A comprehensive DEA-based framework for evaluating sustainability and efficiency of vehicle types: Integrating undesirable inputs and social-environmental indicators
The sustainability and efficiency of different vehicle types play a crucial role in reducing environmental impacts. As governments and industries move towards greener transportation, choosing an appropriate evaluation method remains a challenge. This study uses data envelopment analysis (DEA) to evaluate the efficiency of five major vehicle types – gasoline, diesel, hybrid, electric, and hydrogen – by considering key economic, environmental, and technical factors such as carbon emissions, fuel costs, and non-recyclable materials. The DEA results are then compared with a multiple regression model to analyze the impact of different independent variables on vehicle efficiency. The results of this study show that electric vehicles have the highest environmental and economic efficiency despite the challenges associated with battery recycling. In contrast, diesel vehicles have the lowest efficiency scores due to their high emissions and environmental costs. This study emphasizes the need for policy incentives to accelerate the adoption of sustainable vehicles, including infrastructure investments, financial incentives, and environmental considerations in efficiency assessments.
Authors
- Václav Snåšel (ORCID: https://orcid.org/0000-0002-9600-8319)
- Jan Platoš (ORCID: https://orcid.org/0000-0002-8481-0136)
- Sara Fanati Rashidi (ORCID: https://orcid.org/0000-0002-7957-6816)
- Seyedali Mirjalili (ORCID: https://orcid.org/0000-0002-1443-9458)
- Maryam Olfati (ORCID: https://orcid.org/0000-0001-6843-6829)
Institutions
- VSB - Technical University of Ostrava (CZ)
- Torrens University Australia (AU)
Publication Details
- Journal
- Cleaner Engineering and Technology
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1016/j.clet.2025.100989
- Citations
- 7
- Primary Topic
- Environmental Impact and Sustainability
- Type
- article
- Field-Weighted Citation Impact
- 5.59
Funders
- Grantová Agentura České Republiky
- Javna Agencija za Raziskovalno Dejavnost RS
- Vysoká Škola Bánská - Technická Univerzita Ostrava