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The Art of Balancing Price and Plug: Developing a Theoretical Model for Dynamic Pricing in the Electric Vehicle Market

Author

Listed:
  • Zhining Jia

    (Puxi Branch, Bank of Shanghai, Shanghai 200231, China)

  • Qi Chen

    (School of Economics and Management, Shanghai Open University, Shanghai 200433, China)

  • Qi Xu

    (Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China)

Abstract

This study presents a novel approach to understanding the complex dynamics of the electric vehicle (EV) market through the lens of differential game theory. We developed a comprehensive model that captures the strategic interactions between EV manufacturers and charging network operators, while incorporating the effects of consumer behavior, market uncertainties, and reference price effects. Using differential game theory, we examined the impact of reference price effects and the charging network’s influence on pricing strategies, focusing on three distinct approaches: basic pricing, static pricing considering reference price effects, and dynamic pricing strategies. Our model offers new insights into consumer behavior and price expectations in the rapidly evolving EV market. The key findings reveal that under static or dynamic pricing strategies, the optimal pricing for EV manufacturers is positively correlated with the initial reference price. When the initial reference price is high (low), the optimal pricing strategy resembles skimming pricing (penetration pricing). As the effort level of charging network operators increases and their influence on consumers’ purchase decisions grows stronger, EV manufacturers tend to set higher prices. Notably, while dynamic pricing strategies can optimize EV manufacturers’ profits, the profits of charging network operators may decrease compared with static pricing strategies. This integrated approach significantly contributes to the field by bridging gaps among market dynamics, pricing strategies, and the infrastructure’s development in the context of electric mobility, providing a comprehensive framework for understanding and optimizing the EV ecosystem. Ultimately, this study advances sustainable business models that balance profitability, consumer behavior, and the infrastructure’s growth in the rapidly evolving EV market.

Suggested Citation

  • Zhining Jia & Qi Chen & Qi Xu, 2024. "The Art of Balancing Price and Plug: Developing a Theoretical Model for Dynamic Pricing in the Electric Vehicle Market," Sustainability, MDPI, vol. 16(21), pages 1-23, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9325-:d:1507618
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    References listed on IDEAS

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    1. Lin, Runzi & Xu, Zhenhui & Huang, Xiaoliang & Gao, Jinwu & Chen, Hong & Shen, Tielong, 2022. "Optimal scheduling management of the parking lot and decentralized charging of electric vehicles based on Mean Field Game," Applied Energy, Elsevier, vol. 328(C).
    2. Ramteen Sioshansi, 2012. "OR Forum---Modeling the Impacts of Electricity Tariffs on Plug-In Hybrid Electric Vehicle Charging, Costs, and Emissions," Operations Research, INFORMS, vol. 60(3), pages 506-516, June.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. Christoph M. Flath & Jens P. Ilg & Sebastian Gottwalt & Hartmut Schmeck & Christof Weinhardt, 2014. "Improving Electric Vehicle Charging Coordination Through Area Pricing," Transportation Science, INFORMS, vol. 48(4), pages 619-634, November.
    5. Gadi Fibich & Arieh Gavious & Oded Lowengart, 2003. "Explicit Solutions of Optimization Models and Differential Games with Nonsmooth (Asymmetric) Reference-Price Effects," Operations Research, INFORMS, vol. 51(5), pages 721-734, October.
    6. Ioana Popescu & Yaozhong Wu, 2007. "Dynamic Pricing Strategies with Reference Effects," Operations Research, INFORMS, vol. 55(3), pages 413-429, June.
    7. Barman, Pranjal & Dutta, Lachit, 2024. "Charging infrastructure planning for transportation electrification in India: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    8. Katalin Springel, 2021. "Network Externality and Subsidy Structure in Two-Sided Markets: Evidence from Electric Vehicle Incentives," American Economic Journal: Economic Policy, American Economic Association, vol. 13(4), pages 393-432, November.
    9. Adedamola Adepetu & Srinivasan Keshav, 2017. "The relative importance of price and driving range on electric vehicle adoption: Los Angeles case study," Transportation, Springer, vol. 44(2), pages 353-373, March.
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