知识管理
稳健性(进化)
计算机科学
透视图(图形)
技术管理
构造(python库)
技术变革
实证研究
创新管理
信息技术
企业管理
商业智能
专利分析
业务
经验证据
管理科学
显性知识
技术预测
机制(生物学)
人力资本
作者
Bin Li,L. Wang,Shuaishuai Fu,Jiayu Wan
标识
DOI:10.1108/jkm-03-2025-0345
摘要
Purpose This paper aims to construct a systematic theoretical analysis framework from the perspective of knowledge management capabilities, and to explore the empowering effect and the underlying theoretical mechanisms of artificial intelligence (AI) technology application on enterprise technological innovation, thereby providing theoretical references and empirical evidence for policymaking and management practices. Design/methodology/approach This paper selects the operation data and technical invention patent data of Chinese listed companies from 2012 to 2023 to deeply explore the empowering effect of AI on enterprise technological innovation. This paper uses a fixed-effects model to perform regression analysis on the samples, and conducts systematic robustness tests, heterogeneity analysis and extensibility analysis. Findings This study finds that the application of AI technology can systematically enhance enterprises’ knowledge management capabilities (including knowledge acquisition, integration, application and transformation), thereby empowering technological innovation. This conclusion remains robust after a series of robustness checks. Moreover, compared with logical AI technologies, learning AI technologies exhibit a more pronounced empowering effect on enterprise’s technological innovation. The heterogeneity analysis reveals that the empowering effect of AI technology on technological innovation is stronger in enterprises with low financing constraints, high human capital and technology-intensive characteristics. The extended analysis further shows that AI technology application significantly promotes both incremental and radical technological innovations, though its impact on the latter demonstrates a notable lagged effect. Originality/value Based on the theory of knowledge management, this paper constructs a systematic theoretical analysis framework and explores the internal theoretical mechanism of AI empowering enterprise technological innovation from the perspective of knowledge management capabilities. Meanwhile, this paper innovatively uses machine learning methods to conduct text analysis on the annual reports of listed companies, and simultaneously uses the index of AI technology investment to directly quantify and measure the level of AI application of enterprises, and conduct classified research on it (logical AI and learning AI). In addition, this paper deeply explores the differentiated impact of AI on incremental technological innovation and breakthrough technological innovation.
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