International Journal of

Business & Management Studies

ISSN 2694-1430 (Print), ISSN 2694-1449 (Online)
DOI: 10.56734/ijbms
Framework for stochastic returns management in a closed-loop supply chain

Abstract


The ways of improving the performance of a supply chain through effectively and efficiently closing the loop have received considerable attention both from academic researchers and industry practitioners over the past two decades. This paper proposes a Closed-Loop Supply Chain (CLSC) model with independent third-party reverse logistics Provider (3PRLP) for returns processing. Realistically, product demand is generated by a stochastic process and a fraction of the units that are initially sold are returned by consumers for a full refund in every period. We model the forward flow interaction between the supplier, the retailer and 3PRLP by a widely accepted control policy that is lot size-reorder point inventory policy, which is detailed by the Markov process. We utilize a queuing network to capture reverse flow activities of the 3PRLP, which consists of customer decision delay and each of the 3PRLP activities. We characterize the expected profits for both firms and derive the effects of key parameters through a set of numerical examples. The results of the optimization analysis indicate that both firms’ benefits from processing returns increase with an increasing returns rate. This is due to fact that the retailer captures more profits through selling processed returns at the price of new product. The 3PRLP unambiguously earns more profit from processing the returns since fees from processing returns are sole source of revenue. Furthermore, the directions of effects of changes in the holding cost are similar for both the retailer and 3PRLP. However, the magnitude of effects of the same parameter is quite opposite. Interestingly, the retailer’s profit appears to be more sensitive to the holding cost than that of the 3PRLP’s profit.