Proceedings of the 4th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2022, December 9-11, 2022, Chongqing, China

Research Article

Research on Green Supply Chain Game of Joint Decision-making of Carbon Emission Reduction Effort and Inventory

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  • @INPROCEEDINGS{10.4108/eai.9-12-2022.2327590,
        author={Tongtong  Li},
        title={Research on Green Supply Chain Game of Joint Decision-making of Carbon Emission Reduction Effort and Inventory},
        proceedings={Proceedings of the 4th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2022, December 9-11, 2022, Chongqing, China},
        publisher={EAI},
        proceedings_a={MSIEID},
        year={2023},
        month={3},
        keywords={green supply chain; demand variability; dynamic games; carbon reduction effort; inventory decisions},
        doi={10.4108/eai.9-12-2022.2327590}
    }
    
  • Tongtong Li
    Year: 2023
    Research on Green Supply Chain Game of Joint Decision-making of Carbon Emission Reduction Effort and Inventory
    MSIEID
    EAI
    DOI: 10.4108/eai.9-12-2022.2327590
Tongtong Li1,*
  • 1: Beijing University of Technology
*Contact email: li247626071@126.com

Abstract

Greenhouse gas emissions have caused serious environmental problems, which are gradually affecting social and economic development. This paper takes the environmental perspective into supply chain decision-making and researches the two-level green supply chain game problem of joint decision-making of carbon emission reduction effort and inventory. First, a centralized supply chain decision-making model is built, proving that carbon emission reduction effort can increase the optimal order quantity of the centralized supply chain system, and the increase of demand variability will reduce the optimal profit of the centralized supply chain system. Secondly, in the manufacturer-led Stackelberg game model, the equilibrium solution and its existence conditions are obtained by using the backward induction method, and proving that the manufacturer’s carbon emission reduction is beneficial to itself. Finally, calculating numerical examples to verify the above results by Matlab.