人工智能应用如何提升制造企业韧性？

成琼文　朱婧丽

（中南大学）

内容提要：增强企业组织韧性是保障中国制造业稳定发展的重要前提，也是内生于中国经济高质量发展的迫切要求。本文基于2010—2023年中国A股制造业上市公司面板数据，运用双向固定效应模型探究人工智能对制造企业韧性的影响效应。研究结果显示，人工智能对制造企业韧性具有提升作用，这一结论在经过内生性分析和稳健性检验后依然成立。影响机制检验结果表明，人工智能能够通过优化供需匹配、加强信息治理协同、提升创新能力以及缓解融资约束等途径促进制造企业韧性水平的提升。异质性分析结果显示，人工智能对制造企业韧性的影响主要发生在大型企业、非国有企业、数字应用场景较多企业、技术密集型行业以及对外开放水平较高地区、信息基础设施水平较高地区、经济发展水平较好地区的企业。本文的研究为运用数智化手段提升制造企业韧性以及推动中国制造业迈向全球价值链中高端提供了理论参考。

关键词：人工智能；制造企业韧性；技术创新；风险管理；供需匹配

作者简介：成琼文，中南大学商学院研究员、博士生导师，湖南，410083；朱婧丽，中南大学商学院硕士研究生。

基金项目：国家社会科学基金一般项目“智能制造企业参与国际标准制定对突破性创新的影响机制研究”（23BGL071）；中南大学高端智库项目“新质生产力背景下增强我国新能源汽车产业链供应链韧性和安全性的机制和路径研究”（502901013）

引用格式：成琼文,朱婧丽.人工智能应用如何提升制造企业韧性?[J].经济与管理研究,2025,46(8):56-75.

How Can AI Applications Enhance the Resilience of Manufacturing Enterprises?

CHENG Qiongwen, ZHU Jingli

(Central South University, Hunan 410083)

Abstract: Enhancing the resilience of enterprises is an important prerequisite for guaranteeing the stable development of manufacturing, and is also an urgent requirement endogenous to the high-quality development of China’s economy. Based on panel data from China’s A-share listed manufacturing companies from 2010 to 2023, this paper comprehensively utilizes the two-way fixed effects model to explore the impact of artificial intelligence (AI) on the resilience of manufacturing enterprises.

The findings confirm that AI has an enhancing effect on the resilience of manufacturing enterprises, and this conclusion remains valid after a series of robustness tests. Mechanism analysis shows that this enhancement is achieved by optimizing supply-demand matching, promoting information governance synergy, boosting innovation capability, and alleviating financial constraints. Heterogeneity analysis reveals that this effect is more pronounced in large enterprises, non state-owned enterprises, enterprises with more digital application scenarios, technology-intensive industries, as well as in regions with higher levels of opening up, more developed information infrastructure, and higher levels of economic development. This paper provides theoretical references for leveraging digital intellectualization to enhance the resilience of manufacturing enterprises and promote China’s manufacturing industry toward the mid-to-high end of the global value chain.

Based on the above findings, this paper puts forward the following policy recommendations. First, it is necessary to deepen AI popularization, strengthen the construction of digital infrastructure hardware, and enhance the soft power of scientific and technological innovation to drive the transition of AI information technology to a new stage of AI deep applications and standardized development. Second, it is essential to seize new opportunities for digital reform, focus on creating an efficient and collaborative digital ecosystem, and fully unleash the core potential of data factors. Third, the innovation investment and financing ecosystem should be optimized, and the financial service system that supports scientific and technological innovation should be further improved to break through the bottlenecks of enterprise intelligent transformation.

The marginal contribution of this paper lies in its research perspective and content. Regarding the research perspective, it focuses on the micro-enterprise level and integrates AI and the resilience of manufacturing enterprises into a unified framework, delving deeply into the relationship between the two. In terms of research content, it incorporates the optimization of supply-demand matching, information governance synergy, and innovation capability enhancement as mediating variables into the analytical framework, seeking to dissect and clarify the underlying logic and mechanisms through which AI applications influence enterprise resilience, thereby constructing a practical pathway for AI to enhance the resilience of manufacturing enterprises.

Keywords: AI; resilience of manufacturing enterprise; technological innovation; risk management; supply-demand matching

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