地球信息科学学报 ›› 2023, Vol. 25 ›› Issue (1): 223-238.doi: 10.12082/dqxxkx.2023.220676

• 地理空间分析综合应用 • 上一篇    

上市公司与客户联系视角下的中国城际网络结构时空演化研究

陈刚1,2(), 王光辉3,*(), 郑满茵2   

  1. 1.澳门科技学大学可持续发展研究所,澳门 999078
    2.肇庆学院,肇庆 526061
    3.中国科学院科技战略咨询研究院,北京 100190
  • 收稿日期:2022-09-09 修回日期:2022-11-17 出版日期:2023-01-25 发布日期:2023-03-25
  • 通讯作者: 王光辉(1987— ),男,山东烟台人,博士,副研究员,主要从事舆情网络、区域经济方面的研究。E-mail: wangguanghui@casisd.cn
  • 作者简介:陈刚(1988— ),男,湖北潜江人,博士生,主要从事区域可持续发展、城市网络方面的研究。E-mail: chengang0082006@163.com
  • 基金资助:
    国家自然科学基金项目(71974182);广东省大学生“攀登计划”科技创新培育项目(pdjh2022bo561);肇庆学院大学生创新创业项目(X202110580115)

Research on the Spatiotemporal Evolution of China's Intercity Network Structure from the Perspective of the Relationship between Listed Companies and Customers

CHEN Gang1,2(), WANG Guanghui3,*(), ZHENG Manyin2   

  1. 1. Institute of Sustainable Development, Macau University of Science and Technology, Macau 999078, China
    2. Zhaoqing University, Zhaoqing 526061, China
    3. Institutes of Science and Deveploment, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2022-09-09 Revised:2022-11-17 Online:2023-01-25 Published:2023-03-25
  • Contact: WANG Guanghui
  • Supported by:
    National Natural Science Foundation of China(71974182);Guangdong University Students' "Climbing Plan" Science and Technology Innovation Cultivation Project(pdjh2022bo561);Innovation and Entrepreneurship Project of Zhaoqing University(X202110580115)

摘要:

企业间的联系是城市联系的重要组成部分,加强对基于企业间联系的城市功能网络分析对丰富城市网络理论研究具有重要意义。采用2010—2020年上市公司与其前五大客户间的贸易关系数据构建了中国城市网络,基于企业间的贸易联系视角分析城市网络时空演变特征。研究表明:① 2010—2020年间城市网络规模呈现先升后降的特征,整体网络密度较低,位于0.014~0.018之间;网络重心呈现“S”形空间轨迹变化和整体向南移动的趋势,网络总体空间结构由沿海向“T”形结构转变; ② 网络流量集中于少数节点城市,资金进出量前20城市总额占资金总流量的71.9%,北京、上海是网络的绝对核心,杭州、武汉、深圳、广州等省会或副省级城市承担着区域中心的功能,佛山、齐齐哈尔、南通等制造业发达城市是重要节点;③ 五大城市群中珠江三角洲网络密度最高,位于0.324~0.334之间,长江三角洲贸易总流量最高,为783.5亿元,长江中游城市群和成渝城市群网络发育相对滞后;④ 新冠疫情对整体网络的贸易流量和网络结构产生了明显影响,网络社团进一步分化重组,广州—深圳社团明显增强,上海社团明显减弱。研究结果对推动国内大循环和统一大市场建设具有一定的参考价值。

关键词: 上市公司, 客户关系, 要素流动, 复杂网络, 城际网络, 时空演化, 城市群, 国内大循环

Abstract:

The connection between enterprises is an important part of urban connection. Strengthening the analysis of urban functional network based on the connection between enterprises is of great significance to enrich the theoretical research of urban network. Based on the trade relationship data between listed companies and their top five customers from 2010 to 2020, this paper constructs China's urban network, and analyzes the spatio-temporal evolution characteristics of urban network based on the perspective of trade links between enterprises. The research shows that: ① From 2010 to 2020, the urban network scale shows the characteristics of first rising and then falling, and the overall network density is low, ranging from 0.014 to 0.018. The center of gravity of the network presents the trend of "S" - shaped spatial trajectory change and overall southward movement.This feature is consistent with the trend of China's economic center moving southward in recent years. The overall spatial structure of the network changes from coastal to "T" - shaped structure. This feature is consistent with the "T" strategy of China's land development. ② The network traffic is concentrated in a few node cities. The total amount of capital in and out of the top 20 cities accounts for 71.9% of the total capital flow. Beijing and Shanghai are the absolute core of the network. The provincial capitals or sub provincial cities such as Hangzhou, Wuhan, Shenzhen and Guangzhou assume the function of regional centers. Foshan, Qiqihar, Nantong and other manufacturing developed cities are important nodes. It indicates that trade links are more likely to occur in cities with high administrative levels or developed industries. ③ The Pearl River Delta has the highest network density, which is between 0.324 and 0.334. The Yangtze River Delta has the highest total trade flow, which is 78.35 billion yuan. Although the networking level of urban agglomeration in the middle reaches of the Yangtze River and Chengdu Chongqing urban agglomeration is relatively low, they have become an important force to promote the evolution of network structure. ④ The COVID-19 has had a significant impact on the trade flow and network structure of the overall network. The network associations have been further divided and reorganized. The Guangzhou Shenzhen associations have been significantly strengthened. It shows that Guangzhou and Shenzhen have a strong combination effect. The Shanghai associations have been significantly weakened. The research results have a certain reference value for promoting the construction of domestic big cycle and unified big market.

Key words: listed company, customer relationship, factor flow, complex network, intercity network, spatiotemporal evolution, urban agglomeration, domestic economic cycle