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Subsidizing mass adoption of electric vehicles with a risk-averse manufacturer

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  • Deng, Shiming
  • Li, Wei
  • Wang, Tian

Abstract

This paper explores how a risk-averse electric vehicle (EV) manufacturer responds to the government’s two types of subsidy mechanism: purchase subsidy for consumers and production subsidy for the EV manufacturer. This study develops a Stackelberg framework: the government, as the leader, designs the subsidy policy to reach the EV adoption target while the risk-averse EV manufacturer, as the follower, determines the production quantity and selling price. Using an analytical model that focuses on an additive demand function, we generalize closed-form solutions and present managerial insights. Results show that the risk aversion decreases the production quantity and increases consumer surplus, however, the manufacturer’s profit does not necessarily decrease with risk aversion because the production subsidy improves profit effectively. For the government, demand uncertainty costs the government more. With regard to consumer surplus, consumers tend to benefit under the condition of demand uncertainty; however, the shortage cost hurts them. Comparing the EV manufacturer’s profit, the shortage cost and demand uncertainty decrease profit. More importantly, we assess the different effects of the two subsidies by numerical experiments. Taken the government’s subsidy expenditure and social welfare as the performance metrics, the purchase subsidy is more effective with a less risk-averse manufacturer while the production subsidy is more effective with a more risk-averse manufacturer. Therefore, this paper recommends that the government not ignore the effects of the EV manufacturer’s risk aversion and demand uncertainty when designing subsidy policies.

Suggested Citation

  • Deng, Shiming & Li, Wei & Wang, Tian, 2020. "Subsidizing mass adoption of electric vehicles with a risk-averse manufacturer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
  • Handle: RePEc:eee:phsmap:v:547:y:2020:i:c:s0378437120301576
    DOI: 10.1016/j.physa.2020.124408
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    as
    1. Yu Sang Chang & Powell Niland, 1967. "A Model for Measuring Stock Depletion Costs," Operations Research, INFORMS, vol. 15(3), pages 427-447, June.
    2. Ho-Yin Mak & Ying Rong & Zuo-Jun Max Shen, 2013. "Infrastructure Planning for Electric Vehicles with Battery Swapping," Management Science, INFORMS, vol. 59(7), pages 1557-1575, July.
    3. Youhua (Frank) Chen & Minghui Xu & Zhe George Zhang, 2009. "Technical Note---A Risk-Averse Newsvendor Model Under the CVaR Criterion," Operations Research, INFORMS, vol. 57(4), pages 1040-1044, August.
    4. Xu, Xinsheng & Chan, Chi Kin & Langevin, Andre, 2018. "Coping with risk management and fill rate in the loss-averse newsvendor model," International Journal of Production Economics, Elsevier, vol. 195(C), pages 296-310.
    5. Wu, Meng & Zhu, Stuart X. & Teunter, Ruud H., 2014. "A risk-averse competitive newsvendor problem under the CVaR criterion," International Journal of Production Economics, Elsevier, vol. 156(C), pages 13-23.
    6. Gotoh, Jun-ya & Takano, Yuichi, 2007. "Newsvendor solutions via conditional value-at-risk minimization," European Journal of Operational Research, Elsevier, vol. 179(1), pages 80-96, May.
    7. Wu, Jun & Li, Jian & Wang, Shouyang & Cheng, T.C.E., 2009. "Mean-variance analysis of the newsvendor model with stockout cost," Omega, Elsevier, vol. 37(3), pages 724-730, June.
    8. Qin, Yan & Wang, Ruoxuan & Vakharia, Asoo J. & Chen, Yuwen & Seref, Michelle M.H., 2011. "The newsvendor problem: Review and directions for future research," European Journal of Operational Research, Elsevier, vol. 213(2), pages 361-374, September.
    9. Jian Huang & Mingming Leng & Liping Liang & Jian Liu, 2013. "Promoting electric automobiles: supply chain analysis under a government’s subsidy incentive scheme," IISE Transactions, Taylor & Francis Journals, vol. 45(8), pages 826-844.
    10. Luo, Chunlin & Leng, Mingming & Huang, Jian & Liang, Liping, 2014. "Supply chain analysis under a price-discount incentive scheme for electric vehicles," European Journal of Operational Research, Elsevier, vol. 235(1), pages 329-333.
    11. Nicholas C. Petruzzi & Maqbool Dada, 1999. "Pricing and the Newsvendor Problem: A Review with Extensions," Operations Research, INFORMS, vol. 47(2), pages 183-194, April.
    12. Michael Salinger & Miguel Ampudia, 2011. "Simple Economics of the Price-Setting Newsvendor Problem," Management Science, INFORMS, vol. 57(11), pages 1996-1998, November.
    13. Louis Eeckhoudt & Christian Gollier & Harris Schlesinger, 1995. "The Risk-Averse (and Prudent) Newsboy," Management Science, INFORMS, vol. 41(5), pages 786-794, May.
    14. Panos Kouvelis & Rong Li, 2019. "Integrated Risk Management for Newsvendors with Value-at-Risk Constraints," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 816-832, October.
    15. 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.
    16. 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.
    17. Breetz, Hanna L. & Salon, Deborah, 2018. "Do electric vehicles need subsidies? Ownership costs for conventional, hybrid, and electric vehicles in 14 U.S. cities," Energy Policy, Elsevier, vol. 120(C), pages 238-249.
    18. Jammernegg, Werner & Kischka, Peter, 2013. "The price-setting newsvendor with service and loss constraints," Omega, Elsevier, vol. 41(2), pages 326-335.
    19. Maurice E. Schweitzer & Gérard P. Cachon, 2000. "Decision Bias in the Newsvendor Problem with a Known Demand Distribution: Experimental Evidence," Management Science, INFORMS, vol. 46(3), pages 404-420, March.
    20. Maxime C. Cohen & Ruben Lobel & Georgia Perakis, 2016. "The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption," Management Science, INFORMS, vol. 62(5), pages 1235-1258, May.
    21. Lau, Amy Hing Ling & Lau, Hon-Shiang, 2003. "Effects of a demand-curve's shape on the optimal solutions of a multi-echelon inventory/pricing model," European Journal of Operational Research, Elsevier, vol. 147(3), pages 530-548, June.
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    Cited by:

    1. Gao, Yongling & Leng, Mingming & Zhang, Yaping & Liang, Liping, 2022. "Incentivizing the adoption of electric vehicles in city logistics: Pricing, driving range, and usage decisions under time window policies," International Journal of Production Economics, Elsevier, vol. 245(C).
    2. Cheng, Fei & Chen, Tong & Chen, Qiao, 2022. "Cost-reducing strategy or emission-reducing strategy? The choice of low-carbon decisions under price threshold subsidy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    3. Falbo, Paolo & Pelizzari, Cristian & Rizzini, Giorgio, 2022. "Optimal incentive for electric vehicle adoption," Energy Economics, Elsevier, vol. 114(C).
    4. 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).

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