科研管理

科研管理 ›› 2025, Vol. 46 ›› Issue (5): 1-12.DOI: 10.19571/j.cnki.1000-2995.2025.05.001

• 论文 •    下一篇

数字化转型对中国制造业企业创新的影响研究

李晓蓉,张津明,刘红琴   

  1. 昆明理工大学管理与经济学院，云南 昆明650500
  • 收稿日期:2024-09-24 修回日期:2025-04-22 出版日期:2025-05-20 发布日期:2025-05-12
  • 通讯作者: 刘红琴
  • 基金资助:
    教育部人文社会科学研究青年项目：“区域协调发展视域下省域碳排放差异分析及分区分类碳补偿机制研究”（22JYC790076,2023.02—2025.02）；昆明理工大学哲学社会科学学术精品培育项目：“数字化转型对制造业企业创新影响研究——动态能力与创新能力的链式中介作用”（JPSC2024006,2024.06—2026.06）。

Research on the impact of digital transformation on the innovation of Chinese manufacturing enterprises

Li Xiaorong, Zhang Jinming, Liu Hongqin   

  1. Faculty of Management and Economics, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
  • Received:2024-09-24 Revised:2025-04-22 Online:2025-05-20 Published:2025-05-12

摘要：    如何充分利用数字资源以实现创新绩效的提升，是推动我国制造业高质量发展的现实议题。现有研究集中于动态能力对创新绩效的影响，却鲜少解析动态能力与创新能力的内在异质性和关联性，以及二者在数字化赋能进程中的协同作用机理。本文基于动态能力理论和“资源-能力-绩效”逻辑，以A股上市制造企业2013—2022年数据为样本，运用固定效应模型和Bootstrap等方法，实证检验数字化转型对企业创新绩效的影响机制。研究发现：（1）数字化转型通过技术赋能驱动企业创新绩效提升；（2）动态能力（机会感知、学习吸收、资源重构能力）和创新能力呈现双重传导机制，在数字化转型驱动创新绩效提升的过程中存在多条路径，动态能力和创新能力是内核动因；（3）环境不确定性抑制了机会感知能力、学习吸收能力、创新能力对创新绩效的促进作用，但对资源重构能力的调节作用不显著，企业有必要加强对外部环境的警惕和实时监控。研究结论进一步拓展了中国制造业企业数字化转型驱动创新的作用路径，为企业数字化转型提供理论依据和启示。

关键词: 数字化转型, 创新绩效, 动态能力, 创新能力, 链式中介

Abstract:     Leveraging digital resources effectively to enhance innovation performance constitutes a critical practical issue in promoting the high-quality development of China′s manufacturing sector. Existing research has predominantly focused on the impact of dynamic capabilities on innovation performance, yet seldom explores the intrinsic connection between dynamic capabilities and innovation capabilities, as well as their synergistic interaction mechanisms within digital-enabled transformation processes. Based on the dynamic capability theory and the "resource-capability-performance" logic framework, this thesis empirically examined the impact and mechanisms of digital transformation on corporate innovation performance using the data from A-share listed manufacturing enterprises during 2013-2022 and employing the fixed-effects models and Bootstrap methods. The findings revealed that: (1) Digital transformation drives the enhancement of innovation performance through technological enablement; (2) Dynamic capability (opportunity perception, learning absorption, resource restructuring capability) and innovation capability exhibit dual transmission mechanisms. Multiple pathways exist in the process where digital transformation drives innovation performance improvement, with dynamic capabilities and innovation capabilities acting as core driving factors; (3) Environmental uncertainty significantly inhibits the enhancing effects of opportunity perception capability, learning absorption capability and innovation capability on innovation performance, while its moderating role in resource reconfiguration capability remains insignificant. Enterprises should therefore strengthen vigilance and real-time monitoring of external environment. The research has further expanded the pathways through which digital transformation drives innovation in Chinese manufacturing enterprises, and provided theoretical basis and practical implications for enterprise digital transformation.

Key words: digital transformation, innovation performance, dynamic capability, innovation capability, chain mediation