| Title |
Does green innovation promote environmental efficiency from a global perspective? A hybrid approach (fuzzy DEA-SEM-ANN) |
| ID_Doc |
35197 |
| Authors |
Ghimire, A; Ali, S; Khan, A |
| Title |
Does green innovation promote environmental efficiency from a global perspective? A hybrid approach (fuzzy DEA-SEM-ANN) |
| Year |
2023 |
| Published |
|
| DOI |
10.1007/s11356-023-29761-6 |
| Abstract |
Green innovation is crucial for reducing carbon dioxide (CO2) emissions and promoting environmental efficiency worldwide. However, there is a lack of scholarly research investigating the relationship between environmentally friendly innovations and improved environmental performance. To fill this knowledge gap, a comprehensive study was conducted using data from 64 countries spanning 2010 to 2018. The study employed a hybrid approach, combining fuzzy DEA, structural equation modeling (SEM), and artificial neural networks (ANN) to analyze the nexus between green innovation and environmental efficiency. The SEM analysis revealed that green innovation, green trade, green employment, and green investment significantly impact environmental efficiency. The ANN model achieves a perfect prediction rate for environmental efficiency and green growth, emphasizing the importance of incorporating various sources of green innovation to achieve long-term environmental goals. The study's findings have significant implications for policymakers and governments, highlighting the value of environmentally friendly technologies and the need to allocate resources toward their development. Regional collaboration and integrating green innovation throughout the development process are essential for achieving environmental efficiency. By embracing green innovation, nations can capitalize on its potential benefits while mitigating pollution and promoting sustainable development. Overall, this research serves as a cornerstone for decision-makers, providing insights into the importance of green innovation and guiding efforts to foster environmentally conscious technologies globally. |
| Author Keywords |
Green innovation; Environmental efficiency; Neural network; Fuzzy DEA; SEM |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001073603400012 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
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