Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17–19, 2023, Beijing, China

Research Article

Research on Sales Forecasting of New Energy Passenger Vehicles in Beijing-Tianjin-Hebei City Cluster based on Grey Prediction GM(1,1) Model

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  • @INPROCEEDINGS{10.4108/eai.17-11-2023.2342718,
        author={Ying  Li},
        title={Research on Sales Forecasting of New Energy Passenger Vehicles in Beijing-Tianjin-Hebei City Cluster based on Grey Prediction GM(1,1) Model},
        proceedings={Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17--19, 2023, Beijing, China},
        publisher={EAI},
        proceedings_a={ICEMME},
        year={2024},
        month={2},
        keywords={grey prediction gm(1 1) model; beijing-tianjin-hebei city cluster; new energy passenger vehicles; sales forecast},
        doi={10.4108/eai.17-11-2023.2342718}
    }
    
  • Ying Li
    Year: 2024
    Research on Sales Forecasting of New Energy Passenger Vehicles in Beijing-Tianjin-Hebei City Cluster based on Grey Prediction GM(1,1) Model
    ICEMME
    EAI
    DOI: 10.4108/eai.17-11-2023.2342718
Ying Li1,*
  • 1: Beijing Jiaotong University
*Contact email: liying12108@163.com

Abstract

In recent years, the international community has paid more and more attention to carbon emissions, and China's Double-Carbon Policy is also being steadily implemented. As a key industry in carbon emissions, the transportation industry has become the focus of achieving carbon reduction goals by promoting the development of new energy vehicles. The Beijing-Tianjin-Hebei city group is the closest city group to the political center in China, and its development trend is of great significance to other city groups in China due to the radiation of policy speed. Based on this, this paper uses GM (1,1) model to forecast the sales volume of new energy passenger vehicles in this city group. It is found that the change of future sales volume in this city group presents an exponential upward trend. In view of this trend, this paper puts forward corresponding policy suggestions to lay a theoretical foundation for formulating specific policy measures.