• 中国科学学与科技政策研究会
  • 中国科学院科技政策与管理科学研究所
  • 清华大学科学技术与社会研究中心
ISSN 1003-2053 CN 11-1805/G3

科学学研究 ›› 2024, Vol. 42 ›› Issue (9): 1967-1978.

• 技术创新与制度创新 • 上一篇    下一篇

国际科技创新中心发展模式的聚类分析与比较

陈玲1,孙君1,孔文豪2,汪佳慧1,3   

  1. 1. 清华大学公共管理学院;清华大学产业发展与环境治理研究中心
    2. 清华大学公共管理学院
    3.
  • 收稿日期:2023-04-25 修回日期:2024-01-29 出版日期:2024-09-15 发布日期:2024-09-15
  • 通讯作者: 孔文豪
  • 基金资助:
    北京市政府委托项目《国际科技创新中心指数2022研究》;北京市哲学社会科学重大项目《北京建设国际科技创新中心研究》;清华大学自主科研项目《新一代信息技术产业的创新生态系统培育研究》

Cluster analysis and comparison of development modes of Global Innovation Hubs

  • Received:2023-04-25 Revised:2024-01-29 Online:2024-09-15 Published:2024-09-15

摘要: 国际科技创新中心发展模式是对区域科技创新制度历史与实践活动的抽象总结。识别与比较国际科技创新中心的发展模式是挖掘区域创新规律、定位区域特色发展战略的必要抓手。本文基于历时三年、多达十余轮的专家论证,遴选了31项衡量区域科技创新能力的特征指标,采用聚类分析,对全球100个城市(都市圈)的发展模式进行识别与系统比对。研究发现,国际科技创新中心具有10类差异化的发展模式,其中我国城市集中分布于3类科技创新中心模式,分别为:全能冠军型、创新高地型和成长型。发展模式的识别帮助我国科技创新中心准确定位在全球创新网络中的生态位与对标城市,为我国建成具有全球影响力的科技创新中心提供实证支撑与决策参考。

Abstract: Global Innovation Hubs are centers that emerge as a result of the extensive development and geographical diffusion of science and technology innovation activities, serving as crucial nodes within the global innovation network. The development modes of these hubs represent abstract summaries of the historical evolution and practical implementation of regional science and technology innovation systems. Identifying and comparing these modes is an essential starting point for uncovering regional innovation patterns and formulating targeted development strategies. Previous studies have primarily examined Global Innovation Hubs from the perspective of their temporal dynamics in historical evolution and spatial positioning within the global innovation network. This study aims to further enhance our understanding by exploring the diversity of regional innovation modes, thereby unraveling various developmental paths embedded within different points across the global innovation network. Through more than 10 rounds of expert deliberation spanning three years, this paper selects 31 characteristic indicators to assess regional scientific research capability, innovative economy, and innovative ecology. Using the two-stage K-means clustering method, this study identifies and systematically compares the development patterns of 100 global cities (metropolitan areas). The findings reveal that Global Innovation Hubs exhibit ten distinct types of differentiated development modes: all-around champion hub, international financial hub, ecological hub, knowledge hub, data-driven hub, innovation highland hub, developing hub, international communication hub, growing hub, and quality hub. Notably among them are Chinese cities which predominantly fall into three modes: Beijing and the Guangdong-Hong Kong-Macao Greater Bay Area are the all-around champion hubs; Shanghai is the innovation highland hub; while 15 other cities (metropolitan areas) including Hangzhou, Nanjing and Wuhan are the growing hubs. This study primarily focuses on analyzing these three types of Global Innovation Hubs including China cities. It is observed that they possess distinctive characteristics as follows: Firstly, all-around champion hubs attract top scientific talents worldwide along with leading institutions and facilities. They dominate global frontier technological innovations as well as cooperation networks while connecting with a global technology ecosystem subsystem. Moreover they gather high-tech enterprises globally with outstanding entrepreneurial ecological advantages. Secondly, innovation highland hubs emerge as prominent hubs for emerging technologies and industries at a global level, by fostering strong industry-university-research alliances alongside industrial parks formation where government plays an instrumental role in shaping regional industrial clusters. Thirdly, growing hubs are regional economic growth poles, driving and radiating science and technology innovation activities in the region and its surrounding small satellite cities. However, due to limited scientific knowledge accumulation and technological history, these hubs still function as secondary nodes within the global innovation network. The research findings contribute a novel empirical approach and data foundation for the systematic identification and comparison of Global Innovation Hubs. Moreover, the inclusion of emerging cities (metropolitan areas) such as Beijing and the Guangdong-Hong Kong-Macao Greater Bay Area provides compelling evidence to elucidate the evolution of global innovation geography, particularly highlighting China's ascent as an emerging scientific and technological powerhouse. Furthermore, this study enhances the understanding of Global Innovation Hubs by exploring diverse regional innovation modes. The conclusion reveals ten distinct development models that further substantiate how regions can formulate their own "regional formula" for science, technology, innovation, and industrial advancement based on their unique knowledge base and innovation resources. Identifying development modes can assist China's Global Innovation Hubs in accurately positioning their niche and benchmark city within the global innovation network, providing empirical support and decision-making references for establishing Global Innovation Hubs in China.