科研管理 ›› 2024, Vol. 45 ›› Issue (11): 47-56.DOI: 10.19571/j.cnki.1000-2995.2024.11.005

• 论文 • 上一篇    下一篇

资源价值视角下网络位置对区域创新绩效的影响研究

苏屹1,梁德智1,孙笑明2   

  1. 1.哈尔滨工程大学经济管理学院,黑龙江 哈尔滨150001;
    2.西安建筑科技大学管理学院,陕西 西安710055
  • 收稿日期:2023-09-14 修回日期:2024-08-15 出版日期:2024-11-20 发布日期:2024-11-12
  • 通讯作者: 苏屹
  • 基金资助:
    国家社会科学基金重大项目:“新型举国体制下技术突破的市场机制和政策路径研究”(21&ZD122,2022—2026);国家自然科学基金项目:“空间关联视角下知识源化对区域创新生态系统共生的影响效应研究”(72074059,2021—2024);中央高校基本科研业务费专项资金(3072021GIP0901,2021—2023)。

Research on the impact of network position on regional innovation performance from the perspective of resource values

Su Yi1, Liang Dezhi1, Sun Xiaoming2   

  1. 1. School of Economics and Management, Harbin Engineering University, Harbin 150001, Heilongjiang, China; 
    2. School of Management, Xi′an University of Architecture and Technology, Xi′an 710055, Shaanxi, China
  • Received:2023-09-14 Revised:2024-08-15 Online:2024-11-20 Published:2024-11-12
  • Contact: Su Yi

摘要:     提高区域创新绩效是增强国家创新体系效能的重要实现路径。网络位置对创新绩效错综复杂的影响作用也一直是学者关注的焦点。本文利用知识基础观弥补网络位置理论对资源价值关注不足的局限性,以差异化知识基础衡量资源价值,采用负二项回归模型和中国2001年至2020年跨区域合作专利数据实证检验网络位置、差异化知识基础和区域创新绩效的关系。研究发现:用结构洞和中心度衡量网络位置,结构洞与区域创新绩效呈“U型”曲线关系,且与差异化知识基础的交互效应显著;中心度与区域创新绩效呈“倒U型”曲线关系,与差异化知识基础的交互效应不显著;差异化知识基础正向促进区域创新绩效。政府应该通过鼓励创新主体紧密合作、促进产业结构多元化、建立创新绩效评估机制等措施推动区域创新绩效长效提升。本研究从资源价值视角丰富了网络位置与区域创新绩效关系的研究,为各地区如何利用跨区域合作赋能区域创新高质量发展提供重要政策启示。

关键词: 网络位置, 差异化知识基础, 区域创新绩效, 知识基础观, 交互效应

Abstract:    As an important part of national innovation, improving regional innovation performance is of great significance in enhancing the effectiveness of the national innovation system and supporting new breakthroughs in high-quality economic development. The intricate influence of network position on innovation performance has always been the focus of scholar′s attention, and previous studies have found that network position has a facilitating, inhibiting and nonlinear relationship on innovation performance. To bridge the gap between the theories, an attempt is made to deepen the understanding of the relationship between network position and differentiated knowledge base on regional innovation performance using the knowledge base view. For the network position theory, drawing on the knowledge base view literature that "heterogeneous knowledge is more valuable", we measured the scale of knowledge value in the network from the perspective of heterogeneous knowledge and incorporated the knowledge value into the research framework of network position and regional innovation performance. For the theory of differentiated knowledge base, we constructed indicators of "differentiated knowledge base" based on the network perspective and the view of knowledge bases and established the "relevant" relationship with external knowledge to enrich the research on relevant diversification in differentiated knowledge base.Based on Chinese patent data, the panel negative binomial regression method was used to analyze the non-linear effects and interactions of network position and differentiated knowledge base on regional innovation performance. The study found that: (1) structural hole has a "U-shaped" curve relationship with regional innovation performance, and the interaction effect with differentiated knowledge base is significant; (2) centrality has an "inverted Ushaped" curve relationship with regional innovation performance, and the interaction effect with differentiated knowledge base is not significant; and (3) differentiated knowledge base positively promote regional innovation performance. The significant difference between the interaction effects of network position and differentiated knowledge base on regional innovation performance suggests that the impact of the value of resources acquired through network position on regional innovation performance cannot be ignored.The study has offered several insights. First, when formulating regional innovation policies, the government should consider the network position between regions and its impact on innovation performance. Encouraging interregional firms and academic institutions to strengthen ties and moderately increase regional centrality in the network can enhance innovation. Second, the government should view the differentiated knowledge base as a key driver of innovation. By diversifying the industrial structure and creating open innovation platforms, regions can integrate diverse knowledge and resources, thus boosting innovation. Lastly, a comprehensive innovation performance evaluation mechanism should be established. Monitoring and optimizing the network position and knowledge base can lead to overall regional innovation improvement.

Key words: network position, differentiated knowledge base, regional innovation performance, knowledge-based view, interaction effect