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Analyzing barriers to the adoption and development of electric vehicles: A roadmap towards sustainable transportation system

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  • Zhang, Hong
  • Irfan, Muhammad
  • Ai, Fengyi
  • Al-Aiban, Khalid M.
  • Abbas, Shujaat

Abstract

Electric vehicles (EVs) are positioned as an alternate green energy technology, which potentially can enable the efficient transition to sustainable low-carbon emission transportation systems. However, different barriers hamper the public adoption of EVs. The degree to which these barriers prevent the adoption of EVs and the potential alternatives to these barriers are mostly unknown. To fill this research gap, the current study contributes by systematically identifying those barriers based on their importance. Initially, several barriers were identified using existing literature, and then by employing the modified Delphi method, a total of twenty-five barriers were classified into five significant dimensions. The Analytical Hierarchical Process (AHP) determined the rankings of these barriers based on weight allocation. As a next step, the Grey Technique for Order Preference by Similarity to Ideal Solution (G-TOPSIS) ranked alternative solutions to these barriers. The findings indicate that 'technological barrier' is the top-ranked barrier among all major dimensions. The overall ranking indicated that 'battery technology' is most influential among sub-dimensions. It is recommended that "investment in research and development" is the best alternative to overcome these barriers. In order to improve the renewable and sustainable urban transportation system, all stakeholders should cooperate in a consistent and coherent manner.

Suggested Citation

  • Zhang, Hong & Irfan, Muhammad & Ai, Fengyi & Al-Aiban, Khalid M. & Abbas, Shujaat, 2024. "Analyzing barriers to the adoption and development of electric vehicles: A roadmap towards sustainable transportation system," Renewable Energy, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:renene:v:233:y:2024:i:c:s0960148124012047
    DOI: 10.1016/j.renene.2024.121136
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