Game-Theoretic Analysis of Price and Quantity Decisions for Electric Vehicle Supply Chain Under Subsidy Reduction

  • Jinshi Cheng
  • Jiali Wang
  • Bengang GongEmail author


To avoid the negative effects of electric vehicle (EV) subsidies, the Chinese government has launched an EV subsidy reduction policy, resulting in market uncertainty for EV supply chains. We study the optimal decisions of EV manufacturers and EV sellers by considering the subsidy reduction policy and stochastic demand of the EV market. We develop a newsvendor game model of a two-stage EV supply chain, and analyze how four factors—the degree of subsidy decline, the level of research and development (R&D), market demand, and inventory—affect the two parties’ optimal decisions under centralized and decentralized decision making. Our key results show that: (1) The EV subsidy reduction will not have a significant negative impact on the EV market; (2) The key factors for stimulating the development of the EV market are the R&D level and market demand for EVs, and EV sales are the major contributor to increased EV supply chain profits; (3) Improvement in EV market demand will increase market competition and market vitality; (4) The two decision maker-framework under centralized decision making is more advantageous to the popularization and development of EVs. When centralized decision making is difficult, a coordinated strategy under decentralized decision making can yield the same results as centralized decision making.


Supply chain management Electric vehicle Newsvendor game model Subsidy reduction 

JEL Classification

D41 D58 E61 



The authors are grateful for the generous comments and guidance provided by many experts. This research is supported by the Natural Sciences Foundation (NSF) of China (Grant Nos. 71671001, 71771002) and Natural Science Foundation of Anhui Province of China (Grant No. 1808085MG214).


  1. Du, J., & Ouyang, D. (2017). Progress of Chinese electric vehicles industrialization in 2015: A review. Applied Energy, 188, 529–546.CrossRefGoogle Scholar
  2. Fan, R., & Dong, L. (2018). The dynamic analysis and simulation of government subsidy strategies in low-carbon diffusion considering the behavior of heterogeneous agents. Energy Policy, 117, 252–262.CrossRefGoogle Scholar
  3. Han, H., Ou, X., Du, J., Wang, H., & Ouyang, M. (2014). China’s electric vehicle subsidy scheme: Rationale and impacts. Energy Policy, 73(C), 722–732.Google Scholar
  4. Holtsmark, B., & Skonhoft, A. (2014). The Norwegian support and subsidy policy of electric cars. Should it be adopted by other countries? Environmental Science and Policy, 42, 160–168.CrossRefGoogle Scholar
  5. Hua, C., & Ming, X. (2013). greenhouse gas implications of fleet electrification based on big data-informed individual travel patterns. Environmental Science and Technology, 47(16), 9035–9043.CrossRefGoogle Scholar
  6. Jones, L. R., Cherry, C. R., Vu, T. A., & Nguyen, Q. N. (2013). The effect of incentives and technology on the adoption of electric motorcycles: A stated choice experiment in Vietnam. Transportation Research Part A Policy and Practice, 57(11), 1–11.CrossRefGoogle Scholar
  7. Krause, R. M., Carley, S. R., Lane, B. W., & Graham, J. D. (2013). Perception and reality: Public knowledge of plug-in electric vehicles in 21 U.S. cities. Energy Policy, 63(3), 433–440.CrossRefGoogle Scholar
  8. Langbroek, J. H. M., Franklin, J. P., & Susilo, Y. O. (2016). The effect of policy incentives on electric vehicle adoption. Energy Policy, 94, 94–103.CrossRefGoogle Scholar
  9. Liu, Y. (2014). Household demand and willingness to pay for hybrid vehicles. Energy Economics, 44, 191–197.CrossRefGoogle Scholar
  10. Luo, C., Leng, M., Huang, J., & Liang, L. (2014). Supply chain analysis under a price-discount incentive scheme for electric vehicles. European Journal of Operational Research, 235(1), 329–333.CrossRefGoogle Scholar
  11. Nie, Y., Ghamami, M., Zockaie, A., & Xiao, F. (2016). Optimization of incentive polices for plug-in electric vehicles. Transportation Research Part B Methodological, 84, 103–123.CrossRefGoogle Scholar
  12. Noori, M., & Tatari, O. (2016). Development of an agent-based model for regional market penetration projections of electric vehicles in the United States. Energy, 96, 215–230.CrossRefGoogle Scholar
  13. Robledo, C. B., Oldenbroek, V., Abbruzzese, F., & Wijk, A. J. M. V. (2018). Integrating a hydrogen fuel cell electric vehicle with vehicle-to-grid technology, photovoltaic power and a residential building. Applied Energy, 215, 615–629.CrossRefGoogle Scholar
  14. Song, M.-L., Fisher, R., Wang, J.-L., & Cui, L.-B. (2016). Environmental performance evaluation with big data: Theories and methods. Annals of Operations Research. Scholar
  15. Song, M., & Wang, S. (2018). Measuring environment-biased technological progress considering energy saving and emission reduction. Process Safety and Environmental Protection, 116, 745–753.CrossRefGoogle Scholar
  16. Tian, Y., Govindan, K., & Zhu, Q. (2014). A system dynamics model based on evolutionary game theory for green supply chain management diffusion among Chinese manufacturers. Journal of Cleaner Production, 80(7), 96–105.CrossRefGoogle Scholar
  17. Wang, Y., Sperling, D., Tal, G., & Fang, H. (2017). China’s electric car surge. Energy Policy, 102, 486–490.CrossRefGoogle Scholar
  18. Zhang, X. (2014). Reference-dependent electric vehicle production strategy considering subsidies and consumer trade-offs. Energy Policy, 67(2), 422–430.CrossRefGoogle Scholar
  19. Zhang, X., Liang, Y., & Liu, W. (2017). Pricing model for the charging of electric vehicles based on system dynamics in Beijing. Energy, 119, 218–234.CrossRefGoogle Scholar
  20. Zheng, X., Lin, H., Liu, Z., Li, D., Llopis-Albert, C., & Zeng, S. (2018). Manufacturing decisions and government subsidies for electric vehicles in China: A maximal social welfare perspective. Sustainability, 10(3), 672.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Management EngineeringAnhui Polytechnic UniversityWuhuPeople’s Republic of China

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