With the prevalence of Internet technology, many recycling centers have developed a dual-channel reverse supply chain by introducing online recycling channels on the basis of offline third-party recyclers (TPR). In addition, great imbalanced development has been observed in different regions in China, as supported by the literature review. It is necessary to help companies in the supply chain to adjust their pricing strategies according to regional differences. This paper is aimed at answering the following two questions: (1) After introducing online channels, what strategies should the recycling center adopt to adjust online recycling prices and to readjust the transfer price of offline channels? (2) How do recycling centers and TPR in city A & B modify their pricing strategies in accordance with logistics costs or consumers’ awareness of sustainability changes in city B? To solve the above questions, models were made to study the pricing strategies of recycling centers and the TPR based on the Stackelberg game in a dual-channel reverse supply chain in two cities. The results indicate that recycling centers will benefit from the increase in consumers’ awareness of sustainability and the reduction in logistics costs of the online channel in city B; this is in contrast to the TPR in this city. We also find that the revenue of the TPR in city A will be affected when the above two factors in city B change. Its increase or decrease depends on the selection of pricing strategy by the recycling center.

The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.

Guaranteed-Service Approach (GSA) was used to set safety stock for multi-echelon inventory systems. This approach assumes that each stock can use operating flexibility measures such as expediting and overtime to fulfill excessive customer demand superior to a bound as a supplement to its safety stock. In this paper, we consider a continuous review assembly inventory system with Poisson final demand and fixed costs at each stock controlled by a (R, Q) policy. We use the GSA to optimize the policy with the consideration of operating flexibility costs and fixed order costs. A deterministic mathematical programming model is established for the problem. And the model is solved by a line search for finding the optimal target cycle service level to customer and an iterative procedure for solving the model when the target cycle service level is given. Moreover, we analyze the optimality conditions for the extended GSA model and obtain some important properties in given conditions. Numerical experiments on randomly generated instances demonstrate the efficiency of the procedure and confirm the solution presented in this paper.

In recent years, in order to promote the development of new energy vehicle industry, the Chinese government has actively implemented the dual credit policy. However, the implementation of the dual credit policy has also brought serious financial pressure to new energy vehicle enterprises. As the core of the new energy vehicle supply chain, the new energy vehicle manufacturers not only need to choose between bank loans and internal financing strategies when facing financial constraints, but also need to optimize the decisions under different financing strategies. In this paper, aiming at the supply chain structure composed of a fuel vehicle manufacturer, a battery manufacturer and a new energy vehicle manufacturer with financial constraints, the Stackelberg game model is constructed and solved under three scenarios: no financial constraints, bank loans and internal financing. Based on considering the battery manufacturer as the leader and the new energy vehicle manufacturer as the follower, we solve the optimal decisions and profits through comparative analysis, and further verify the results by using a numerical example. The results indicate that the change in interest rate in the two financing modes will have opposite effects on the fuel vehicle manufacturer; although the battery R&D level and the profit of the new energy vehicle manufacturer will be higher under internal financing, it will harm the profit of the battery manufacturer; Interestingly, under the internal financing mode, the increase in interest rate will actually inhibit the profit of the battery manufacturer.

The dual credit policy brings conflict to the NEV (New Energy Vehicle) supply chain, so it is necessary to study the coordination strategy of NEV supply chain. Firstly, considering a competitive ICEV (Internal Combustion Engine Vehicle), we construct and solve Stackelberg game models in both centralized and decentralized decision modes. Then, we construct a revenue sharing contract to optimize decisions and profits under decentralized mode. Finally, we verify the model solution results by using numerical examples, and propose new management insights from three perspectives of protecting the ICEV industry, promoting the NEV market, and sharing the credit income. The research results indicate that the dual credit policy can effectively promote the development of NEV enterprises, and the higher the credit price, the greater the promoting effect; The government should not set excessively high credit price; The credit revenue sharing contract, which optimizes the decision-making of enterprises from the perspective of the whole supply chain system, can benefit both NEV manufacturers and battery manufacturers.

Under the dual credit policy, the new energy vehicle industry is faced with the multi-decision collaborative optimization problem of service level, R&D level and pricing under different service modes. This paper aims at the supply chain structure composed of a new energy vehicle manufacturer and a battery manufacturer, and respectively constructs decision models under three service modes: the new energy vehicle manufacturer providing service, the battery manufacturer providing service, and jointly providing service. On the basis of solving the model by using Stackelberg game theory, numerical analysis is used to put forward management suggestions. The results show that under the joint providing service mode, both enterprises can obtain the highest profit, followed by the mode of the new energy manufacturer providing service, while the profits of both enterprises are the lowest under the mode of the battery manufacturer providing service. The government departments should actively increase the credit price under the policy.