Abstract
PurposeThis paper intends to address the decision-making and coordination of green supply chain (GSC) considering risk-averse manufacturers under mixed carbon policy.Design/methodology/approachThis paper focuses on a GSC consisting of a manufacturer and a retailer, in which the manufacturer is risk-averse (R-A). This paper employs Stackelberg game theory and mean variance analysis to assess the pricing decision-making process under various scenarios. Furthermore, cost-sharing contracts are introduced to coordinate the GSC.FindingsThe research results suggest that the green level of the product and the profit of the GSC under a centralized scenario are higher than those under a decentralized scenario, while the retail price is lower. Under the decentralized scenario, the green level of product, wholesale price and manufacturer’s profit in the R-A scenario are lower than the values in the risk-neutrality scenario, while retailer's profit is higher. In addition, when a cost-sharing contract is utilized for coordination in the GSC, it can lead to Pareto improvement, regardless of whether the manufacturer makes risk-neutrality or R-A decisions.Originality/valueThis research provides a deeper understanding of GSC decision-making and coordination strategy under mixed carbon policy with consideration of R-A from a theoretical perspective and provides decision support for enterprises to choose strategies in practice.
Reference29 articles.
1. Effects of carbon emission reduction on supply chain coordination with vendor-managed deteriorating product inventory;International Journal of Production Economics,2019
2. Carbon footprint and the management of supply chains: insights from simple models;IEEE Transactions on Automation Science Engineering,2012
3. Research on decision-making of supply chain with dual sale mode considering government's low-carbon policies;Chinese Management Science,2018
4. Research on low-carbon coordination of dual-channel supply chain based on revenue sharing;Statistics and Decision-Making,2020
5. Optimal production and subsidy rate considering dynamic consumer green perception under different government subsidy orientations;Computers and Industrial Engineering,2022