Pricing and Collecting Decision of a Closed-Loop Supply Chain Under Market Segmentation With Reward-Penalty Mechanism

This paper examines the impact of reward-penalty mechanism (RPM) on the decision-making of a closed-loop supply chain (CLSC) under the framework of market segmentation. Decentralized dynamic game models are developed to obtain and compare the pricing and collecting decision of the CLSC with and without RPM. We find that: (i) RPM improves the actual collection rate and the profit of the recycler, while it decreases the prices of new and remanufactured products in market segments in response to higher consumer preferences; (ii) a higher buyback price guarantees that the manufacturer becomes more profitable when the government imposes low or high intensity of reward-penalty. Otherwise, the manufacturer should set a lower buyback price when the government imposes moderate intensity of reward-penalty; (iii) higher intensity of reward-penalty can not only effectively improve the environmental sustainability of CLSC, but also obtain higher social welfare; (iv) the mechanism that reward equals penalty is optimal, in which case the same intensity maximizes the actual collection rate as well as the profits of the manufacturer and the recycler. Our analysis discusses the parameters which have significant impacts on the pricing and collecting decision of the closed-loop supply chain and gains managerial insights that are both environmentally and economically beneficial.