财经论丛 ›› 2024, Vol. 40 ›› Issue (12): 102-112.

• 工商管理 • 上一篇    

人工智能应用如何影响制造企业创新绩效?

李果1, 白云朴2   

  1. 1.南京大学信息管理学院,江苏 南京 210023;
    2.南京邮电大学管理学院,江苏 南京 210093
  • 收稿日期:2023-10-19 出版日期:2024-12-10 发布日期:2024-12-10
  • 作者简介:李果(1997—),女,甘肃白银人,南京大学信息管理学院博士生;白云朴(1985—),男,内蒙古呼伦贝尔人,南京邮电大学管理学院副教授,博士。
  • 基金资助:
    国家社会科学基金项目(20CGL061);教育部人文社科青年基金项目(19YJC790002)

How does Application of Artificial Intelligence Affect the Innovation Performance of Manufacturing Enterprises?

LI Guo1, BAI Yunpu2   

  1. 1. School of Information Management, Nanjing University, Nanjing 210023, China;
    2. School of Management, Nanjing University of Posts and Telecommunications, Nanjing 210093, China
  • Received:2023-10-19 Online:2024-12-10 Published:2024-12-10

摘要: 人工智能在技术研发领域的应用为制造企业带来了前所未有的创新机遇和突破。本文基于动态能力理论和企业创新理论构建了人工智能应用赋能制造企业创新绩效的理论分析框架,利用2013—2021年我国制造业A股上市企业面板数据,运用文本挖掘技术构建人工智能应用综合测度指标,实证检验人工智能在制造企业技术研发领域的应用对企业创新绩效的影响效应及其作用机制。结果发现,人工智能应用显著提升了制造企业创新绩效,且该结论在一系列稳健性检验后依然成立。中介效应检验表明,动态能力在人工智能应用提升制造企业创新绩效的过程中发挥部分中介作用。异质性检验结果显示,人工智能应用对制造企业创新绩效的促进作用在国有企业、大企业、高新技术行业企业以及人工智能应用程度较高地区的企业中更为显著。本研究为理解人工智能赋能制造企业创新绩效提供了新视角,同时为推动制造企业智能化转型提供了理论基础和决策参考。

关键词: 人工智能, 创新绩效, 动态能力, 文本分析

Abstract: The application of artificial intelligence (AI) in technology research and development has brought unprecedented innovation opportunities and challenges to manufacturing companies. Based on the dynamic capability theory and the enterprise innovation theory, this paper constructs a theoretical analysis framework of AI application affecting enterprises' innovation performance, utilizes the data from A-share listed enterprises in China's manufacturing industry from 2013 to 2021, uses the text mining technology to construct a comprehensive measurement index for the degree of application of AI, and empirically test the impact of AI on enterprises' innovation performance and its functioning mechanism in the field of technology R&D of manufacturing enterprises. The results indicate that the application of AI has significantly improved the innovation performance of manufacturing enterprises, and this conclusion still holds after a series of robustness tests. In addition, dynamic capabilities play a partial mediating role in the process of improving the innovation performance of manufacturing firms through AI. The heterogeneity test results indicate that the improvement effect of AI on the innovation performance of enterprises is more significant for state-owned enterprises, large enterprises, enterprises in high-tech industries, and enterprises in regions with a higher degree of AI application. The results of the study provide a new perspective for understanding the innovation performance of manufacturing enterprises empowered by AI, and a theoretical basis and decision-making reference for promoting the intelligent transformation of enterprises.

Key words: Artificial Intelligence, Innovation Performance, Dynamic Capability, Text Analysis

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