Maximizing the profit of omnichannel closed-loop supply chains with mean-variance criteria

The maximization of profitability stands as a paramount objective within supply chains. The conventional approach involves implementing an 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 opti-mization models for the omnichannel closed-loop supply chain. Specifically, our focus lies in analyzing the performance of manufacturers who distribute products through physical stores. 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 system profitability. However, if the introduced physical store belongs to another firm, then total profit experiences a decline. To further substantiate our claims, we conduct a comprehensive numerical analysis to show the performance of our optimization models.

Automated summary

This study constructs two optimization models for the omnichannel closed-loop supply chain by leveraging the combined power of leader-follower game and mean-variance theories. The focus is on analyzing the performance of manufacturers who distribute products through physical stores. The results show that the risk-averse attitude of the physical store has a positive impact on the overall system profitability, but if the introduced physical store belongs to another firm, total profit experiences a decline.