In recent years, there has been an increasing concern on closed-loop supply chains and green supply chains. Due to both economic incentives and legislation regulation, more and more companies are involved in product recovery business. Remanufacturing is one of the various product recovery options. Successful practices of remanufacturing can be found in industries like automotive, construction, mining, aerospace, etc. A special feature of remanufacturing business is the correlation between supply and demand. This phenomenon is due to the large proportion of replacement customers. As reported by Lund and Hauser (2010), many remanufactured products are used for replacement. A possible explanation would be that customer wants to avoid the switching cost of changing to a different product.
This study is motivated by these special characteristics of remanufacturing practices. A remanufacturing system is considered with the existence of replacement customer segment and uncertain return yield. The remanufacturing company acquires used products from previous customers through acquisition programs. The supply of return flow is price dependent. Demand comes from both replacement customer and first-time buyer which is also price dependent. Replacement customer will return their old products and get trade-in rebates for new purchases. The demand can be satisfied by either remanufacturing used products or manufacturing new ones.
This model represents the remanufacturing practice of many durable products. For highly saturated markets, a significant portion of purchase could be replacement. A practical example can be found in Caterpillar, which is the world’s largest manufacturer of construction and mining equipment and diesel and natural gas engines. Customers who return their end-of-life products will get a cashback from Caterpillar. The company also offers trade-in rebates to those replacement customers. In this article, the problem with deterministic and random yield rate is studied. The effect of different pricing schemes is also investigated.
The rest of the study is organized as follows. The relevant literature is reviewed in section “Related Literature.” In section “Model,” the model is described in detail and the optimal pricing policy is presented. To get managerial insights, numerical study is provided in section “Numerical Study.” Finally, conclusions and future research directions are discussed in section “Conclusions.”