IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0283320.html
   My bibliography  Save this article

Optimal number of charging station and pricing strategy for the electric vehicle with component commonality considering consumer range anxiety

Author

Listed:
  • Wenchao Yu
  • Linghong Zhang
  • Rui Lu
  • Junjie Ma

Abstract

The battery driving mileage on a single charge and convenience of the charging stations affect Electric Vehicle’s (EV) demand. This paper studies the optimal number of charging stations and EV’s price strategy considering different component commonality configurations. Assume the EV manufacturer provides two types of EV and the two EVs have the same battery configuration (battery as a common part) or the same naked vehicle–EV without batteries (naked vehicle as a common part). And the common part could be configured with low or high quality. We discuss four scenarios with different common parts and different quality levels. For each scenario, we present the optimal number of the charging stations and EV prices. Then we compare the optimal solutions and manufacturer’s profits in above four scenarios with numerical simulation and give some managerial insights. Our analysis reveals that (1) consumers’ range anxiety towards battery will affect manufacturer’s product configuration strategy, EVs’ prices and demands. (2) large consumers’ sensitivity towards charging station will corresponding to more charging station, high EV prices and demands. If consumers are very concerned about the charging convenience, high-end electric vehicles need to be launched first, then as customers’ anxiety about charging decreases, the low quality EV could be developed and diffused. (3) the unit product cost reduction caused by the commonality may increase or decrease the EVs’ prices, which depends on the relationship between the demand increment incurred by one more charging station and the cost coefficient of building the charging station. (4) The low quality naked vehicle as common component will increase both the number of the charging stations and the demand and the manufacturer is more likely to obtain high profits. (5) the cost saving coefficient of battery common parts has greater influence on the selection of commonality. When consumers’ range anxiety towards battery is very high, manufacturers should choose low-quality naked vehicles or high-quality battery as common components.

Suggested Citation

  • Wenchao Yu & Linghong Zhang & Rui Lu & Junjie Ma, 2023. "Optimal number of charging station and pricing strategy for the electric vehicle with component commonality considering consumer range anxiety," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-21, May.
    • Handle: RePEc:plo:pone00:0283320
    DOI: 10.1371/journal.pone.0283320
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0283320
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0283320&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0283320?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hans Sebastian Heese & Jayashankar M. Swaminathan, 2006. "Product Line Design with Component Commonality and Cost-Reduction Effort," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 206-219, May.
    2. Wu, Peng, 2019. "Which battery-charging technology and insurance contract is preferred in the electric vehicle sharing business?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 537-548.
    3. Guo, Fang & Yang, Jun & Lu, Jianyi, 2018. "The battery charging station location problem: Impact of users’ range anxiety and distance convenience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 1-18.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Javazi, Leila & Alinaghian, Mahdi & Khosroshahi, Hossein, 2025. "Evaluating government policies promoting electric vehicles, considering battery technology, energy saving, and charging infrastructure development: A game theoretic approach," Applied Energy, Elsevier, vol. 390(C).

    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. Ding, Yanyan & Jian, Sisi, 2024. "Strategic investment in charging infrastructure: Sharing costs or taking over?," Applied Energy, Elsevier, vol. 376(PA).
    2. Jalali, Hamed & Carmen, Raïsa & Van Nieuwenhuyse, Inneke & Boute, Robert, 2019. "Quality and pricing decisions in production/inventory systems," European Journal of Operational Research, Elsevier, vol. 272(1), pages 195-206.
    3. Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(C).
    4. Fadda, Edoardo & Manerba, Daniele & Cabodi, Gianpiero & Camurati, Paolo Enrico & Tadei, Roberto, 2021. "Comparative analysis of models and performance indicators for optimal service facility location," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    5. Maria Mayorga & Hyun-Soo Ahn & Goker Aydin, 2013. "Assortment and inventory decisions with multiple quality levels," Annals of Operations Research, Springer, vol. 211(1), pages 301-331, December.
    6. Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
    7. Peng, Ruoqing & Tang, Justin Hayse Chiwing G. & Yang, Xiong & Meng, Meng & Zhang, Jie & Zhuge, Chengxiang, 2024. "Investigating the factors influencing the electric vehicle market share: A comparative study of the European Union and United States," Applied Energy, Elsevier, vol. 355(C).
    8. N. Bora Keskin & John R. Birge, 2019. "Dynamic Selling Mechanisms for Product Differentiation and Learning," Operations Research, INFORMS, vol. 67(4), pages 1069-1089, July.
    9. 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).
    10. Yoo, Seung Ho & Choi, Thomas Y. & Sheu, Jiuh-Biing, 2021. "Electric vehicles and product–service platforms: Now and in future," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    11. Shanshan Guo & H. Sebastian Heese, 2017. "Product variety and distribution channel structure," International Journal of Production Research, Taylor & Francis Journals, vol. 55(12), pages 3392-3410, June.
    12. Bernstein, Fernando & Gürhan Kök, A. & Meca, Ana, 2015. "Cooperation in assembly systems: The role of knowledge sharing networks," European Journal of Operational Research, Elsevier, vol. 240(1), pages 160-171.
    13. Kartik Kalaignanam & Tarun Kushwaha & Anand Nair, 2017. "The Product Quality Impact of Aligning Buyer-Supplier Network Structure and Product Architecture: an Empirical Investigation in the Automobile Industry," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 4(1), pages 1-17, September.
    14. Linder, Christian, 2019. "Customer orientation and operations: The role of manufacturing capabilities in small- and medium-sized enterprises," International Journal of Production Economics, Elsevier, vol. 216(C), pages 105-117.
    15. Serguei Netessine & Terry A. Taylor, 2007. "Product Line Design and Production Technology," Marketing Science, INFORMS, vol. 26(1), pages 101-117, 01-02.
    16. Stylianos Kavadias & Karl T. Ulrich, 2020. "Innovation and New Product Development: Reflections and Insights from the Research Published in the First 20 Years of Manufacturing & Service Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 84-92, January.
    17. Nadine Gatzert & Katrin Osterrieder, 2020. "The future of mobility and its impact on the automobile insurance industry," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 23(1), pages 31-51, March.
    18. Maher Agi & Xinghao Yan, 2020. "Greening products in a supply chain under market segmentation and different channel power structures," Post-Print hal-02898158, HAL.
    19. Fu, Jiali & Nåbo, Arne & Bhatti, Harrison John, 2024. "Locating charging infrastructure for freight transport using multiday travel data," Transport Policy, Elsevier, vol. 152(C), pages 21-28.
    20. Fernando Bernstein & A. Gürhan Kök, 2009. "Dynamic Cost Reduction Through Process Improvement in Assembly Networks," Management Science, INFORMS, vol. 55(4), pages 552-567, April.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0283320. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.