Unlocking innovation potential: the impact of artificial intelligence transformation on enterprise innovation capacity

Purpose Building upon the resource-based view (RBV) and related research, this paper empirically examines the impact and specific mechanisms of artificial intelligence transformation on corporate innovation capabilities. It provides micro-level evidence of AI’s influence on innovation behavior. Design/methodology/approach Drawing upon data from Chinese listed companies spanning the period from 2011 to 2022, this study employs a dual fixed-effects model and a mediation effects model to empirically analyze the influence of enterprise AI transformation on its innovation capability as well as the specific mechanisms involved. Findings The research reveals that AI transformation significantly enhances the innovation capability of enterprises. Heterogeneity analysis indicates that AI transformation exerts a stronger promoting effect on the innovation capability of non-technology firms, large enterprises and those within the manufacturing sector. Mechanism analysis further reveals that AI transformation enhances innovation capability by boosting enterprise profits, reducing costs and reinforcing internal control mechanisms. Further examination demonstrates that AI transformation elevates the quality, efficiency and eco-friendliness of enterprise innovation. Originality/value Firstly, this study employs text analysis methods from machine learning to construct artificial intelligence indicators at the firm level, providing stronger evidence of AI’s impact on corporate innovation capabilities. Secondly, it extends corporate innovation behavior to include innovation quality, efficiency and green innovation practices, offering a more comprehensive validation of AI’s role in fostering corporate innovation.

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Publication Details

Journal
European Journal of Innovation Management
Published
2024-11-25
DOI
https://doi.org/10.1108/ejim-07-2024-0809
Citations
16
Primary Topic
Innovation Policy and R&D
Type
article
Field-Weighted Citation Impact
18.07
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article

Unlocking innovation potential: the impact of artificial intelligence transformation on enterprise innovation capacity

Kerong Zhang, Xuan Ye, Liangyu Jiang
16 citations
European Journal of Innovation Management
Innovation Policy and R&D
18.07
article

Unlocking innovation potential: the impact of artificial intelligence transformation on enterprise innovation capacity

Kerong Zhang, Xuan Ye, Liangyu Jiang
article en
16 citations

Abstract

Purpose Building upon the resource-based view (RBV) and related research, this paper empirically examines the impact and specific mechanisms of artificial intelligence transformation on corporate innovation capabilities. It provides micro-level evidence of AI’s influence on innovation behavior. Design/methodology/approach Drawing upon data from Chinese listed companies spanning the period from 2011 to 2022, this study employs a dual fixed-effects model and a mediation effects model to empirically analyze the influence of enterprise AI transformation on its innovation capability as well as the specific mechanisms involved. Findings The research reveals that AI transformation significantly enhances the innovation capability of enterprises. Heterogeneity analysis indicates that AI transformation exerts a stronger promoting effect on the innovation capability of non-technology firms, large enterprises and those within the manufacturing sector. Mechanism analysis further reveals that AI transformation enhances innovation capability by boosting enterprise profits, reducing costs and reinforcing internal control mechanisms. Further examination demonstrates that AI transformation elevates the quality, efficiency and eco-friendliness of enterprise innovation. Originality/value Firstly, this study employs text analysis methods from machine learning to construct artificial intelligence indicators at the firm level, providing stronger evidence of AI’s impact on corporate innovation capabilities. Secondly, it extends corporate innovation behavior to include innovation quality, efficiency and green innovation practices, offering a more comprehensive validation of AI’s role in fostering corporate innovation.

European Journal of Innovation ManagementVol. 28(8)
Fuyang Normal University (CN), Nanjing University of Finance and Economics (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Innovation Policy and R&D
18.07
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