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Impact of Carbon Trading Mechanism Considering Blockchain Technology on the Evolution of New Energy Vehicle Industry in the Post-Subsidy Era

Author

Listed:
  • Wenhui Zhao

    (College of Economics and Management, Shanghai Electric Power University, Shanghai 201306, China)

  • Yimeng Liu

    (College of Economics and Management, Shanghai Electric Power University, Shanghai 201306, China)

  • Jiansheng Hou

    (Jinhua Power Supply Company, Jinhua 321035, China
    State Grid Zhejiang Electric Power Co., Jinhua 321000, China)

  • Lifang Liu

    (Shanghai Qiyuan Core Power Technology Co., Ltd., National Power Investment Green Power Transportation Industry Innovation Center, Shanghai 201700, China)

Abstract

The incentives for the new energy vehicle industry have been decreasing year by year, and the industry has gradually returned from being “government-oriented” to “market-oriented”. In this context, motivating car companies and consumers to choose new energy vehicles to reach the dual-carbon goal is an urgent problem to be solved. In this study, we consider using blockchain technology to include the new energy vehicle industry in carbon trading, analyze the strategic choices of the government, automobile manufacturers, and consumers from the perspective of evolutionary games, and use MATLAB 2017b to conduct simulation analysis. The results show that (1) the implementation of a carbon trading mechanism by the government is favorable to automobile manufacturers and consumers in choosing new energy vehicles, but it is greatly influenced by the costs of technology implementation; (2) the government can induce consumers and automakers to choose new energy vehicles through total control and initial carbon quotas; and (3) the additional investment costs of automobile manufacturers will affect their willingness to produce new energy vehicles, and the government can adjust the existing “double points” policy to encourage automobile manufacturers to choose to produce new energy vehicles.

Suggested Citation

  • Wenhui Zhao & Yimeng Liu & Jiansheng Hou & Lifang Liu, 2023. "Impact of Carbon Trading Mechanism Considering Blockchain Technology on the Evolution of New Energy Vehicle Industry in the Post-Subsidy Era," Sustainability, MDPI, vol. 15(17), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:13190-:d:1231410
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    References listed on IDEAS

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    1. Chen, Zhenni & Du, Huibin & Li, Jianglong & Southworth, Frank & Ma, Shoufeng, 2019. "Achieving low-carbon urban passenger transport in China: Insights from the heterogeneous rebound effect," Energy Economics, Elsevier, vol. 81(C), pages 1029-1041.
    2. Liao, Dongsheng & Tan, Binbin, 2023. "An evolutionary game analysis of new energy vehicles promotion considering carbon tax in post-subsidy era," Energy, Elsevier, vol. 264(C).
    3. Liu, Yajie & Dong, Feng, 2022. "What are the roles of consumers, automobile production enterprises, and the government in the process of banning gasoline vehicles? Evidence from a tripartite evolutionary game model," Energy, Elsevier, vol. 238(PC).
    4. Fan, Ruguo & Bao, Xuguang & Du, Kang & Wang, Yuanyuan & Wang, Yitong, 2022. "The effect of government policies and consumer green preferences on the R&D diffusion of new energy vehicles: A perspective of complex network games," Energy, Elsevier, vol. 254(PA).
    5. Chen, Rongkai & Fan, Ruguo & Wang, Dongxue & Yao, Qianyi, 2023. "Effects of multiple incentives on electric vehicle charging infrastructure deployment in China: An evolutionary analysis in complex network," Energy, Elsevier, vol. 264(C).
    6. Li, Zhitang & Zhang, Cuihua & Xu, Henry & Lyu, Ruxia, 2023. "The optimal vehicle product line strategy considering product information disclosure under government carbon regulation," Omega, Elsevier, vol. 119(C).
    7. Nie, Qingyun & Zhang, Lihui & Li, Songrui, 2022. "How can personal carbon trading be applied in electric vehicle subsidies? A Stackelberg game method in private vehicles," Applied Energy, Elsevier, vol. 313(C).
    8. Zhao, Dan & Ji, Shou-feng & Wang, He-ping & Jiang, Li-wen, 2021. "How do government subsidies promote new energy vehicle diffusion in the complex network context? A three-stage evolutionary game model," Energy, Elsevier, vol. 230(C).
    9. Li, Kun & Dong, Feng, 2022. "Government strategy for banning gasoline vehicles: Evidence from tripartite evolutionary game," Energy, Elsevier, vol. 254(PA).
    10. Liu, Chang & Liu, Yuan & Zhang, Dayong & Xie, Chunping, 2022. "The capital market responses to new energy vehicle (NEV) subsidies: An event study on China," Energy Economics, Elsevier, vol. 105(C).
    11. Nie, Qingyun & Zhang, Lihui & Tong, Zihao & Hubacek, Klaus, 2022. "Strategies for applying carbon trading to the new energy vehicle market in China: An improved evolutionary game analysis for the bus industry," Energy, Elsevier, vol. 259(C).
    12. Sheldon, Tamara L. & Dua, Rubal, 2019. "Measuring the cost-effectiveness of electric vehicle subsidies," Energy Economics, Elsevier, vol. 84(C).
    13. Diao, Qinghua & Sun, Wei & Yuan, Xinmei & Li, Lili & Zheng, Zhi, 2016. "Life-cycle private-cost-based competitiveness analysis of electric vehicles in China considering the intangible cost of traffic policies," Applied Energy, Elsevier, vol. 178(C), pages 567-578.
    14. Zhu, Lijing & Wang, Peize & Zhang, Qi, 2019. "Indirect network effects in China’s electric vehicle diffusion under phasing out subsidies," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    15. Wang, Zhongcheng & Li, Xinyue & Xue, Xinhong & Liu, Yahuan, 2022. "More government subsidies, more green innovation? The evidence from Chinese new energy vehicle enterprises," Renewable Energy, Elsevier, vol. 197(C), pages 11-21.
    16. Ji, Shou-feng & Zhao, Dan & Luo, Rong-juan, 2019. "Evolutionary game analysis on local governments and manufacturers' behavioral strategies: Impact of phasing out subsidies for new energy vehicles," Energy, Elsevier, vol. 189(C).
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    3. Xia Wenhui & Xiao Tong & Xia Qianyin & Li Yuesi, 2025. "An Applied Study of an Electric Vehicle Revenue Game Model Considering Graphene Battery Materials," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(3), pages 1424-1436, April.

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