科研管理 ›› 2024, Vol. 45 ›› Issue (3): 113-121.DOI: 10.19571/j.cnki.1000-2995.2024.03.012

• 论文 • 上一篇    下一篇

高技术产业集聚对区域阶段创新绩效的影响研究

徐丹1,2,于渤2   

  1. 1.济南大学商学院,山东 济南250024;
    2.哈尔滨工业大学经济与管理学院,黑龙江 哈尔滨150001
  • 收稿日期:2022-09-02 修回日期:2023-09-25 出版日期:2024-03-20 发布日期:2024-03-11
  • 通讯作者: 于渤
  • 基金资助:
    国家社会科学基金重点项目:“黑龙江老工业基地创新驱动发展与结构调整问题研究”(16AZD006,2016—2021)。

Research on agglomeration of high-tech industries on the staged innovation performance of regions

Xu Dan1,2, Yu Bo1   

  1. 1. Business School, University of Jinan, Jinan 250024, Shandong, China;
    2. School of Economics and Management, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China
  • Received:2022-09-02 Revised:2023-09-25 Online:2024-03-20 Published:2024-03-11
  • Contact: Bo Yu

摘要:     高技术产业集聚是地区突破发展瓶颈,开辟创新增长赛道的关键支撑,也是赋能区域创新发展的内在动力。立足创新价值链视角,基于组态思维运用模糊集定性比较分析方法(fsQCA),以我国30省份为研究对象,探究在区域创新基础及环境的协同作用下,专业化与多样化高技术产业集聚对区域知识生产、技术研发与成果转化三阶段创新绩效的复杂影响机制与差异化作用路径。研究发现:(1)驱动知识生产与技术研发绩效提升路径包括“多样化高技术产业集聚主导型”“环境支持下要素拉动型”以及“综合驱动型”三类;(2)驱动成果转化绩效提升路径包含“专业化高技术产业集聚主导型”“开放环境下专业化集聚-创新基础协同型”“环境支持下要素拉动型”以及“政府引导下研发人员弥补型”四类;(3)三阶段区域创新驱动路径的差异性在于不同高技术产业集聚类型及研发人员是否发挥核心作用;(4)东部地区与中西部地区各阶段创新绩效提升路径呈现不同特点,体现为核心主导要素的差异化激励效应。本文研究结论有助于打开高技术产业集聚对区域创新过程作用机制的“黑箱”,为我国各地区寻求更适配的阶段化创新路径提供实践参考。
关键词

关键词: 高技术产业专业化集聚, 高技术产业多样化集聚, 区域三阶段创新绩效, 组态分析

Abstract:     High-tech industry agglomeration is the key support for the regions to break through the development bottleneck and establish the growth track of innovation, as well as the inner dynamics to empower regional innovation. Based on the perspective of innovation value chain, this paper took 30 provincial-level regions in China as the research samples, and applied the fuzzy set qualitative comparative analysis (fsQCA) method to test. We focused on exploring the multiple paths of specialized agglomeration and diversity agglomeration of high-tech industries to improve the performance of knowledge production, technology development and innovation commercialization under the coordination of regional innovation foundation and innovation environment. Furthermore, we deeply discussed the difference and location heterogeneity of these paths. The results found that: (1) The paths driving the improvement of knowledge production performance and technology development performance include the high-tech industry diversity agglomeration-led type, the factor-pulling and environment-supported type and the comprehensively-driven type. (2) The improvement path of regional innovation commercialization performance can be identified as the high-tech industry specialization agglomeration-led type, the specialized agglomeration-innovation founded and environment-supported type, the factor-pulling and environment-supported type and the government-guided and R&D personnel compensated type. (3) Differences in three stages of regional innovation paths lie in the different types of high-tech industry agglomeration and the core role of R&D personnel. (4) The paths of innovation performance improvement at three stages in the eastern areas and the central and western regions showed different characteristics, which are reflected in the differentiated incentive effects of the dominant elements. The findings will help to open the black box of the influence mechanism of high-tech industry agglomeration on the regional innovation process, and provide practical insights for regions to seek for suitable innovation paths.

Key words: specialized agglomeration of high-tech industries, diversified agglomeration of high-tech industries, three-staged innovation performance of regions, configuration analysis