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Are Existing Battery Electric Vehicles Adoption Studies Able to Inform Policy? A Review for Policymakers

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  • Rongqiu Song

    (School of Geography and Planning, Cardiff University, Cardiff CF10 3WA, UK)

  • Dimitris Potoglou

    (School of Geography and Planning, Cardiff University, Cardiff CF10 3WA, UK)

Abstract

Accelerating the adoption of electric vehicles provides a rare historic opportunity for reducing the dependence on fossil fuel and decarbonising road networks in the field of transport. Many countries have introduced various policy packages on both national and local levels to encourage electric vehicle adoption, but their market shares remain low. For better understanding the reasons behind this evidence, exploring the determinants that influence consumers’ adoption intentions is significant. Previous literature reviews have made clear and elaborated syntheses of influential factors; however, a summary of how evidence can be translated into policy through these factors is lacking. In response, this paper synthesises the main policies of various countries, summarises the previous research results, and forms corresponding policy tools, which can provide a reference to policymakers and guide the policy-making process.

Suggested Citation

  • Rongqiu Song & Dimitris Potoglou, 2020. "Are Existing Battery Electric Vehicles Adoption Studies Able to Inform Policy? A Review for Policymakers," Sustainability, MDPI, vol. 12(16), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6494-:d:397795
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    3. Christopher W. H. Davis & Antonie J. Jetter & Philippe J. Giabbanelli, 2022. "Automatically Generating Scenarios from a Text Corpus: A Case Study on Electric Vehicles," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    4. Hopkins, Emma & Potoglou, Dimitris & Orford, Scott & Cipcigan, Liana, 2023. "Can the equitable roll out of electric vehicle charging infrastructure be achieved?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    5. Fabio Luis Marques dos Santos & Paolo Tecchio & Fulvio Ardente & Ferenc Pekár, 2021. "User Automotive Powertrain-Type Choice Model and Analysis Using Neural Networks," Sustainability, MDPI, vol. 13(2), pages 1-15, January.

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