智能制造提高了企业创新效率吗？

——基于企业生命周期理论的解释

李 娇¹　刘建丽²

（1.中国社会科学院大学；2.中国社会科学院）

内容提要：智能制造天然携带一般信息技术所具有的渗透性、替代性、协同性等技术经济特征，在应用到制造领域时，需要经过长期的实验和验证，在实施和产生效果方面存在一定的滞后性和异质性。现有研究关注的问题是智能制造是否会提高企业创新效率，继而产生了生产率之争，但真正的问题是智能制造什么时候提高哪些企业的创新效率，即智能制造提高企业创新效率的有效性问题。本文基于2010—2023年的A股制造业上市公司数据，从企业生命周期视角研究智能制造对企业创新效率的影响。实证结果表明，智能制造整体提高了企业创新效率；从生命周期来看，智能制造对成熟期企业具有正向影响，但对成长期和衰退期企业无影响；企业不同生命周期的创新意愿、研发能力和组织特征是产生这一现象的主要原因。异质性分析结果显示，智能制造提高成熟期非国有企业、高科技企业、技术密集型企业的创新效率，对其他类别或阶段的企业无影响。从作用机制来看，智能制造通过知识吸收能力强化来提升企业创新效率。本文的研究结论对于发展智能制造以助力制造强国建设具有一定启示。

关键词：智能制造；创新效率；生命周期理论；制造业；知识吸收能力

作者简介：李娇，中国社会科学院大学商学院博士研究生，北京，102488；刘建丽，中国社会科学院工业经济研究所研究员、博士生导师，通信作者，北京，100006。

基金项目：国家社会科学基金重大项目“智能制造关键核心技术国产替代战略与政策研究”（21&ZD132）；中国社会科学院登峰战略企业管理优势学科建设项目（DF2023YS25）

引用格式：李娇,刘建丽.智能制造提高了企业创新效率吗?——基于企业生命周期理论的解释[J].经济与管理研究,2025,46(7):110-127.

Does Intelligent Manufacturing Improve Enterprise Innovation Efficiency?

—Explanation Based on Enterprise Life Cycle Theory

LI Jiao¹, LIU Jianli²

(1. University of Chinese Academy of Social Sciences, Beijing 102488;

2. Chinese Academy of Social Sciences, Beijing 100006)

Abstract: Manufacturing serves as the lifeline of national economic development. Promoting R&D innovation in manufacturing enterprises amid the wave of digital intelligence has become crucial for driving the high-quality development of China’s manufacturing sector and ascending to the higher end of the global value chain. Intelligent manufacturing involves not only technological breakthroughs but also a comprehensive transformation of enterprises with technological upgrading as a pivotal driver. By integrating next-generation information technology with manufacturing technology, intelligent manufacturing promotes the production, reorganization, and management of knowledge, thereby enhancing the knowledge absorption capacity in the innovation process and improving the R&D productivity of enterprises. Existing research mainly focuses on whether intelligent manufacturing improves enterprise innovation efficiency, sparking debates about productivity. However, the core issue should be the effectiveness of intelligent manufacturing in improving enterprise innovation efficiency.

Based on data from A-share listed manufacturing companies from 2010 to 2023, this paper explores the influence of intelligent manufacturing on enterprise innovation efficiency from the perspective of the enterprise life cycle. The empirical results show that intelligent manufacturing generally improves enterprise innovation efficiency. From a life cycle perspective, intelligent manufacturing has a positive impact on enterprises in the maturity stage but does not exert a significant impact on those in the growth or decline stages. This phenomenon can primarily be attributed to the varying innovation willingness, R&D capabilities, and organizational characteristics of enterprises in different life cycle stages. Heterogeneity regression analysis reveals that intelligent manufacturing has a significant impact on improving the innovation efficiency of non-state-owned enterprises, high-tech industries, and technology-intensive enterprises in the maturity stage. Regarding the mechanism, intelligent manufacturing can improve enterprise innovation efficiency by strengthening the knowledge absorption capacity.

The main contributions are as follows. (1) This paper explores the relationship between intelligent manufacturing and enterprise innovation based on life cycle theory, supplementing the existing dualism of intelligent manufacturing and enterprise innovation. (2) The measurement of innovation efficiency based on the scaled R&D expenditure incorporates enterprises’ initial investment in patent applications and citations, which can more accurately reflect the input-output relationship of enterprise innovation efficiency. (3) Different from the mechanisms of human capital upgrading, strategic transformation, information channels, capital channels, and cost channels in the existing research, this paper puts forward a knowledge absorption capacity mechanism through which intelligent manufacturing enhances enterprise innovation efficiency, thereby enriching current research.

Keywords: intelligent manufacturing; innovation efficiency; life cycle theory; manufacturing; knowledge absorption capacity

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