Maximizing the Profit of Omnichannel Closed-Loop Supply Chains with Mean-Variance Criteria

Abstract

Maximizing profitability stands as a paramount objective within supply chains. The conventional approach involves implementing the omnichannel retailing strategy to integrate diverse sales channels. However, such implementation often introduces uncertainty in product pricing and recycling, undermining the system's robustness. In this study, we leverage the combined power of leader-follower game and mean-variance theories to construct two optimization models for the omnichannel closed-loop supply chain. Specifically, our focus lies in analyzing the performance of manufacturers who distribute products through the physical store. By meticulously considering the risk-aversion attribute inherent in the supply chain, we derive closed-form solutions for the optimal approach. The main results show the positive impact of a risk-averse attitude exhibited by the physical store on the overall profitability of the supply chain. However, if the introduced physical store belongs to another firm, the total profit experiences a decline. To further substantiate our claims, we conduct a comprehensive numerical analysis to show the performance of our optimization models.