| 摘要: |
| 突破性技术创新需要组织、配置、利用多领域的知识资源，大数据应用可以从知识多元化和吸收能力等方面优化企业知识资源，进而促进企业突破性技术创新。采用沪深A股上市公司2009—2023年的数据分析发现：大数据应用显著提升了企业突破性技术创新水平，并通过推动知识多元化和提高知识吸收能力两条路径促进企业突破性技术创新；地区知识产权保护强度提高弱化了大数据应用对企业突破性技术创新的促进作用，该调节效应仅在竞争性行业中显著；大数据应用对突破性技术创新的促进作用，在竞争性行业比管制性行业更显著，在国有企业、知识多元化水平较高企业、非高科技行业企业、东部和市场化水平较高地区企业中显著，在非国有企业、高科技行业企业、中西部和市场化水平较低地区企业中不显著，在知识多元化水平较低企业中则表现为负向影响。因此，应加快推进大数据应用，着力提升企业知识多元化水平和知识吸收能力，构建兼顾知识流动与创新激励的动态知识产权保护体系，有效促进企业突破性技术创新。 |
| 关键词: 大数据应用 突破性技术创新 知识资源 知识多元化 知识吸收能力 知识产权保护强度 |
| DOI： |
| 分类号: |
| 基金项目: |
|
| Impact of Big Data Applications on Enterprises’ Breakthrough Technological Innovation: The Path of Optimizing Knowledge Resources and the Regulatory Role of Intellectual Property Protection |
|
WANG Jun, ZHOU Xiao-yu
|
|
School of Economics and Management, China University of Petroleum (East China), Qingdao 266580, Shandong, China
|
| Abstract: |
| The deep integration of big data applications and breakthrough technological innovation is pivotal to advancing China’s national big data strategy. Through the application of big data, enterprises can enhance their dynamic construction capabilities, improve synergy effects, and build a sustainable competitive advantage. This creates opportunities for breakthrough technological innovation and contributes to the development of new quality productive forces, carrying significant economic and practical significance. However, few studies have explored this from the perspectives of knowledge diversity and knowledge absorption capacity. Based on panel data from Shanghai and Shenzhen A-share listed companies spanning 2009 to 2023, this study adopts a resource orchestration perspective to theoretically and empirically investigate how big data applications affect enterprises’ breakthrough technological innovation. The findings reveal that big data applications significantly drive breakthrough technological innovation, with conclusions remaining robust after comprehensive endogeneity and robustness tests. Two mediating pathways are identified: enhancing enterprises’ knowledge diversity and improving knowledge absorption capabilities. Heterogeneity analyses further reveal that the positive effect is more pronounced among state-owned enterprises, enterprises with higher levels of knowledge diversity, those located in eastern China or provincial capitals, and enterprises operating in competitive or non-high-tech industries. Additionally, the intensity of intellectual property protection has a negative moderating effect in the process of big data applications promoting enterprises’ breakthrough technological innovation. Compared with previous studies, this study makes two expansions. First, in terms of research objects, it distinguishes itself from traditional innovation methods, classifies innovation into detailed categories, incorporates big data applications and breakthrough technological innovation into a unified research framework, and deeply explores the value impact and internal transmission mechanism of enterprises’ big data applications, filling the research gap on breakthrough technological innovation in big data applications. Second, in terms of research level and mechanism, it focuses on the micro-level of enterprises, embeds knowledge diversity and knowledge absorption capacity into the research framework of the relationship between big data applications and breakthrough technological innovation, and explores the influence mechanism of big data applications, or the underlying mechanism of digitalization, on breakthrough technological innovation, providing a new perspective for research and deeply revealing the fundamental reasons affecting enterprises’ breakthrough technological innovation. This study sheds light on the internal logic between enterprises’ big data applications and achieving breakthrough technological innovation, which is conducive to the government departments formulating more targeted big data development strategies, providing personalized policy support for different types of enterprises, and better guiding enterprises to achieve breakthrough technological innovation. |
| Key words: big data application breakthrough technological innovation knowledge resource knowledge diversity knowledge absorption capacity intensity of intellectual property protection |
