地理学报 ›› 2019, Vol. 74 ›› Issue (4): 694-709.doi: 10.11821/dlxb201904006

• 人口与城镇化研究 • 上一篇    下一篇

基于财富500强中国企业网络的城市网络空间联系特征

赵新正1,2,3(), 李秋平1, 芮旸1,2,3, 刘晓琼1,2,3(), 李同昇1,2,3   

  1. 1. 西北大学城市与环境学院,西安 710127
    2. 陕西省地表系统与环境承载力重点实验室,西安 710127
    3. 陕西省情研究院,西安 710127
  • 收稿日期:2017-10-30 修回日期:2019-03-11 出版日期:2019-04-25 发布日期:2019-04-23
  • 作者简介:

    作者简介:赵新正(1983-), 男, 河南安阳人, 博士, 副教授, 主要从事城市地理研究。E-mail: xzzhao@nwu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41401184, 41329001);福特基金(0155-0883);教育部人文社会科学青年基金项目(14YJCZH222);陕西省教育厅项目(14JK1753)

The characteristics of urban network of China: A study based on the Chinese companies in the Fortune Global 500 list

Xinzheng ZHAO1,2,3(), Qiuping LI1, Yang RUI1,2,3, Xiaoqiong LIU1,2,3(), Tongsheng LI1,2,3   

  1. 1. College of Urban and Environmental Science, Northwest University, Xi'an 710127, China
    2. Key Laboratory of Earth Surface System and Environmental Carrying Capacity of Shaanxi Province, Northwest University, Xi'an 710127, China
    3. Shaanxi Institute of Provincial Resource, Environment and Development, Xi'an 710127, China
  • Received:2017-10-30 Revised:2019-03-11 Online:2019-04-25 Published:2019-04-23
  • Supported by:
    National Natural Science Foundation of China, No.41401184, No.41329001;Ford Foundation, No.0155-0883;MOE Project of Humanities and Social Sciences, No.14YJCZH222;Natural Science Foundation of MOE in Shaanxi, No.14JK1753

摘要:

基于2015年世界财富500强中的102家中国企业数据,根据企业组织特征构建了反映企业—城市间关联的折衷网络模型,借助网络分析等多种方法分析了中国地级城市间和典型城市群之间的网络联系。研究发现:① 城市网络总体连通性较差、向心集中性强,发育不够完备;城市网络连接具有明显的行政中心指向、沿海指向和资源指向;网络节点城市对外经济依赖度高,网络结构扁平特征明显。城市群网络存在权力分散、地位分化和外部联系依赖特征。② 城市网络中省域、城市群和俱乐部边界效应明显,区域内外的中心城市规模和数量对省域行政区经济、城市群经济和俱乐部经济的发展产生影响。③ 城市在多尺度网络中的功能分化明显,大城市和区域型中心城市比中小城市拥有更加完备和均衡的功能体系。沿海三大城市群的辐射带动作用明显,其他城市群的优势功能有待突出。④ 城市(群)跨尺度区域功能互动效应显著,城市(群)的自我经济集聚能力与城市(群)的对外辐射带动功能之间存在密切的正向关系。研究为城市网络模型拓展及理解中国城市网络空间联系特征提供了支撑。

关键词: 折衷网络模型, 城市网络, 跨尺度关联, 边界效应

Abstract:

Based on the data of Chinese enterprises that entered the Fortune 500 list in 2015, this paper uses the eclectic model to construct the inter-city association network. Using the network analysis method, the spatial connection characteristics of 311 inter-city networks at prefecture level and above and 20 urban agglomerations networks in China are examined respectively. The research found that: (1) The overall connectivity of urban network is poor, the centripetal concentration is strong, and the network is not complete. The urban network connection shows a strong tendency of political center cities directivity, coastal cities directivity as well as resource-based cities directivity. The external economic dependence of each node city in the urban network is high, and the urban network structure has obvious flattening characteristics. The network of urban agglomerations is characterized by decentralization of power, differentiation of status and dependence on external connections. (2) The boundary effect of provinces, urban agglomerations and urban agglomerations clubs in the urban network is significant. The network evolution process is influenced by the provincial administrative district economy, the urban agglomerations economy and the urban agglomerations club economy. The size and number of central cities in the region and its surrounding areas have an impact on the provincial administrative district economy, the city agglomerations economy and the urban agglomerations club economy. (3) The function of cities is obviously divided in a multi-scale network. The large cities and regional central cities have a complete and more balanced function system than the small and medium-sized cities do. The radiation effect of three major urban agglomerations in coastal China is significant, while the dominant function of other urban agglomerations needs to be strengthened. (4) The cross-scale regional functional interaction effect of cities (clusters) is significant. The radiation-driven function of cities (clusters) is positively related to their self-agglomeration capabilities. This study provides support for the understanding of urban network model expansion and the spatial relation of urban network in China.

Key words: eclectic mode, urban network, trans-scale correlation, boundary effects