Juanjuan Qin

This study considers a low-carbon supply chain model comprised of a capital-constrained manufacturer and a retailer under a cap-and-trade system. These two parties can choose from two financing modes: bank financing or mixed financing, in which the latter combines bank financing with equity financing. Two decision-making power structures are formulated, namely the Nash game model and the retailer-led Stackelberg game model. Subsequently, a comparative analysis of equilibrium outcomes for both parties within these power structures is performed, yielding the following insights: (1) In the bank financing mode, retailers find greater profitability in adopting dominance. When emission reduction efficiency is high, manufacturers obtain more profit within a Nash game context. However, when emission reduction efficiency is low, manufacturers accrue more profit in a Stackelberg game context. In the mixed financing mode without cap-and-trade regulations, supply chain participants do not express a preference for any specific game structure. (2) Without cap-and-trade regulation, in both the Nash and Stackelberg game models, the supply chain participants find more profitability in mixed financing when carbon emission reduction efficiency is high. Meanwhile, bank financing proves more profitable when the carbon emission reduction is low. Moreover, this study investigates the impact of wholesale and retail prices of low-carbon products on the financing strategies of the supply chain participants under different power structures and financing modes. Additionally, extended models are considered, including the manufacturer-led Stackelberg game structure and the capital-constrained manufacturer with a certain amount of initial capital.

In the Business to Consumer (B2C) environment, it is important to alleviate the mismatch between delivery capacity and demand in the express delivery supply chain. To do this, we propose three contracts to improve supply chain performance: the advanced payment contract, penalty contract, and time insurance contract. To assess these contracts, we considered the supply chain of one e-retailer and one express delivery provider. We discussed which contract is better for the supply chain partners when the three contracts can coordinate the supply chain. We found that when its unit cost of delayed orders is lower, the e-retailer will choose the advance payment contract among three contracts. When its unit cost of delayed orders is medium, the e-retailer will opt for the time insurance contract. When its unit cost of delayed orders is high, the e-retailer will not choose the advanced payment contract. In this case, whether the e-retailer chooses the time insurance contract and penalty contract depends on the value of wholesale price.

Motivated by the industrial practices, this work explores the carbon emission reductions for the manufacturer, while taking into account the capital constraint and the cap-and-trade regulation. To alleviate the capital constraint, two contracts are analyzed: greening financing and cost sharing. We use the Stackelberg game to model four cases as follows: (1) in Case A1, the manufacturer has no greening financing and no cost sharing; (2) in Case A2, the manufacturer has greening financing, but no cost sharing; (3) in Case B1, the manufacturer has no greening financing but has cost sharing; and, (4) in Case B2, the manufacturer has greening financing and cost sharing. Then, using the backward induction method, we derive and compare the equilibrium decisions and profits of the participants in the four cases. We find that the interest rate of green finance does not always negatively affect the carbon emission reduction of the manufacturer. Meanwhile, the cost sharing from the retailer does not always positively affect the carbon emission reduction of the manufacturer. When the cost sharing is low, both of the participants’ profits in Case B1 (under no greening finance) are not less than that in Case B2 (under greening finance). When the cost sharing is high, both of the participants’ profits in Case B1 (under no greening finance) are less than that in Case B2 (under greening finance).

This paper discusses optimal order-taking strategies under competing trade credit policies with varying demands. This study examines three decision-making scenarios, namely, (i) a centralized supply chain, (ii) a decentralized supply chain, and (iii) a coordinated supply chain with a buyback contract. Optimal decisions are obtained for each scenario. We find that if the average forecast value of credit sensitivity is higher than the real value, then the supply chain is at risk of having an overestimated performance; if the average forecast value of credit sensitivity is lower than the actual value, then the supply chain is at risk of having an underestimated performance. As the sensitivity of the credit competition increases, the supply chain’s performance decreases. The supply chain can be coordinated by a buyback contract.

This paper investigates the optimal replenishment policy for the retailer with the ramp type demand and demand dependent production rate involving the trade credit financing, which is not reported in the literatures. First, the two inventory models are developed under the above situation. Second, the algorithms are given to optimize the replenishment cycle time and the order quantity for the retailer. Finally, the numerical examples are carried out to illustrate the optimal solutions and the sensitivity analysis is performed. The results show that if the value of production rate is small, the retailer will lower the frequency of putting the orders to cut down the order cost; if the production rate is high, the demand dependent production rate has no effect on the optimal decisions. When the trade credit is less than the growth stage time, the retailer will shorten the replenishment cycle; when it is larger than the breakpoint of the demand, within the maturity stage of the products, the trade credit has no effect on the optimal order cycle and the optimal order quantity.