To analyze the effect of government reward-penalty policies (RPPs) on the decisions of a dual-channel closed-loop supply chain (CLSC), this paper endogenizes government decision variables to maximize social welfare and builds four decision-making models (without RPP, with carbon emission RPP, with recycling amount RPP, and with double RPP) by using a Stackelberg dynamic game between the government and supply chain members. The research results show that, (1) in the four models, there exist optimal prices and reward-penalty coefficients to maximize the supply chain members’ profits and social welfare. (2) Comparing with model , under most conditions, three government RPPs decrease the demand for new products and increase the demand for remanufactured products. Comparing the case without RPP, R’s profit decreases, and when the carbon emission cap is very big and the lowest recycling amount is very small, M’s profit increases. (3) In most cases, the three government RPPs can effectively control the total carbon emission and increase the social welfare, but they damage the benefits of retailers and consumers. With the increase of the carbon emission intensity of remanufactured products, the government can implement the double RPP, the carbon emission RPP, and the recycling amount RPP in turn.

中文翻译：

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政府政策环境下双渠道闭环供应链的决策：动态博弈论

为了分析政府奖励惩罚政策（RPP）对双通道闭环供应链（CLSC）决策的影响，本文内生了政府决策变量以最大化社会福利，并构建了四种决策模型（无RPP） ，碳排放量RPP，回收量RPP和两倍RPP），方法是使用政府与供应链成员之间的Stackelberg动态博弈。研究结果表明：（1）在四个模型中，存在最优价格和奖惩系数，以最大化供应链成员的利润和社会福利。（2）与模型相比，在大多数情况下，三个政府RPP减少了对新产品的需求，并增加了对再制造产品的需求。比较没有RPP，R的情况的利润减少，并且当碳排放上限非常大且最低回收量很小时，M的利润就会增加。（3）在大多数情况下，三个政府RPP可以有效地控制总碳排放并增加社会福利，但它们损害了零售商和消费者的利益。随着再制造产品碳排放强度的增加，政府可以依次实施双重RPP，碳排放RPP和回收量RPP。