Concerns about the environment have grown worldwide as carbon emissions, one of the primary drivers of global warming, continue to rise. As the transportation industry is one of the most greenhouse-gas-emitting sectors in the European Union (EU), the need for environmentally friendly solutions has been increasing progressively. In this regard, electric vehicles (EVs) play an important part in mitigating some of the adverse effects of road transportation on human health, the environment, and climate. Therefore, the popularity of electric vehicles in the EU has recently increased significantly because of climate change mitigation efforts. In this paper, we aim to analyze and compare the performance of European EVs with multi-criteria decision-making (MCDM) methods, namely preference selection index (PSI) and axial-distance-based aggregated measurement (ADAM) techniques, which do not need the criteria weights for measurement and a novel three-dimensional evaluation technique. The results of both MCDM methods reveal that the EVs of the Tesla Inc. and Geely Group models are found to be the best-performing vehicles. We also investigate the efficiency of the European EV market by the super-efficiency data envelopment analysis (DEA) technique, which enables us to evaluate among efficient units. The efficiency scores indicate that five EVs from three different manufacturer groups obtain efficiency levels. To the best of our knowledge, European EV market evaluation by integrated and comparative analysis has not been encountered for the EU on a group basis. The suggested MCDM and DEA techniques can benefit stakeholders while assessing the European EV market.


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    Titel :

    Analyzing the Performances and Efficiencies of European Electric Vehicles in the European Union Market Using Decision Analysis Methods


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    04.04.2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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