grading policy results in higher profits for both the broker and the remanufacturer as compared with a heuristic policy for creating grades.

Keywords:

• Reverse supply chain
• B2B transactions
• used products
• assortment planning

Notes

1 As we discuss in the conclusion, our model can be modified to account for scenarios when the remanufacturer processes some units before the demand is realized.

Additional information

Notes on contributors

Akshay Mutha

Akshay Mutha is an assistant professor of business analytics, at the University of Vermont. His research focuses on developing analytical models for businesses engaged in remanufacturing and servicizing operations.

Saurabh Bansal

Saurabh Bansal is an associate professor of supply chain management and information systems, and on the operations research faculty at the Pennsylvania State University. His research focuses on developing mathematical models, algorithms, and data analysis protocols to estimate business risks and optimize business operations under risks.