IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i23p8806-d980619.html
   My bibliography  Save this article

Evolutionary Game of Actors in China’s Electric Vehicle Charging Infrastructure Industry

Author

Listed:
  • Mu Li

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Yingqi Liu

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Weizhong Yue

    (Beijing Municipal Commission of Housing and Urban-Rural Development, Beijing 101160, China)

Abstract

China proposed a development direction of “new infrastructure” in 2020, due to the ongoing scientific and technological revolution and industrial transformation. The charging station industry is one of the seven industries of the “new infrastructure”. Hence, it is of great importance to study China’s electric vehicle charging infrastructure industry. Based on game theory, this study analyzes the game strategies for the evolution of actors in China’s electric vehicle charging infrastructure industry. Firstly, the Chinese government has classified the industry according to the subsidy for charging piles and battery swapping stations. Then, the government, operators, and consumers constructed an evolutionary game model. The results show that: (1) under the investment subsidy mode, the purchase cost that consumers invest in purchasing traditional fuel-consuming vehicles has a positive impact on the operator’s production enthusiasm. In addition, the government’s subsidy amount has a positive impact on consumers’ decision to purchase battery-swappable electric vehicles; and (2) under the operational subsidy mode, due to the government’s strong supervision of the industry, there is a positive correlation between the word-of-mouth effect and the consumer’s decision to buy rechargeable electric vehicles.

Suggested Citation

  • Mu Li & Yingqi Liu & Weizhong Yue, 2022. "Evolutionary Game of Actors in China’s Electric Vehicle Charging Infrastructure Industry," Energies, MDPI, vol. 15(23), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8806-:d:980619
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/23/8806/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/23/8806/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shanjun Li & Lang Tong & Jianwei Xing & Yiyi Zhou, 2017. "The Market for Electric Vehicles: Indirect Network Effects and Policy Design," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(1), pages 89-133.
    2. Jinshi Cheng & Jiali Wang & Bengang Gong, 2020. "Game-Theoretic Analysis of Price and Quantity Decisions for Electric Vehicle Supply Chain Under Subsidy Reduction," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1185-1208, April.
    3. Baumgarte, Felix & Kaiser, Matthias & Keller, Robert, 2021. "Policy support measures for widespread expansion of fast charging infrastructure for electric vehicles," Energy Policy, Elsevier, vol. 156(C).
    4. Stergios Statharas & Yannis Moysoglou & Pelopidas Siskos & Pantelis Capros, 2021. "Simulating the Evolution of Business Models for Electricity Recharging Infrastructure Development by 2030: A Case Study for Greece," Energies, MDPI, vol. 14(9), pages 1-24, April.
    5. Wang, Yue & Shi, Jianmai & Wang, Rui & Liu, Zhong & Wang, Ling, 2018. "Siting and sizing of fast charging stations in highway network with budget constraint," Applied Energy, Elsevier, vol. 228(C), pages 1255-1271.
    6. Sadeghi-Barzani, Payam & Rajabi-Ghahnavieh, Abbas & Kazemi-Karegar, Hosein, 2014. "Optimal fast charging station placing and sizing," Applied Energy, Elsevier, vol. 125(C), pages 289-299.
    7. Majidpour, Mostafa & Qiu, Charlie & Chu, Peter & Pota, Hemanshu R. & Gadh, Rajit, 2016. "Forecasting the EV charging load based on customer profile or station measurement?," Applied Energy, Elsevier, vol. 163(C), pages 134-141.
    8. Zhu, Zhi-Hong & Gao, Zi-You & Zheng, Jian-Feng & Du, Hao-Ming, 2016. "Charging station location problem of plug-in electric vehicles," Journal of Transport Geography, Elsevier, vol. 52(C), pages 11-22.
    9. Arias, Mariz B. & Kim, Myungchin & Bae, Sungwoo, 2017. "Prediction of electric vehicle charging-power demand in realistic urban traffic networks," Applied Energy, Elsevier, vol. 195(C), pages 738-753.
    10. Liu, Yingqi & Kokko, Ari, 2013. "Who does what in China’s new energy vehicle industry?," Energy Policy, Elsevier, vol. 57(C), pages 21-29.
    11. Kangda Chen & Fuquan Zhao & Han Hao & Zongwei Liu, 2018. "Synergistic Impacts of China’s Subsidy Policy and New Energy Vehicle Credit Regulation on the Technological Development of Battery Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-19, November.
    12. Chen, Xiao & Wu, Tian & Zheng, Rui & Guo, Xiaoxian, 2018. "How vehicle market is segmented and influenced by subsidy policy: A theoretical study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 776-782.
    13. Hongxia Sun & Yao Wan & Huirong Lv, 2020. "System Dynamics Model for the Evolutionary Behaviour of Government Enterprises and Consumers in China’s New Energy Vehicle Market," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    14. Ahman, Max, 2006. "Government policy and the development of electric vehicles in Japan," Energy Policy, Elsevier, vol. 34(4), pages 433-443, March.
    15. Gu, Xiaoyu & Ieromonachou, Petros & Zhou, Li, 2019. "Subsidising an electric vehicle supply chain with imperfect information," International Journal of Production Economics, Elsevier, vol. 211(C), pages 82-97.
    16. Schroeder, Andreas & Traber, Thure, 2012. "The economics of fast charging infrastructure for electric vehicles," Energy Policy, Elsevier, vol. 43(C), pages 136-144.
    17. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
    18. Yiyi Zhou & Shanjun Li, 2018. "Technology Adoption and Critical Mass: The Case of the U.S. Electric Vehicle Market," Journal of Industrial Economics, Wiley Blackwell, vol. 66(2), pages 423-480, June.
    19. 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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin, Haiyang & Bian, Caiyun & Wang, Yu & Li, Hailong & Sun, Qie & Wallin, Fredrik, 2022. "Optimal planning of intra-city public charging stations," Energy, Elsevier, vol. 238(PC).
    2. Zhu, Lijing & Zhang, Qi & Lu, Huihui & Li, Hailong & Li, Yan & McLellan, Benjamin & Pan, Xunzhang, 2017. "Study on crowdfunding’s promoting effect on the expansion of electric vehicle charging piles based on game theory analysis," Applied Energy, Elsevier, vol. 196(C), pages 238-248.
    3. Motoaki, Yutaka & Yi, Wenqi & Salisbury, Shawn, 2018. "Empirical analysis of electric vehicle fast charging under cold temperatures," Energy Policy, Elsevier, vol. 122(C), pages 162-168.
    4. Kim, Hyunjung & Kim, Dae-Wook & Kim, Man-Keun, 2022. "Economics of charging infrastructure for electric vehicles in Korea," Energy Policy, Elsevier, vol. 164(C).
    5. Buzna, Luboš & De Falco, Pasquale & Ferruzzi, Gabriella & Khormali, Shahab & Proto, Daniela & Refa, Nazir & Straka, Milan & van der Poel, Gijs, 2021. "An ensemble methodology for hierarchical probabilistic electric vehicle load forecasting at regular charging stations," Applied Energy, Elsevier, vol. 283(C).
    6. Zhou, Guangyou & Zhu, Zhiwei & Luo, Sumei, 2022. "Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm," Energy, Elsevier, vol. 247(C).
    7. Wang, Yue & Shi, Jianmai & Wang, Rui & Liu, Zhong & Wang, Ling, 2018. "Siting and sizing of fast charging stations in highway network with budget constraint," Applied Energy, Elsevier, vol. 228(C), pages 1255-1271.
    8. Yue Wang & Zhong Liu & Jianmai Shi & Guohua Wu & Rui Wang, 2018. "Joint Optimal Policy for Subsidy on Electric Vehicles and Infrastructure Construction in Highway Network," Energies, MDPI, vol. 11(9), pages 1-21, September.
    9. Wang, Hua & Zhao, De & Cai, Yutong & Meng, Qiang & Ong, Ghim Ping, 2021. "Taxi trajectory data based fast-charging facility planning for urban electric taxi systems," Applied Energy, Elsevier, vol. 286(C).
    10. Yan, Jie & Zhang, Jing & Liu, Yongqian & Lv, Guoliang & Han, Shuang & Alfonzo, Ian Emmanuel Gonzalez, 2020. "EV charging load simulation and forecasting considering traffic jam and weather to support the integration of renewables and EVs," Renewable Energy, Elsevier, vol. 159(C), pages 623-641.
    11. Shubham Mishra & Shrey Verma & Subhankar Chowdhury & Ambar Gaur & Subhashree Mohapatra & Gaurav Dwivedi & Puneet Verma, 2021. "A Comprehensive Review on Developments in Electric Vehicle Charging Station Infrastructure and Present Scenario of India," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    12. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
    13. Munseok Chang & Sungwoo Bae & Gilhwan Cha & Jaehyun Yoo, 2021. "Aggregated Electric Vehicle Fast-Charging Power Demand Analysis and Forecast Based on LSTM Neural Network," Sustainability, MDPI, vol. 13(24), pages 1-17, December.
    14. Yunsun Kim & Sahm Kim, 2021. "Forecasting Charging Demand of Electric Vehicles Using Time-Series Models," Energies, MDPI, vol. 14(5), pages 1-16, March.
    15. Du, Jiuyu & Ouyang, Danhua, 2017. "Progress of Chinese electric vehicles industrialization in 2015: A review," Applied Energy, Elsevier, vol. 188(C), pages 529-546.
    16. Byungsung Lee & Haesung Lee & Hyun Ahn, 2020. "Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation," Energies, MDPI, vol. 13(18), pages 1-15, September.
    17. Neaimeh, Myriam & Salisbury, Shawn D. & Hill, Graeme A. & Blythe, Philip T. & Scoffield, Don R. & Francfort, James E., 2017. "Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles," Energy Policy, Elsevier, vol. 108(C), pages 474-486.
    18. Jacobus Nel & Roula Inglesi-Lotz, 2022. "Electric Vehicles Market and Policy Conditions: Identifying South African Policy ``Potholes"," Working Papers 202257, University of Pretoria, Department of Economics.
    19. Arlt, Marie-Louise & Astier, Nicolas, 2023. "Do retail businesses have efficient incentives to invest in public charging stations for electric vehicles?," Energy Economics, Elsevier, vol. 124(C).
    20. Shanjun Li & Xianglei Zhu & Yiding Ma & Fan Zhang & Hui Zhou, 2022. "The Role of Government in the Market for Electric Vehicles: Evidence from China," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(2), pages 450-485, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8806-:d:980619. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.