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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 membersâ€™ 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 â€™s profit decreases, and when the carbon emission cap is very big and the lowest recycling amount is very small, M â€™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.

Decision-Making of a Dual-Channel Closed-Loop Supply Chain in the Context Government Policy: A Dynamic Game Theory