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    DEA-Based electric vehicles efficiency assessment: the case of the European Union countries using mixed and solar sources of energy

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    Rania AlJondob_ OGS Approved Thesis.pdf (1.936Mb)
    Date
    2021-06
    Author
    Aljondob, Rania Tahsin
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    Abstract
    Adopting electric vehicles (EVs) is represented as a promising solution to have more efficient and sustainable transport systems, European Union (EU) members show a significant interest in adopting EVs, and the governments promote the idea by providing facilities to the buyers. EVs need electricity to operate, which could be generated using mixed sources of energy or solar energy. Generating electricity has environmental and economic impacts. Three environmental indicators (water consumption, GHG emissions, and energy consumption) and one economic indicator (contribution to GDP) for 28 EU countries were used to evaluate the EVs efficiency. An input-oriented single stage data envelopment analysis (DEA) model was used to obtain the efficiency scores. The k-means clustering algorithm was used to aggregate the 28 countries into high, medium, or low-efficiency groups. Moreover, in this study, total efficiency scores compared using the t-test tool found that using solar energy is more efficient than using mixed-sources of energy
    DOI/handle
    http://hdl.handle.net/10576/21593
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    • Engineering Management [‎140‎ items ]

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