Pricing and collection decisions of a closed-loop supply chain with fuzzy demand

Abstract

This paper proposes one centralized and three decentralized models (manufacturer-dominated, retailer-dominated, and collector-dominated) for a closed-loop supply chain with fuzzy demand and different quality levels for second-hand products. Optimal pricing, collection ratios, and profit allocations for each model are determined through a combination of a Stackelberg game and a fuzzy cut-set method. The model is also successfully applied to a case of automobile starter. Results indicate that the centralized model can gain the highest expected overall profit if the cost coefficient of collection effort and the difference between unit mean transferred price and unit classification expense of recycled product are greater than the corresponding thresholds. For the three decentralized models, optimal prices of new products rise with the ratio of used products of different quality levels. However, the optimal prices of new and remanufactured products and the optimal collection ratios drop with the cost coefficient of the collection effort. Additionally, a counterintuitive result is identified. The optimal collection ratio reaches a maximum in the manufacturer-dominated model rather than the collector-dominated model. Two important management implications are derived from the results: First, all supply chain members should build strategic partnerships following a centralized model to maximize the expected overall profit; Second, the manufacturers should strive for raising the remanufacturing rate of recycled products to gain a maximum expected overall profit and a satisfactory collection ratio of recycled products.