Mean-Variance Analysis for Optimal Operation and Supply Chain Coordination in a Green Supply Chain

Abstract

It is urgently-needed to construct a green supply chain (GSC) from collection of used products through recycling of them to sales of products using the recycled parts. Besides, it is necessary to consider the uncertainty in product demand as a risk in a GSC. This study proposes the optimal operations for a GSC with a retailer and a manufacturer. A retailer pays an incentive for collection of used products from customers and sells a single type of products in a market. A manufacturer produces the products ordered by the retailer, using recyclable parts with acceptable quality and compensates the collection cost of used products as to the recycled parts. This paper discusses the following risk attitudes: risk-neutral attitude, risk-averse attitude, and risk-prone attitude. Using mean-variance analysis, the optimal decisions for product order quantity, collection incentive, and lower limit of quality level, in the decentralized GSC (DGSC) and the integrated GSC (IGSC) are made. DGSC optimizes the utility function of each member. IGSC does that of the whole system. The analysis numerically investigates how (i) risk attitude and (ii) quality of recyclable parts affect the optimal operations. Supply chain coordination between GSC members to shift IGSC from DGSC is discussed.

The coordination mechanism of a risk-averse green supply chain

“…Some researchers have examined the green supply chain considering members’ risk preferences. Yamaguchi et al (2017) optimized the order quantity collection incentive and the lower limit of quality level of decentralized green supply chain and integrated green supply chain under risk-neutral, risk-averse and risk-prone attitudes, respectively, using the mean variance analysis approach. Raza and Govindaluri (2019) investigated a green dual channel supply chain and suggested an enhanced dual channel supply chain coordination model to achieve supply chain coordination.…”