| Title | Tapping into the green potential: The power of artificial intelligence adoption in corporate green innovation drive |
|---|---|
| ID_Doc | 31218 |
| Authors | Hussain, M; Yang, SH; Maqsood, US; Zahid, RMA |
| Title | Tapping into the green potential: The power of artificial intelligence adoption in corporate green innovation drive |
| Year | 2024 |
| Published | Business Strategy And The Environment, 33, 5 |
| Abstract | In response to growing environmental challenges, there is an urgent need to understand how corporations can leverage new technologies to boost sustainability and eco-innovation. This study addresses this need by investigating Artificial Intelligence adoption (AIA) influence on green innovation (greenovation) performance among Chinese firms as China's expanding digital economy and severe ecological pressures make it unique study context. Specifically, panel data on 8722 firm-year observations from Chinese listed firms from 2008 to 2017 is analyzed to test the relationship. The main findings show that higher AIA is associated with increased greenovation, measured through green patents. This positive effect is more pronounced among privately-owned enterprises versus state-owned enterprises. Additionally, financial analysts are found to strengthen the AI-greennovation link through information dissemination and scrutiny. Importantly, the study findings are robust and validated through a battery of tests, including change regression, instrumental variable methods, propensity score match (PSM), and sysGMM. Overall, this study provides novel empirical evidence that AI holds promise as an enabler of corporate eco-innovation. The findings have crucial implications for research and practice regarding leveraging digital technologies for sustainability, especially in emerging economies like China that is undergoing rapid technological change. |
Similar Articles
| ID | Score | Article |
|---|---|---|
35658
|
Wang, ZR; Zhang, TY; Ren, XH; Shi, YK AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies(2024) | |
| 32238
|
Zhang, ZG; Li, PL; Huang, LX; Kang, YC The impact of artificial intelligence on green transformation of manufacturing enterprises: evidence from China(2024)Economic Change And Restructuring, 57, 4 | |
| 35594
|
Ying, Y; Jin, S Artificial intelligence and green product innovation: Moderating effect of organizational capital(2024)Heliyon, 10, 7 | |
| 30366
|
Huang, XA; Wang, YZ; Chen, Y; Hu, ZG Green Technology Innovation and Enterprise Performance: An Analysis Based on Causal Machine Learning Models(2024)Sustainability, 16, 6 | |
| 76193
|
Song, ML; Pan, HT; Shen, ZY; Tamayo-Verleene, K Assessing the influence of artificial intelligence on the energy efficiency for sustainable ecological products value(2024) | |
| 30658
|
Tian, HN; Zhao, LY; Li, YF; Wang, W Can enterprise green technology innovation performance achieve "corner overtaking" by using artificial intelligence?-Evidence from Chinese manufacturing enterprises(2023) | |
| 62041
|
Xu, C; Sun, GL; Kong, T The impact of digital transformation on enterprise green innovation(2024) | |
| 30164
|
Wang, YQ; Wang, W How green industrial policy affects the constancy of green technology innovation: a fresh proof from the innovation motivation perspective(2024)Environmental Research Communications, 6, 3 | |
| 35086
|
Wang, XY; Zhong, XF Digital transformation and green innovation: firm-level evidence from China(2024) | |
| 30151
|
Du, LZ; Wei, MJ; Wu, KY Information technology and firm's green innovation: evidence from China(2023)Environmental Science And Pollution Research, 30, 43 |