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Macro Analysis and Forecast of Global Expansion of Electric Vehicles

Author

Listed:
  • Thakur Dhakal

    (Kangwon National University (South Korea))

  • Kyoung-Soon Min

    (Kangwon National University (South Korea))

Abstract

This study analyzes the diffusion of battery electric vehicles (BEV) in the world and evaluates the vehicle charging stations based on the European Union (EU) scenario. Initially, the global BEV sales data from 2005 to 2018 are fitted with the two most frequently used econometric logistics and Bass diffusion models. Further, the study identifies the different stage adopters, forecasts the consumption of BEVs, and examines the velocity and acceleration of BEV diffusion. Finally, future charging stations are examined to meet the BEV sales demand. Results suggest that the adoption of BEVs demonstrates a better fit on the Bass model where the global BEV market is estimated to grow from 5,3 millions in 2019 to near 40 millions units by 2030, and with the reference of the EU countries’ adoption scenario, the global charging stations will be increased from near 2 millions in 2019 to near 10 millions units by 2030.

Suggested Citation

  • Thakur Dhakal & Kyoung-Soon Min, 2021. "Macro Analysis and Forecast of Global Expansion of Electric Vehicles," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 15(1), pages 67-73.
    • Handle: RePEc:hig:fsight:v:15:y:2021:i:1:p:67-73
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    File URL: https://foresight-journal.hse.ru/data/2021/04/12/1387175437/6-Dhakal-67-73.pdf
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    References listed on IDEAS

    as
    1. Shen, Zuo-Jun Max & Feng, Bo & Mao, Chao & Ran, Lun, 2019. "Optimization models for electric vehicle service operations: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 462-477.
    2. Loisel, Rodica & Pasaoglu, Guzay & Thiel, Christian, 2014. "Large-scale deployment of electric vehicles in Germany by 2030: An analysis of grid-to-vehicle and vehicle-to-grid concepts," Energy Policy, Elsevier, vol. 65(C), pages 432-443.
    3. Fanchao Liao & Eric Molin & Bert van Wee, 2017. "Consumer preferences for electric vehicles: a literature review," Transport Reviews, Taylor & Francis Journals, vol. 37(3), pages 252-275, May.
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    Cited by:

    1. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    2. Monica Bonacina & Mert Demir & Antonio Sileo & Angela Zanoni, 2024. "The slow lane: a study on the diffusion of full-electric cars in Italy," Working Papers 2024.19, Fondazione Eni Enrico Mattei.
    3. Bonacina, Monica & Demir, Mert & Sileo, Antonio & Zanoni, Angela, 2024. "The slow lane: a study on the diffusion of full-electric cars in Italy," FEEM Working Papers 344135, Fondazione Eni Enrico Mattei (FEEM).
    4. Anqi Chen & Shibing You, 2022. "The Fuel Cycle Carbon Reduction Effects of New Energy Vehicles: Empirical Evidence Based on Regional Data in China," Sustainability, MDPI, vol. 14(23), pages 1-17, November.

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    More about this item

    Keywords

    business; innovation; diffusion; potential market; electric vehicle;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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