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A key stakeholder-based financial subsidy stimulation for Chinese EV industrialization: A system dynamics simulation

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  • Lu, Chao
  • Liu, Hu-Chen
  • Tao, Jie
  • Rong, Ke
  • Hsieh, Ying-Che

Abstract

Successful policy-making for an emerging industry relies on two key factors: adopting a scientific perspective and accurately forecasting the policy's potential effects. By combining Mitchell's score-based approach and expert grading method, this paper identifies the key stakeholders of the Chinese electric vehicle (EV) industry, and proposes a key stakeholder-based policy research framework (G-MIC: Government — Manufacturers, Infrastructure, Consumers). Furthermore, a system dynamics (SD) model is outlined, focusing on financial subsidy (FS) policy and the three groups of programs that are set to simulate level of FS, FS allocation, and the demand for realizing the CAO (Civilian Auto Ownership) goal of the Chinese EV industry by 2020. The findings reveal that the following show that a key stakeholder perspective is a better approach to policy research; the SD model constructed under the G-MIC framework extends the methodology of SD; and a “bottom-up” policy-making path is more likely to improve policy outcomes.

Suggested Citation

  • Lu, Chao & Liu, Hu-Chen & Tao, Jie & Rong, Ke & Hsieh, Ying-Che, 2017. "A key stakeholder-based financial subsidy stimulation for Chinese EV industrialization: A system dynamics simulation," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 1-14.
    • Handle: RePEc:eee:tefoso:v:118:y:2017:i:c:p:1-14
    DOI: 10.1016/j.techfore.2017.01.022
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    Cited by:

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    6. Wang, Ning & Shang, Kai & Duan, Yan & Qin, Dandan, 2023. "Carbon quota allocation modeling framework in the automotive industry based on repeated game theory: A case study of ten Chinese automotive enterprises," Energy, Elsevier, vol. 279(C).
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    8. Kong, Deyang & Xia, Quhong & Xue, Yixi & Zhao, Xin, 2020. "Effects of multi policies on electric vehicle diffusion under subsidy policy abolishment in China: A multi-actor perspective," Applied Energy, Elsevier, vol. 266(C).
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    10. Qingyou Yan & Guangyu Qin & Meijuan Zhang & Bowen Xiao, 2019. "Research on Real Purchasing Behavior Analysis of Electric Cars in Beijing Based on Structural Equation Modeling and Multinomial Logit Model," Sustainability, MDPI, vol. 11(20), pages 1-15, October.
    11. Zihan Zhang & Junkang Song & Wanjiang Wang, 2023. "Study on the Behavior Strategy of the Subject of Low-Carbon Retrofit of Residential Buildings Based on Tripartite Evolutionary Game," Sustainability, MDPI, vol. 15(9), pages 1-25, May.
    12. Wang, Ning & Tang, Linhao & Zhang, Wenjian & Guo, Jiahui, 2019. "How to face the challenges caused by the abolishment of subsidies for electric vehicles in China?," Energy, Elsevier, vol. 166(C), pages 359-372.
    13. Jianlong Wu & Zhongji Yang & Xiaobo Hu & Hongqi Wang & Jing Huang, 2018. "Exploring Driving Forces of Sustainable Development of China’s New Energy Vehicle Industry: An Analysis from the Perspective of an Innovation Ecosystem," Sustainability, MDPI, vol. 10(12), pages 1-24, December.
    14. Liu, Hu-Chen & You, Xiao-Yue & Xue, Yi-Xi & Luan, Xue, 2017. "Exploring critical factors influencing the diffusion of electric vehicles in China: A multi-stakeholder perspective," Research in Transportation Economics, Elsevier, vol. 66(C), pages 46-58.
    15. Zhang, Ruining & Ai, Xianneng & Li, Hui, 2023. "How to design subsidy policies for clean energy projects? A study on “coal-to-gas” project in China," Resources Policy, Elsevier, vol. 85(PB).
    16. Yanyan Liu & Ying Cheng & Wei Liu, 2018. "Understanding Gatekeeping Transformation in the Chinese EV Industry: An Exploratory Study of the Focal Firms' Cross-industrial Interactions," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 16(3-B), pages 485-503.
    17. Li, Jingjing & Nian, Victor & Jiao, Jianling, 2022. "Diffusion and benefits evaluation of electric vehicles under policy interventions based on a multiagent system dynamics model," Applied Energy, Elsevier, vol. 309(C).
    18. Li, Hui & Zhang, Ruining & Ai, Xianneng, 2022. "Cost estimation of “coal-to-gas” project: Government and residents’ perspectives," Energy Policy, Elsevier, vol. 167(C).
    19. Guzzo, Daniel & Rodrigues, Vinicius Picanço & Mascarenhas, Janaina, 2021. "A systems representation of the Circular Economy: Transition scenarios in the electrical and electronic equipment (EEE) industry," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    20. Li, Yina & Liang, Chenchen & Ye, Fei & Zhao, Xiande, 2023. "Designing government subsidy schemes to promote the electric vehicle industry: A system dynamics model perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    21. Ye, Rui-Ke & Gao, Zhuang-Fei & Fang, Kai & Liu, Kang-Li & Chen, Jia-Wei, 2021. "Moving from subsidy stimulation to endogenous development: A system dynamics analysis of China's NEVs in the post-subsidy era," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    22. Zhu, Lin & Cunningham, Scott W., 2022. "Unveiling the knowledge structure of technological forecasting and social change (1969–2020) through an NMF-based hierarchical topic model," Technological Forecasting and Social Change, Elsevier, vol. 174(C).

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