Can enterprise green technology innovation performance achieve "corner overtaking" by using artificial intelligence?-Evidence from Chinese manufacturing enterprises
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Tian, Hongna
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Zhao, Liyan
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Harbin Univ Sci & Technol, Sch Econ & Management, Dept Management, Harbin, Peoples R ChinaHarbin Univ Sci & Technol, Sch Econ & Management, Dept Management, Harbin, Peoples R China
Zhao, Liyan
[1
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Li, Yunfang
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Harbin Univ Sci & Technol, Sch Econ & Management, Dept Management, Harbin, Peoples R ChinaHarbin Univ Sci & Technol, Sch Econ & Management, Dept Management, Harbin, Peoples R China
Li, Yunfang
[1
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Wang, Wei
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Harbin Univ Sci & Technol, Sch Econ & Management, Dept Management, Harbin, Peoples R ChinaHarbin Univ Sci & Technol, Sch Econ & Management, Dept Management, Harbin, Peoples R China
Wang, Wei
[1
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机构:
[1] Harbin Univ Sci & Technol, Sch Econ & Management, Dept Management, Harbin, Peoples R China
To examine the impact of the application of artificial intelligence on the green technology innovation performance of enterprises, a multi-period difference-in-differences model was constructed. Panel data of Chinese listed manufacturing companies over the period of 2014-2020 were used. According to Stimulus-OrganismResponse theory, the impact of artificial intelligence on the green technology innovation performance of enterprises is not direct. The mediating effects of basic knowledge coupling, complementary knowledge coupling, and extended knowledge coupling are verified through empirical tests. The results show that artificial intelligence significantly positively impacts the innovation performance of enterprises in relation to the development of green technology and its decomposition variables (efficiency and progress of green technology). The mediation effect indicates that artificial intelligence mainly promotes the green technology innovation performance of enterprises by affecting their knowledge coupling.