Green Technology Innovation Efficiency of New Energy Vehicles Based on Corporate Profitability Perspective
Abstract
:1. Introduction
2. Literature Review
2.1. The Concept of Green Technological Innovation Efficiency
2.2. Measurement of Green Technological Innovation Efficiency
2.3. Key Factors Affecting Green Technology Innovation
3. Research Design
3.1. Model Specification
3.1.1. Network SBM Moder
3.1.2. SBM Super-Efficiency Model Incorporating Undesired Outputs
3.1.3. Malmquist–Luenberger Index Model
3.1.4. Tobit Modeling
3.2. Variables Chosen
3.2.1. Input–Output Indicators for the R&D Phase of Green Technologies
3.2.2. Input–Output Indicators at the Green Transformation Stage
3.2.3. Influencing Factors
3.3. Sample Selection and Data Sources
4. Empirical Analysis
4.1. Measurement of Green Technology Innovation Efficiency in the New Energy Vehicle Industry
4.1.1. Static Analysis of Green Technology Innovation
4.1.2. The Efficiency of Two-Stage Green Technology Innovation
4.1.3. Efficiency Based on the Geographic Location of the Enterprise
4.2. The Dynamic Efficiency of Green Technology Innovation
4.3. Tobit Model Result Analysis
5. Conclusions and Discussion
5.1. Conclusions
5.2. Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Point | Indicator Category | Indicator Name | Description of Indicators |
---|---|---|---|
R&D phase | Manpower inputs | R&D personnel equivalent | Number of enterprise R&D personnel/number of persons in enterprise (persons) |
Capital investment | R&D investment intensity | Enterprise R&D investment expenditure/enterprise revenue | |
Intermediate outputs | Green patent applications | Total number of green patents obtained by enterprises independently and jointly | |
Transformation phase | Green patent grants | Number of invention green patents granted to enterprises | |
Energy inputs | Total energy consumption | Tons of standard coal | |
Expected outputs | Enterprise business income | Revenue from business | |
Corporate profitability | Corporate net profit | ||
Unexpected outputs | Total pollutant emission intensity | Enterprise emissions of sulfur dioxide, nitrogen oxides, and particulate matter (soot and dust) |
2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | Average | |
---|---|---|---|---|---|---|---|---|---|---|
Technical efficiency | 0.350 | 0.312 | 0.291 | 0.269 | 0.254 | 0.251 | 0.250 | 0.242 | 0.247 | 0.274 |
Pure technical efficiency | 0.382 | 0.338 | 0.316 | 0.292 | 0.277 | 0.272 | 0.271 | 0.264 | 0.268 | 0.298 |
Scale efficiency | 0.909 | 0.921 | 0.921 | 0.928 | 0.928 | 0.933 | 0.935 | 0.936 | 0.933 | 0.927 |
R&D Phase | Transformation Phase | |||||
---|---|---|---|---|---|---|
Year | Technical Efficiency | Pure Technical Efficiency | Scale Efficiency | Technical Efficiency | Pure Technical Efficiency | Scale Efficiency |
2015 | 0.140 | 0.183 | 0.854 | 0.560 | 0.581 | 0.964 |
2016 | 0.140 | 0.182 | 0.863 | 0.485 | 0.495 | 0.980 |
2017 | 0.142 | 0.183 | 0.862 | 0.440 | 0.449 | 0.980 |
2018 | 0.138 | 0.172 | 0.885 | 0.401 | 0.412 | 0.970 |
2019 | 0.137 | 0.169 | 0.896 | 0.371 | 0.386 | 0.959 |
2020 | 0.137 | 0.169 | 0.897 | 0.364 | 0.375 | 0.970 |
2021 | 0.142 | 0.174 | 0.898 | 0.358 | 0.368 | 0.971 |
2022 | 0.134 | 0.165 | 0.907 | 0.350 | 0.362 | 0.966 |
2023 | 0.126 | 0.154 | 0.910 | 0.368 | 0.383 | 0.955 |
2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | Average Value | |
---|---|---|---|---|---|---|---|---|---|---|
Eastern region | 0.352 | 0.315 | 0.293 | 0.27 | 0.255 | 0.251 | 0.247 | 0.241 | 0.246 | 0.274 |
Central region | 0.326 | 0.298 | 0.287 | 0.268 | 0.25 | 0.25 | 0.258 | 0.243 | 0.249 | 0.27 |
Western region | 0.376 | 0.333 | 0.29 | 0.272 | 0.259 | 0.255 | 0.262 | 0.264 | 0.257 | 0.285 |
Year | EC | TC | PE | SE | ML |
---|---|---|---|---|---|
2015–2016 | 1.054 | 0.858 | 1.063 | 0.992 | 0.905 |
2016–2017 | 1.022 | 0.884 | 1.013 | 1.009 | 0.904 |
2017–2018 | 0.986 | 0.906 | 1.002 | 0.984 | 0.893 |
2018–2019 | 1.004 | 0.921 | 1.002 | 1.003 | 0.924 |
2019–2020 | 0.998 | 0.952 | 0.998 | 1 | 0.95 |
2020–2021 | 1.001 | 0.944 | 1.005 | 0.996 | 0.945 |
2021–2022 | 0.959 | 0.973 | 1 | 0.959 | 0.934 |
2022–2023 | 0.962 | 1.094 | 0.913 | 1.053 | 1.053 |
Mean | 0.998 | 0.939 | 0.999 | 0.999 | 0.937 |
Variable Name | Ratio | Standard Error | t-Value | p-Value |
---|---|---|---|---|
Gov | −0.1021 | 0.0012 | −2.87 | 0.004 |
Insize | −0.2277 | 0.1279 | −2.26 | 0.024 |
Rd | −0.0012 | 0.0004 | −5.66 | 0.000 |
_cons | 0.2218 | 0.0208 | 105.00 | 0.000 |
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Zhu, C.; Wang, Z.; Xue, Y. Green Technology Innovation Efficiency of New Energy Vehicles Based on Corporate Profitability Perspective. World Electr. Veh. J. 2025, 16, 311. https://doi.org/10.3390/wevj16060311
Zhu C, Wang Z, Xue Y. Green Technology Innovation Efficiency of New Energy Vehicles Based on Corporate Profitability Perspective. World Electric Vehicle Journal. 2025; 16(6):311. https://doi.org/10.3390/wevj16060311
Chicago/Turabian StyleZhu, Chunqian, Zhongshuai Wang, and Yawei Xue. 2025. "Green Technology Innovation Efficiency of New Energy Vehicles Based on Corporate Profitability Perspective" World Electric Vehicle Journal 16, no. 6: 311. https://doi.org/10.3390/wevj16060311
APA StyleZhu, C., Wang, Z., & Xue, Y. (2025). Green Technology Innovation Efficiency of New Energy Vehicles Based on Corporate Profitability Perspective. World Electric Vehicle Journal, 16(6), 311. https://doi.org/10.3390/wevj16060311