Pricing Decision Problem in Closed-Loop Supply Chain Under Uncertain Random Environment

Abstract

As worldwide resource limitation and environmental pollution have led to an increasing attention on reverse collection and remanufacturing in many countries, pricing decision problem in closed-loop supply chain has already attracted broad research interests. Closed-loop supply chain contains many indeterminate factors and these factors may have great effects on chain members’ decisions. Hence, it is necessary to take these indeterminacies into consideration when we deal with closed-loop supply chain management problem. This paper studies a pricing decision problem in closed-loop supply chain where randomness and uncertainty co-exist. Since we consider the different degrees of the risk-aversion of the retailer, two different models are built to derive the optimal pricing strategies of the supply chain participants under different decision conditions. On the basis of these two models and numerical studies, we explore how the risk sensitivity of the retailer affects the performances of the participants’ decisions and their optimal profits. Interestingly, It is found that the manufacturer is better off when the retailer is more risk averse.