科研管理 ›› 2023, Vol. 44 ›› Issue (10): 53-61.DOI: 10.19571/j.cnki.1000-2995.2023.10.006

• 论文 • 上一篇    下一篇

知识产权保护与企业数字化转型——基于知识产权示范城市的准自然实验

许为宾1,2,唐青舟1,李欢1   

  1. 1.贵州大学管理学院, 贵州 贵阳550025;
    2.贵州大学喀斯特地区发展战略研究中心,贵州 贵阳550025
  • 收稿日期:2022-10-16 修回日期:2023-04-24 出版日期:2023-10-20 发布日期:2023-10-10
  • 通讯作者: 许为宾
  • 基金资助:
    国家自然科学基金项目:“历史的延续:家族涉入的家族化起源依赖与家族企业创新行为研究”(72262006,2023—2026);国家自然科学基金项目:“家族企业控制权配置的社会阶层烙印与企业投资‘脱实向虚’”(71862006,2019—2022);贵州大学文科研究一般项目:“基于企业成长视角的高管激励、治理情境与技术创新动态能力演化研究”(GDYB2021019,2021—2023)。

Intellectual property protection and digital transformation of enterprises: A quasi-natural experiment based on intellectual property demonstration cities

Xu Weibin1,2, Tang Qingzhou1, Li Huan1   

  1. 1. School of Management, Guizhou University, Guiyang 550025, Guizhou, China; 
    2. Karst Region Development Strategy Research Center, Guizhou University, Guiyang 550025, Guizhou, China
  • Received:2022-10-16 Revised:2023-04-24 Online:2023-10-20 Published:2023-10-10

摘要:    在企业积极推进数字化转型以实现持续发展的进程中,制度政策发挥了至关重要的作用。文章以知识产权示范城市建设为切入点,使用2008—2021年沪深A股上市公司数据进行实证检验发现,知识产权示范城市建设可以有效促进企业进行数字化转型。进一步检验发现,前者对后者的促进关系在西部地区和大城市中更显著。从作用机制来看,知识产权示范城市建设通过增加创新投入的“研发效应”,以及提升人力资本的“人才效应”两种机制来促进企业进行数字化转型。研究结论为理解企业数字化转型前置动因问题,提供了新视角和新知识。

关键词: 知识产权示范城市, 知识产权保护, 企业数字化转型, 双重差分模型

Abstract:     Digital transformation is a key factor for enterprises to achieve sustainable development. With the development and progress of technology, the technological factors driving the successful completion of digital transformation by enterprises have gradually matured. However, due to the incomplete social system of laws and regulations related to it, the successful implementation of digital transformation by enterprises has been hindered. Therefore, this paper explored the relationship between the intellectual property protection system and digital transformation of enterprises from the perspective of construction of intellectual property demonstration cities. Based on this, the paper used the difference-in-differences method to empirically test the impact and mechanism of construction of intellectual property demonstration cities with respect to digital transformation of enterprises by using the listed companies on the Shanghai and Shenzhen stock exchanges from 2008 to 2021 as a sample. The study found that the construction of intellectual property demonstration cities can significantly promote digital transformation of enterprises, and this conclusion still holds after a series of robustness tests. In terms of the mechanism, the construction of intellectual property demonstration cities promotes the digital transformation of enterprises through two mechanisms: the "R&D effect" of increasing innovation investment and the "talent effect" of enhancing human capital. Further analysis found that the promotion effect of the construction of intellectual property demonstration cities on digital transformation of enterprises is more significant in western regions and large cities. The research conclusions will provide a new perspective and inspiration for understanding the preconditions of digital transformation of enterprises.The research contribution of this paper is reflected in three aspects: Firstly, the digital transformation of enterprises represents the advanced productive forces of the future and it is a powerful driving force for further stimulating innovation-driven development. Improving and promoting policies and systems related to the digital transformation is an important guarantee for helping enterprises smoothly achieve digital transformation. The research conclusion of this paper will provide empirical evidence for understanding the policy effects of constructing intellectual property demonstration cities, and it will also provide solid evidence for enriching the theory of supply-led institutional change, thus having a certain theoretical contribution. At the same time, this paper used the implementation practice of construction of intellectual property demonstration cities as a quasi-natural experiment to identify the relationship between institutional policy changes and micro-digital transformation of enterprises through the exogenous impact of policy demonstration, reducing the problem of endogeneity in estimation and making the estimation results more accurate. This will further improve the relevant research methods by optimizing the internal problems which existed in previous studies that used the number of local intellectual property cases to measure the level of intellectual property protection.Secondly, by examining the "R&D effect" and "talent effect" of intellectual property demonstration city construction policies, this paper clarified their intrinsic impact mechanisms and revealed the "mechanism black box" of how intellectual property institutions affect digital transformation of enterprises. This will provide a logical theoretical explanation for the reasons behind digital transformation of enterprises and will help to enrich and expand research in this field.Thirdly, previous research mostly explored the differentiated impact of intellectual property protection on digital transformation of enterprises from the perspective of enterprise characteristics. This paper started from such two aspects as city location and city size and explored the policy empowerment effect differences in construction of intellectual property demonstration cities in terms of digital transformation of enterprises, thus further revealing the external boundaries of the policy's impact on digital transformation of enterprises. This is conducive to understanding how macro-policies can "precisely irrigate" the micro-enterprise fields from the perspective of urban characteristics. Therefore, it is of great practical significance for the government to further improve the construction of intellectual property cities and consolidate the "new engine" function of institutional policies in promoting the development of the digital economy.

Key words:  intellectual property demonstration city, intellectual property protection, digital transformation of enterprise, difference-in-differences (DID) model