Exploring the Association Between Artificial Intelligence Management and Green Innovation: Expanding the Research Field for Sustainable Outcomes

Green innovation is essential for achieving sustainable development goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production), as it fosters environmental and social benefits while also creating new economic opportunities. Despite previous studies actively conducting empirical analyses on green innovation, research on guiding the green innovation process through artificial intelligence remains scarce. This study aims to explore key variables that affect green innovation, thereby promoting the sustainable development of organizations, and to investigate the incentive mechanisms behind it. By uncovering the internal and external factors that drive green innovation and their interactions, we can better understand and optimize the process of fostering green innovation. Unlike previous studies, this research not only explores variables and verifies main effects but also provides and validates a research model related to the occurrence of green innovation. Additionally, this study determines the extent to which artificial intelligence management influences green innovation through knowledge sharing and examines whether an innovative culture moderates the impact of artificial intelligence management and knowledge sharing on green innovation, as well as whether it moderates the mediating effect of knowledge sharing within the model. Therefore, this study collected data from 331 adult employees of SMEs across 23 provinces, cities, and districts in China and conducted empirical analyses, including confirmatory factor analysis (CFA) and reliability analysis. The results indicate that artificial intelligence management directly affects green innovation and indirectly affects it through the partial mediating role of knowledge sharing. Furthermore, an innovative culture significantly moderates the mediating role of knowledge sharing between artificial intelligence management and green innovation. In exploring the variables of green innovation, this study established an adjusted mediating model and verified its significance. In summary, the causal relationship between artificial intelligence management and green innovation, as demonstrated through this process, contributes to the expansion of the research field and the advancement of SDGs, specifically Goals 9 and 12. The study’s findings highlight the importance of integrating artificial intelligence management to enhance green innovation, which is vital for the sustainable development and economic growth outlined in the SDGs.

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Publication Details

Journal
Sustainability
Published
2024-10-26
DOI
https://doi.org/10.3390/su16219315
Citations
8
Primary Topic
Knowledge Management and Sharing
Type
article
Field-Weighted Citation Impact
7.66
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article

Exploring the Association Between Artificial Intelligence Management and Green Innovation: Expanding the Research Field for Sustainable Outcomes

Xiu Jin, Jiaxing Du, Han Cai
8 citations
Sustainability
Knowledge Management and Sharing
7.66
article

Exploring the Association Between Artificial Intelligence Management and Green Innovation: Expanding the Research Field for Sustainable Outcomes

Xiu Jin, Jiaxing Du, Han Cai
article en
8 citations

Abstract

Green innovation is essential for achieving sustainable development goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production), as it fosters environmental and social benefits while also creating new economic opportunities. Despite previous studies actively conducting empirical analyses on green innovation, research on guiding the green innovation process through artificial intelligence remains scarce. This study aims to explore key variables that affect green innovation, thereby promoting the sustainable development of organizations, and to investigate the incentive mechanisms behind it. By uncovering the internal and external factors that drive green innovation and their interactions, we can better understand and optimize the process of fostering green innovation. Unlike previous studies, this research not only explores variables and verifies main effects but also provides and validates a research model related to the occurrence of green innovation. Additionally, this study determines the extent to which artificial intelligence management influences green innovation through knowledge sharing and examines whether an innovative culture moderates the impact of artificial intelligence management and knowledge sharing on green innovation, as well as whether it moderates the mediating effect of knowledge sharing within the model. Therefore, this study collected data from 331 adult employees of SMEs across 23 provinces, cities, and districts in China and conducted empirical analyses, including confirmatory factor analysis (CFA) and reliability analysis. The results indicate that artificial intelligence management directly affects green innovation and indirectly affects it through the partial mediating role of knowledge sharing. Furthermore, an innovative culture significantly moderates the mediating role of knowledge sharing between artificial intelligence management and green innovation. In exploring the variables of green innovation, this study established an adjusted mediating model and verified its significance. In summary, the causal relationship between artificial intelligence management and green innovation, as demonstrated through this process, contributes to the expansion of the research field and the advancement of SDGs, specifically Goals 9 and 12. The study’s findings highlight the importance of integrating artificial intelligence management to enhance green innovation, which is vital for the sustainable development and economic growth outlined in the SDGs.

SustainabilityVol. 16(21)
Gachon University (KR), Luoyang Institute of Science and Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 3%
Knowledge Management and Sharing
7.66
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