LAPSE:2024.0162
Published Article
LAPSE:2024.0162
Artificial Intelligence and Carbon Emissions in Manufacturing Firms: The Moderating Role of Green Innovation
Yixuan Chen, Shanyue Jin
February 10, 2024
Carbon emissions have gained worldwide attention in the industrial era. As a key carbon-emitting industry, achieving net-zero carbon emissions in the manufacturing sector is vital to mitigating the negative effects of climate change and achieving sustainable development. The rise of intelligent technologies has driven industrial structural transformations that may help achieve carbon reduction. Artificial intelligence (AI) technology is an important part of digitalization, providing new technological tools and directions for the low carbon development of enterprises. This study selects Chinese A-share listed companies in the manufacturing industry from 2012 to 2021 as the research objects and uses a fixed-effects regression model to study the relationship between AI and carbon emissions. This study clarifies the significance of enterprise AI technology applications in realizing carbon emissions reduction and explores the regulatory mechanism from the perspective of the innovation effect. The results show that the application of enterprise AI technology positively impacts carbon emissions reduction. Simultaneously, green technological innovation, green management innovation, and green product innovation play moderating roles; in other words, enterprise green innovation strengthens the effect of AI on carbon emissions reduction. This study clarifies the necessity of intelligent manufacturing and enriches theories related to AI technology and carbon emissions.
Keywords
Artificial Intelligence, carbon emissions, green management innovation, green product innovation, green technology innovation
Suggested Citation
Chen Y, Jin S. Artificial Intelligence and Carbon Emissions in Manufacturing Firms: The Moderating Role of Green Innovation. (2024). LAPSE:2024.0162
Author Affiliations
Chen Y: College of Business, Gachon University, Seongnam 13120, Republic of Korea
Jin S: College of Business, Gachon University, Seongnam 13120, Republic of Korea [ORCID]
Journal Name
Processes
Volume
11
Issue
9
First Page
2705
Year
2023
Publication Date
2023-09-10
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr11092705, Publication Type: Journal Article
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LAPSE:2024.0162
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doi:10.3390/pr11092705
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Feb 10, 2024
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CC BY 4.0
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[v1] (Original Submission)
Feb 10, 2024
 
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Feb 10, 2024
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Calvin Tsay
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