A comprehensive DEA-based framework for evaluating sustainability and efficiency of vehicle types: Integrating undesirable inputs and social-environmental indicators

被引:0
作者
Rashidi, Sara Fanati [1 ]
Olfati, Maryam [1 ]
Mirjalili, Seyedali [2 ]
Platos, Jan [1 ]
Snasel, Vaclav [1 ]
机构
[1] VSB Tech Univ Ostrava, Fac Elect Engn & Comp Sci, Dept Comp Sci, Ostrava, Czech Republic
[2] Torrens Univ Australia, Ctr Artificial Intelligence Res & Optimizat, Adelaide, Australia
来源
CLEANER ENGINEERING AND TECHNOLOGY | 2025年 / 27卷
关键词
Data envelopment analysis; Environmental sustainability; Vehicle efficiency; Undesirable inputs and outputs; Multiple regression model; Sensitivity analysis; Sustainable transportation; NONPARAMETRIC PRODUCTION ANALYSIS; DATA ENVELOPMENT ANALYSIS; WEAK DISPOSABILITY; OUTPUTS; GAINS;
D O I
10.1016/j.clet.2025.100989
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:15
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