Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China
As new-energy vehicles (NEVs) gradually gain public attention, their carbon-reduction issues have become a focal point in academia. This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagu...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/3/635 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850200115122274304 |
|---|---|
| author | Lingyao Wang Taofeng Wu Fangrong Ren |
| author_facet | Lingyao Wang Taofeng Wu Fangrong Ren |
| author_sort | Lingyao Wang |
| collection | DOAJ |
| description | As new-energy vehicles (NEVs) gradually gain public attention, their carbon-reduction issues have become a focal point in academia. This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagum Gini coefficient, and decomposes carbon-emission factors using the LMDI method. Results show that the overall carbon-reduction efficiency is low, with an average value of only 0.266. Significant differences exist in production- and consumption-stage efficiencies across regions. Shanxi Province performed the best, with efficiency scores of 1 in both stages, while the carbon-reduction stage showed the lowest efficiency, ranging between 0.2 and 0.3 in most regions. The central region exhibited the highest carbon-reduction efficiency, followed by the western and eastern regions, primarily influenced by intra-regional disparities. Energy intensity significantly suppresses carbon emissions, followed by energy structure, while economic development and population size positively contribute to carbon emissions. This study provides theoretical support for regional governments to formulate policies related to the NEV industry and offers practical guidance for its further development. |
| format | Article |
| id | doaj-art-0619048386624e1290b704496df4e64a |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-0619048386624e1290b704496df4e64a2025-08-20T02:12:25ZengMDPI AGEnergies1996-10732025-01-0118363510.3390/en18030635Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in ChinaLingyao Wang0Taofeng Wu1Fangrong Ren2School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaCollege of Economics and Management, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Economics and Management, Nanjing Forestry University, Nanjing 210037, ChinaAs new-energy vehicles (NEVs) gradually gain public attention, their carbon-reduction issues have become a focal point in academia. This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagum Gini coefficient, and decomposes carbon-emission factors using the LMDI method. Results show that the overall carbon-reduction efficiency is low, with an average value of only 0.266. Significant differences exist in production- and consumption-stage efficiencies across regions. Shanxi Province performed the best, with efficiency scores of 1 in both stages, while the carbon-reduction stage showed the lowest efficiency, ranging between 0.2 and 0.3 in most regions. The central region exhibited the highest carbon-reduction efficiency, followed by the western and eastern regions, primarily influenced by intra-regional disparities. Energy intensity significantly suppresses carbon emissions, followed by energy structure, while economic development and population size positively contribute to carbon emissions. This study provides theoretical support for regional governments to formulate policies related to the NEV industry and offers practical guidance for its further development.https://www.mdpi.com/1996-1073/18/3/635NEVscarbon-reduction efficiencyspatial differencesDEALMDI |
| spellingShingle | Lingyao Wang Taofeng Wu Fangrong Ren Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China Energies NEVs carbon-reduction efficiency spatial differences DEA LMDI |
| title | Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China |
| title_full | Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China |
| title_fullStr | Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China |
| title_full_unstemmed | Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China |
| title_short | Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China |
| title_sort | analysis of spatial differences and influencing factors of carbon emission reduction efficiency of new energy vehicles in china |
| topic | NEVs carbon-reduction efficiency spatial differences DEA LMDI |
| url | https://www.mdpi.com/1996-1073/18/3/635 |
| work_keys_str_mv | AT lingyaowang analysisofspatialdifferencesandinfluencingfactorsofcarbonemissionreductionefficiencyofnewenergyvehiclesinchina AT taofengwu analysisofspatialdifferencesandinfluencingfactorsofcarbonemissionreductionefficiencyofnewenergyvehiclesinchina AT fangrongren analysisofspatialdifferencesandinfluencingfactorsofcarbonemissionreductionefficiencyofnewenergyvehiclesinchina |