科研管理

科研管理 ›› 2025, Vol. 46 ›› Issue (10): 82-92.DOI: 10.19571/j.cnki.1000-2995.2025.10.009

• 论文 • 上一篇    下一篇

知识产权保护对人工智能技术创新的影响研究

刘思明1, 张新宇1, 王文静2, 张艺馨3   

  1. 1.对外经济贸易大学统计学院，北京100029；
    2.中央财经大学统计与数学学院，北京100081；
    3.国家统计局 统计科学研究所，北京100826
  • 收稿日期:2024-07-23 修回日期:2025-02-28 接受日期:2025-02-28 出版日期:2025-10-20 发布日期:2025-10-14
  • 通讯作者: 王文静
  • 基金资助:
    教育部人文社会科学重点研究基地重大项目：“数字经济驱动高质量发展的统计测度与分析研究”（22JJD910002, 2023.01—2025.12）；国家社科基金一般项目：“高质量发展目标下创新创业的统计测度、驱动效应与机制优化研究”（21BTJ053, 2021.09—2025.06）；全国统计科学研究重点项目：“关于知识产权保护程度对创新能力影响的测度”（2023LZ038, 2023.11—2025.11）；对外经济贸易大学中央高校基本科研业务费专项资金资助 （CXTD13-04, 2022.01—2025.12）。

Research on the impact of intellectual property protection on artificial intelligence technological innovation

Liu Siming1, Zhang Xinyu1, Wang Wenjing2, Zhang Yixin3   

  1. 1. School of Statistics, University of International Business and Economics, Beijing 100029, China;
    2. School of Statistics and Mathematics, Central University of Finance and Economics, Beijing 100081, China; 
    3. Research Institute of Statistics Sciences, National Bureau of Statistics, Beijing 100826, China
  • Received:2024-07-23 Revised:2025-02-28 Accepted:2025-02-28 Online:2025-10-20 Published:2025-10-14

摘要：    加快人工智能技术创新是我国在新一轮全球竞争中赢得战略主动以及推动新质生产力发展的关键所在。知识产权保护是激发创新活力的重要制度安排。然而，针对人工智能创新的典型特征，知识产权保护能否以及如何发挥创新促进效应尚不明晰。本文基于WIPO的标准识别人工智能专利，构建2010—2021年中国273个城市包含33万余件人工智能专利申请的样本数据。在此基础上，以国家知识产权示范城市政策为准自然实验，借助多时点双重差分模型考察知识产权保护对人工智能创新的影响。结果显示，知识产权示范城市政策通过科技与数字人才集聚、公共支出创新偏向性强化和风险投资引入机制，对城市人工智能创新产生显著促进效应。异质性分析结果表明，知识产权保护的激励效应在人工智能合作研发专利、底层实现技术专利和发明专利产出中更加突出。进一步研究发现，知识产权保护不仅增加了城市人工智能创新数量，还有利于提升创新质量。本研究增添了知识产权保护影响人工智能创新翔实的经验证据，对于充分发挥知识产权保护政策激励效应具有重要启示。

关键词: 知识产权保护, 人工智能技术创新, 知识产权示范城市, 双重差分模型

Abstract:    Accelerating artificial intelligence (AI) technological innovation is crucial for China to gain the strategic advantages in the new round of global competition and to promote the development of new productive forces. Intellectual property (IP) protection is an essential institutional arrangement for stimulating innovative vitality. However, given the typical characteristics of AI innovation, the effectiveness of IP protection in facilitating innovation remains unclear. Based on the identification criteria of AI patents released by WIPO, we constructed a dataset of over 330,000 AI patent applications from 273 Chinese cities from 2010 to 2021. On this basis, the research employed the intellectual property demonstration city policy as a quasi-natural experiment framework and applies a multi-period DID model to examine the impact of IP protection on AI innovation. The results indicated that the IP demonstration city policy significantly promotes urban AI innovation through mechanisms such as the agglomeration of scientific and digital talents, enhanced innovation-oriented public expenditure, and introduction of venture capital. The heterogeneity analysis showed that the incentive effect of IP protection is pronounced in collaborative patents, foundational technology patents, and the output of invention patents. Further research revealed that IP protection not only increases the quantity of urban AI innovation but also contributes to improving innovation quality. This study will provide detailed evidence for the impacts of IP protection on AI innovation and offer valuable implications for fully leveraging the incentive effects of IP policies.

Key words: intellectual property protection, artificial intelligence technological innovation, intellectual property demonstration city, difference-in-differences (DID) model