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地理科学进展 >

2025 , Vol. 44 >Issue 7: 1351 - 1363

DOI: https://doi.org/10.18306/dlkxjz.2025.07.003

研究论文

中国城市数字经济投资网络演变特征与驱动因素

  • 骆康 , 1 ,
  • 郭庆宾 , 1, * ,
  • 刘海猛 2 ,
  • 童昀 3
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  • 1.海南大学国际商学院，海口 570228
  • 2.中国科学院地理科学与资源研究所，北京 100101
  • 3.海南大学国际旅游与公共管理学院，海口 570228
* 郭庆宾(1984—)，男，山东日照人，教授，博士生导师，主要从事经济地理与区域发展研究。E-mail:

骆康(1993—)，男，湖北蕲春人，博士，副教授，博士生导师，主要研究方向为数字经济与城市群网络等。E-mail:

收稿日期: 2024-12-16

  修回日期: 2025-05-01

  网络出版日期: 2025-07-25

基金资助

国家自然科学基金项目(42461024)

海南省自然科学基金项目(725QN274)

海南省高等学校科学研究项目(Hnky2025-3)

海南大学科研启动项目(KYQD(SK) 2423)

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Change and driving factors of digital economy investment network in Chinese cities

  • LUO Kang , 1 ,
  • GUO Qingbin , 1, * ,
  • LIU Haimeng 2 ,
  • TONG Yun 3
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  • 1. International Business School, Hainan University, Haikou 570228, China
  • 2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 3. College of International Tourism and Public Administration, Hainan University, Haikou 570228, China

Received date: 2024-12-16

  Revised date: 2025-05-01

  Online published: 2025-07-25

Supported by

National Natural Science Foundation of China(42461024)

Natural Science Foundation of Hainan Province(725QN274)

Scientific Research Project of Higher Education Institutions in Hainan Province(Hnky2025-3)

Research Start-up Project of Hainan University(KYQD(SK) 2423)

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摘要

数字经济是新型生产力的重要载体，也是城市优质发展的新生动力，探索其投资网络格局和机制，对于加快数字要素流动和精准布局具有十分重要的意义。论文采用股权穿透方法获取企查查数据平台2000—2020年中国334个城市152万多条企业投资数据，进而运用加权中心度、优势流、二次指派程序(quadratic assignment procedure，QAP)等方法从“节点—路径—社群”多层次分析中国城市数字经济投资网络的演变特征和驱动因素。研究表明：(1) 北京、上海、深圳、南京等城市辐射带动作用显著，数字经济各行业投资存在高—高、低—低集聚现象，偏远地区存在网络边缘化困境；(2) 数字经济投资路径呈现多极化，且各行业路径不断重构，京津冀、长三角、珠三角等地区“领头羊”效应明显；(3) 数字经济产业投资网络呈现社群化和区域化特征，网络拓展蔓延态势明显，具有爆发式增长特点；(4) 各变量作用效果因时因地而异，经济发展、产业结构高级化、信息化、城市化等水平相近巩固了数字经济投资网络联系，而人力资本和科技创新水平差异则强化了这一关系。

关键词： 数字经济; 投资网络; 驱动因素; 优势流; 大数据

本文引用格式

骆康 , 郭庆宾 , 刘海猛 , 童昀 . 中国城市数字经济投资网络演变特征与驱动因素[J]. 地理科学进展, 2025 , 44(7) : 1351 -1363 . DOI: 10.18306/dlkxjz.2025.07.003

Abstract

The digital economy is an important carrier of new productivity and a new driving force for high-quality urban development. Exploring its investment network pattern and mechanism is of great significance for accelerating the flow and accurate layout of digital elements. This study used the equity penetration method to obtain the investment data of more than 1.52 million enterprises in 334 cities in China from 2000 to 2020, and then used the weighted centrality, dominant flow, and quadratic assignment procedure (QAP) methods to analyze the characteristics of change and driving factors of the investment network of China's urban digital economy from the node-path-community levels. The findings are as follows: 1) Beijing, Shanghai, Shenzhen, and Nanjing played a significant role in driving the radiation; investment in various sectors of the digital economy showed a high-high, low-low concentration, and remote areas faced the problem of network marginalization. 2) Investment path of the digital economy showed multipolarization, the path of various industries was constantly restructured, and the "leadership" effect of the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta was obvious. 3) Digital economy industrial investment network presented the characteristics of community and regionalization, and the network expansion and spread was clear, with the characteristics of explosive growth. 4) The effects of various variables varied with time and space. Similarity in economic development, advanced industrial structure, informatization, and urbanization consolidated the network connection of digital economy investment, while differences in human capital and scientific and technological innovation also strengthened this relationship.

Key words： digital economy; investment network; driving factors; dominant flow; big data

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