| Title |
Towards a high-energy efficiency world: Assessing the impact of artificial intelligence on urban energy efficiency |
| ID_Doc |
33444 |
| Authors |
Li, QY; Zhang, JQ; Feng, Y; Sun, RG; Hu, J |
| Title |
Towards a high-energy efficiency world: Assessing the impact of artificial intelligence on urban energy efficiency |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.jclepro.2024.142593 |
| Abstract |
Global warming has increased the frequency of natural disasters, making enhancing energy efficiency an inevitable choice to address the worsening global climate risks. Whether industrial robots, as a crucial component of artificial intelligence, can contribute to improving energy efficiency remains a subject of debate. This study employs the SBM and super-efficiency SBM models to assess the energy efficiency of 262 Chinese cities from 2010 to 2020. We investigate the impact and mechanisms of industrial robots at the city level on energy efficiency. The research findings indicate that the application of industrial robots promotes enhanced energy efficiency, which remains robust after subjecting it to a battery of tests, including SYS-GMM and instrumental variable analyses. However, a significant nonlinear relationship exists between industrial robot utilization and energy efficiency, with diminishing marginal effects. Mechanism analysis reveals that the fundamental mechanisms facilitating this improvement are the digital economy, industrial structural adjustments, and innovations in green technology. Heterogeneity analysis suggests that industrial robots have a more pronounced impact on cities with higher energy efficiency, greater manufacturing levels in resource-dependent areas, and lower population densities. Furthermore, the application of industrial robots can influence the energy efficiency of neighboring regions through spatial spillover effects. |
| Author Keywords |
Artificial intelligence; Industrial robots; Energy efficiency; Spatial spillover effect; Nonlinear effect; Moderating effect |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001245529800001 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Environmental; Environmental Sciences |
| Research Area |
Science & Technology - Other Topics; Engineering; Environmental Sciences & Ecology |
| PDF |
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