地理学报 ›› 2021, Vol. 76 ›› Issue (4): 835-852.doi: 10.11821/dlxb202104005

• 城市研究 • 上一篇    下一篇

基于创新企业的中国城市网络联系特征

黄晓东1,2,3(), 马海涛4(), 苗长虹3   

  1. 1.华东师范大学城市与区域科学学院,上海 200241
    2.华东师范大学全球创新与发展研究院,上海 200062
    3.河南大学黄河文明与可持续发展研究中心,开封 475001
    4.中国科学院地理科学与资源研究所 中国科学院区域可持续发展分析与模拟重点实验室,北京 100101
  • 收稿日期:2019-10-16 修回日期:2020-09-24 出版日期:2021-04-25 发布日期:2021-06-25
  • 通讯作者: 马海涛(1979-), 男, 山东滕州人, 博士, 副研究员, 硕士生导师, 中国地理学会会员(S110008167M), 主要从事城市网络与创新研究。E-mail: maht@igsnrr.ac.cn
  • 作者简介:黄晓东(1993-), 男, 河南安阳人, 博士生, 研究方向为科技创新与城市发展。E-mail: 498325802@qq.com
  • 基金资助:
    国家自然科学基金项目(41971209);国家自然科学基金项目(41571151)

Connectivity characteristics for city networks in China based on innovative enterprises

HUANG Xiaodong1,2,3(), MA Haitao4(), MIAO Changhong3   

  1. 1. School of Urban and Regional Science, East China Normal University, Shanghai 200241, China
    2. Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China
    3. Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng 475001, Henan, China
    4. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2019-10-16 Revised:2020-09-24 Published:2021-04-25 Online:2021-06-25
  • Supported by:
    National Natural Science Foundation of China(41971209);National Natural Science Foundation of China(41571151)

摘要:

多部门创新企业的跨城布局能够增进城市间的知识流动与创新联系,大量创新企业部门关联构成的城市网络是理解国家创新格局的重要认知基础。本文运用1778家国家级创新企业部门关联数据和“总部—分支机构”方法建立中国城市间有向关系矩阵,借助社会网络分析、GIS技术及空间交互模型方法,对创新企业建构的中国城市网络联系特征进行分析。结果发现:① 基于创新企业的中国城市网络联系覆盖广但极不均质,菱形联系格局在次级网络中逐步显现,京津冀、长三角和珠三角城市群是网络联系的核心枢纽。② 城市间创新企业流具有明显的行政中心指向特征与省级边界效应,直辖市及省会城市对创新企业流具有较强吸引力,北京是网络联系最强核心,上海和深圳次之。③ 城市网络区域异质性突出,东部区域“内联外控”与中、西部区域“内弱外强”的联系格局呈现鲜明对比,东部区域内沿海三大城市群网络的联系结构也存在较大差异。④ 城市的行政等级、经济水平和创新环境等属性指标,以及城市间地理、技术、制度的邻近性关系指标,都对城市吸收和输出创新企业流产生了不同程度的影响,外资并不利于促进中国城际创新企业流和网络的形成。

关键词: 创新企业, 城市网络, 协同创新, 创新格局, 中国

Abstract:

Improving the connectivity of multi-sector enterprises at a cross-regional level can enhance knowledge and technology transfer and stimulate innovation and synergies among cities. Therefore, the study of city networks, which comprise a large number of multi-sector enterprises, can provide an important knowledge base for innovation and development at the regional and national levels. Based on an evaluation of innovative enterprises in China by authoritative institutions, data were collected on 1778 multi-sector enterprises, which included details on the headquarters, the branches (a total of 30,625) and the locations. A city-based network for the country was established, using the data for the multi-sector linkages and a model for the headquarters-branches, to explore the network connectivity characteristics via social network analysis, the GIS method and the spatial interactive model. The results showed that (1) although the network covered 353 cities across China, the spatial distribution of the network was extremely uneven. For instance, a diamond-shaped connectivity pattern emerged gradually as the network hierarchy decreased. The Beijing-Tianjin-Hebei region, the Yangtze River Delta and the Pearl River Delta were found to be the three key hubs of the network. (2) The intercity linkages between innovative enterprise sectors (innovative enterprise flows), had a clear administrative center and a provincial boundary effect. Moreover, the innovative enterprises were strongly attracted to the municipalities and provincial capitals. Beijing was at the heart of the network, followed by Shanghai and Shenzhen. (3) Differences existed in regional connectivity. There was a striking difference between the eastern region and the central-western region. The former had a high connectivity with respect to both the internal and the external networks, while the latter had lower connectivity for the internal network but a higher connectivity at the external level. At the same time, although the network structures for all the three eastern megalopolises showed strong cohesion, their connectivity characteristics were quite different. (4) The input and output of innovative enterprise flows were to varying degrees influenced by the indicator attributes for each city, and these in turn were related to the administrative hierarchy, the economic strength and the innovative environment of the region, as well as proximity indicators, which were related to geographical, technological and institutional factors. Foreign capital was not conducive to innovative enterprise flows and to the formation of innovative intercity company-based networks in China.

Key words: innovative enterprise, city network, collaborative innovation, innovation pattern, China