当代财经 ›› 2025, Vol. 0 ›› Issue (6): 85-98.

• 企业管理 • 上一篇    下一篇

人工智能应用程度对企业数字技术创新的影响研究

田慧敏, 李海林, 周文浩, 张丽萍   

  1. 华侨大学 工商管理学院,福建 泉州 362021
  • 收稿日期:2024-06-11 修回日期:2025-05-25 出版日期:2025-06-15 发布日期:2025-06-17
  • 通讯作者: 李海林,华侨大学教授,博士生导师,工学博士,主要从事数据科学与创新管理研究,联系方式hailin@hqu.edu.cn
  • 作者简介:田慧敏,华侨大学博士研究生,主要从事创新管理研究;周文浩,华侨大学博士研究生,主要从事突破性创新研究;张丽萍,华侨大学研究员,管理学博士,主要从事创新管理研究。
  • 基金资助:
    国家社会科学基金后期资助项目“基于大数据分析的科研主体创新绩效影响机制研究”(22FGLB035); 福建省社会科学基金重点项目“基于颠覆性科研成果识别分析的企业基础研究能力提升研究”(FJ2025A033); 福建省社会科学规划基金项目“基于大数据分析的福建省‘专精特新’中小企业创新绩效提升路径研究”(FJ2024BF039); 福建省创新战略研究科技计划项目“数据要素赋能福建省科技型中小企业创新发展的机理及路径研究”(2024R0043)

Research on the Influence of Artificial Intelligence Application Degree on Enterprise Digital Technology Innovation

Tian Hui-min, Li Hai-lin, Zhou Wen-hao, Zhang Li-ping   

  1. Huaqiao University, Quanzhou 362021, China
  • Received:2024-06-11 Revised:2025-05-25 Online:2025-06-15 Published:2025-06-17

摘要: 人工智能是推动企业进步与发展的关键数字技术之一,对企业的创新模式产生了深远影响。基于“技术—组织—环境”(TOE)框架,深入探讨人工智能应用程度、行业集中度和动态能力的协同作用对企业数字技术创新的影响。选取2020—2022年沪深A股制造业上市公司作为研究样本,采用数据驱动方法展开研究。通过聚类分析发现,可将样本企业划分为三种类型,即强适应性企业、智能柔性企业和弱能力型企业。其中,智能柔性企业在促进高水平数字技术创新方面表现最为突出。决策树分析结果显示,在强适应性企业中,人工智能应用程度、行业集中度、创新能力和吸收能力均对数字技术创新有正向影响,适度提升这些因素的水平能提高企业实现高水平数字技术创新的概率。在智能柔性企业中,人工智能应用程度、行业集中度和适应能力对数字技术创新同样具有正向影响,但在特定情境下,吸收能力可能对数字技术创新产生抑制作用。在弱能力型企业中,行业集中度与数字技术创新之间呈倒U型关系,当行业集中度处于中等水平时,适度的适应能力能促进数字技术创新的提升。为此,企业应全面提高人工智能应用程度;政府应积极营造良好的数字创新发展环境,充分激发企业的数字创新潜力。

关键词: 人工智能应用程度, 数字技术创新, 动态能力, 行业集中度, 机器学习

Abstract: Artificial intelligence is one of the key digital technologies driving the progress and development of enterprises, and has had a profound impact on their innovation models. Based on the “Technology-Organization-Environment”(TOE) framework, this paper explores in depth the synergistic effects of artificial intelligence application level, industry concentration, and dynamic capabilities on digital technology innovation in enterprises. By selecting the A-share manufacturing companies listed on the Shanghai and Shenzhen stock exchanges from 2020 to 2022 as research samples, this paper conducts a study with a data-driven approach. Through the cluster analysis, it is found that the sample enterprises can be divided into three types: strong adaptive enterprises, intelligent flexible enterprises, and weak capability enterprises. Among them, intelligent flexible enterprises have shown the most outstanding performance in promoting high-level digital technology innovation. The decision tree analysis results show that in highly adaptive enterprises, the degree of artificial intelligence application, industry concentration, innovation ability, and absorption ability all have a positive impact on digital technology innovation. Moderately improving the level of these factors can increase the probability of enterprises achieving high-level digital technology innovation. In intelligent flexible enterprises, the degree of application of artificial intelligence, industry concentration, and adaptability also have a positive impact on digital technology innovation, but in specific contexts, absorptive capacity may have a inhibitory effect on digital technology innovation. In weakly capable enterprises, there is an inverted U-shaped relationship between industry concentration and digital technology innovation. When industry concentration is at a moderate level, moderate adaptability can promote the improvement of digital technology innovation. Therefore, enterprises should comprehensively improve the application level of artificial intelligence and the government should actively create a favorable environment for the development of digital innovation and fully stimulate the digital innovation potential of enterprises.

Key words: artificial intelligence application degree, digital technology innovation, dynamic capability, industry concentration, machine learning

中图分类号: