Barriers and policy solutions for electric vehicle adoption in Spain: a multidimensional analysis

Bianca Cid & María Teresa García-Álvarez

European Journal of Government and Economics2025https://doi.org/10.17979/ejge.2025.14.1.11299article
ABDC C
Weight
0.37

What the paper says

In Spain, the transport sector is one of the largest contributors to greenhouse gas (GHG) emissions, primarily due to the widespread use of fossil fuels. Electric vehicles (EVs) are a key component in transitioning towards sustainable mobility and transport decarbonization. The article presents novel insights into the interplay between economic, technical, regulatory, and social factors affecting EV uptake in Spain, distinguishing itself from previous studies, using a multidimensional approach. It not only identifies the main challenges but also proposes actionable solutions based on successful international case studies. These include enhancing financial incentives, expanding nationwide charging networks, ensuring consistent regulatory frameworks and promoting public awareness campaigns to dispel misconceptions about EVs, among others. By integrating these aspects, the research contributes significantly to the discourse on sustainable transport in Spain, aiming to provide a roadmap for policymakers and stakeholders in achieving national climate targets.

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https://doi.org/https://doi.org/10.17979/ejge.2025.14.1.11299

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@article{bianca2025,
  title        = {{Barriers and policy solutions for electric vehicle adoption in Spain: a multidimensional analysis}},
  author       = {Bianca Cid & María Teresa García-Álvarez},
  journal      = {European Journal of Government and Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.17979/ejge.2025.14.1.11299},
}

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Barriers and policy solutions for electric vehicle adoption in Spain: a multidimensional analysis

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.