珠三角城市群经济联系的演变特征及影响因素探讨

赵亚博; 黄柳倩; 马世发; 范建红; 谢涤湘

doi:10.12052/gdutxb.210178

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

珠三角城市群经济联系的演变特征及影响因素探讨

更新时间：2026-05-27

- 珠三角城市群经济联系的演变特征及影响因素探讨
- A Discussion on Evolution Characteristics and Influencing Factors of the Economic Links in the Pearl River Delta Urban Agglomeration
- 广东工业大学学报 2022年39卷第3期页码：95-104
- 作者机构：
  
  1. 广东工业大学建筑与城市规划学院,广东,广州,510090
  2. 自然资源部城市国土资源监测与仿真重点实验室,广东,深圳,518034
- 作者简介：
  
  赵亚博(1988–)，男，讲师，博士，主要研究方向为城市与区域发展，E-mail：zhaoyabo3@163.com
  谢涤湘(1974–)，男，教授，博士，主要研究方向为城市社会文化地理学与城市规划，E-mail：xiedixiang@126.com
- 基金信息：
  
  国家自然科学基金资助项目(42101186, 42071176);自然资源部城市国土资源监测与仿真重点实验室开放基金资助课题(KF-2020-05-010);广东省自然科学基金资助项目(2019A1515011653);广州省社科规划“两区专项”项目(GD20SQ16)
- DOI：10.12052/gdutxb.210178
  中图分类号： TU984.2
- 网络首发：2022-05-10，
  
  纸质出版：2022
- 稿件说明：
移动端阅览
赵亚博, 黄柳倩, 马世发, 范建红, 谢涤湘. 珠三角城市群经济联系的演变特征及影响因素探讨[J]. 广东工业大学学报, 2022, 39(3): 95-104.

Zhao Ya-bo, Huang Liu-qian, Ma Shi-fa, et al. A Discussion on Evolution Characteristics and Influencing Factors of the Economic Links in the Pearl River Delta Urban Agglomeration[J]. 2022, 39(3): 95-104.
赵亚博, 黄柳倩, 马世发, 范建红, 谢涤湘. 珠三角城市群经济联系的演变特征及影响因素探讨[J]. 广东工业大学学报, 2022, 39(3): 95-104. DOI： 10.12052/gdutxb.210178.

Zhao Ya-bo, Huang Liu-qian, Ma Shi-fa, et al. A Discussion on Evolution Characteristics and Influencing Factors of the Economic Links in the Pearl River Delta Urban Agglomeration[J]. 2022, 39(3): 95-104. DOI： 10.12052/gdutxb.210178.

摘要

城市间频密的经济联系是城市群的重要特征，并随城市群发育程度的提升而增强。本文以我国发育程度最高的城市群之一−珠三角城市群为实证案例，基于改进的引力模型法、地理信息系统(Geographic Information System，GIS)和二次指派程序(Quadratic Assignment Procedure，QAP)分析法，结合社会经济数据，对2000~2019年城市间经济联系的演变特征进行了分析，并探讨了影响因素。研究发现：珠三角城市群经济联系强度不断提升，其中广州与其余各城市间的经济联系增量最多，深圳市的增幅最大；珠三角城市群经济联系方向呈现稳中有变的趋势，且各个城市的相对地位因此不断发生变化。经济距离差异、经济发展与城镇人口增长、产业分工与产业联系、政策推动是影响经济联系变化的主要原因。其中，经济距离差异是基本原因，与经济联系总量高度负相关；经济发展快慢与城镇人口增速是直接原因，与经济联系的增强保持同步性；产业发展与产业分工则是间接因素，与经济联系的变化具有正相关性；政策因素则是重要推手，在影响经济联系方面发挥着重要作用。本文研究有助于厘清近20年珠三角城市群经济联系的演变特征及影响因素，对制定促进城市群高质量发展的规划与政策具有一定启示意义。

Abstract

Economic link is an important form of interaction among cities

especially in urban agglomeration areas

and it is increasing with the development level of urban agglomerations. The present study takes the Pearl River Delta urban agglomeration as an empirical case

based on the improved gravity model method

GIS spatial analysis and QAP analysis

combines with social and economic data

analyzes the evolution characteristics of urban economic links in 2000~2019

and discusses the influencing factors. The main results are as follows: While the economic links of the Pearl River Delta urban agglomeration kept increasing constantly

Guangzhou has the largest increase in economic links with other cities

and Shenzhen has the largest increase; the direction of economic links variations in stability

and the relative position of cities in economic links are changing. Economic distance difference

economic development and urban population growth

industrial division and industrial links

and policy promotion are the main influencing factors of economic links. Among them

the difference in economic distance is the basic factor

and highly negatively correlated with the total amount of economic links; the speed of economic development and the urban population growth rate are the direct factors

and its growth is synchronized with the strengthening of economic links; industrial division and industrial links of labor are indirect factors

which have a positive correlation with changes in economic links; policy factors are important promoters and play an important role in influencing economic links. This study can help to clarify the evolution characteristics and influencing factors of the economic links in the Pearl River Delta urban agglomeration

and may have a certain reference for optimizing the urban links and promoting the improvement of urbanization quality.

关键词

Keywords

references

CHEN M X, YE C, ZHOU Y. Urbanization rate and its policy implications: discussion and development of northam’s curve [J]. Geographical Research, 2011, 30(8): 1499-1507.

ZHOU C S, WANG Y Q, XU Q Y, et al . The new process of urbanization in the Pearl River Delta [J ] . Geographical Research, 2019, 38(1): 45-63.

ZOU B. Practices, effects, and challenges of the inventory development pattern: the assessment and extended thoughts of urban renewal implementation in Shenzhen [J]. Urban Planning Review, 2017, 41(1): 89-94.

ZHAO Y B, ZANG P, ZHU X M. Latest developments in urban renewal research at domestic and abroad [J]. Urban Development Studies, 2019, 26(10): 42-48.

LIU X J, DERUDDER B, WU K. Measuring polycentric urban development in China: an intercity transportation network perspective [J]. Regional Studies, 2016, 50(8): 1302-1315.

CASTELLS M. Rise of the network society[M]. Oxford: Blackwell Publishers, 2000.

TAYLOR P J. Regionality in the world city network [J]. International Social Science Journal, 2010, 56(181): 361-372.

LI C F. Inter-regional connectivity—as a recent frontier of regional geography [J]. Acta Geographica Sinica, 1995, 50(6): 491-496.

HUANG J, LI J, ZHOU H, et al . Dynamic development of Wuhan metropolitan area based on urban connection [J ] . Planners, 2017, 33(1): 85-92.

WANG H J, ZHAI L J, LIU Y F, et al . Urban connection and function in Wuhan urban agglomeration based on multi-dimensional urban factor flows [J ] . Economic Geography, 2018, 38(7): 50-58.

NIU X Y, WANG Y, DING L. Measuring urban system hierarchy with cellphone signaling [J]. Planners, 2017, 33(1): 50-56.

SUN B D, ZHANG T L, WANG Y, et al . Are mega-cities wrecking urban hierarchies? a cross-national study on the evolution of city-size distribution [J ] . Cities, 2021, 108: 102999.

XU L Y, LI H. Network characteristics and mechanism of changes in urban spatial economic linkages: a case study of Pearl River Delta and Gulf of Tonkin [J]. Urban Problem, 2015(5): 20-26.

XIA C , ZHANG A Q, WANG H J, et al . Bidirectional urban flows in rapidly urbanizing metropolitan areas and their macro and micro impacts on urban growth: a case study of the Yangtze River middle reaches megalopolis, China [J ] . Land Use Policy, 2019, 82: 158-168.

WANG J Y, SONG W, LIU T Q. A study on urban network structure based on multi-source flow data, Jilin Province [J]. Planners, 2020, 36(2): 64-68.

HU G J, CHEN C M, JIN X X, et al . Research progress of networking of urban systems in China [J ] . Acta Geographica Sinica, 2019, 74(4): 681-693.

CHEN P Q, ZHENG T X. A road direction of Macao’s integration into the world airport group of the Greater Bay Area of Guangdong-Hong Kong-Macao [J]. Journal of Guangdong University of Technology, 2019, 36(6): 45-52.

SHI Q Q, KANG J J, LU F X, et al . Accessibility and urban economic linkages of counties in Shanxi Province [J ] . Progress in Geography, 2016, 35(11): 1340-1351.

LIU M, ZHAO X. The spatial network structure of urban agglomeration and its economic-coordinated development - based on the comparative analysis of the three urban agglomerations in the Yangtze River Economic Belt [J]. Inquiry into Economic Issues, 2019, 41(9): 100-111.

SHAO D. Spatial analysis on core-periphery urban contact of Guanzhong city clusters: a case study of Xi’an and Weinan [J]. Urban Development Studies, 2018, 25(7): 148-153.

ZHAO M X, DERUDDER B, HUANG J H. Examining the transition processes in the Pearl River Delta polycentric mega-city region through the lens of corporate networks [J]. Cities, 2017, 60: 147-155.

LIU J Z, GAO S Y. The research of Beijing-Tianjin-Hebei urban agglomerations’ spatial connection based on urban relation intensity and urban flow [J]. Areal Research and Development, 2013, 32(2): 57-61.

ZHAO D X, HAN Z L, ZHAO B. Spatial framework and change of the northeast China’s economic links [J]. Scientia Geographica Sinica, 2016, 36(6): 846-854.

XU J B, ZHAN Q, LIU C H, et al . The analysis spatial heterogeneity of Changsha-Zhuzhou-Xiangtan urban agglomeration based on economic relation and spatial flow [J ] . Economic Geography, 2015, 35(10): 36-43.

ZHENG W, XU W L, CHEN Y. Dynamic evolution of economic network within inter-regional urban agglomerations: based on the urban agglomerations of West Coast of Taiwan Straits, Yangtze River Delta and Pearl River Delta [J]. Economic Geography, 2019, 39(7): 58-66.

RUAN J E, CHEN Y B, QIAN Q L, et al . A multidimensional analysis of economic spatial pattern of Pearl River Delta urban agglomeration under the influence of high-speed railway [J ] . Journal of Geo-information Science, 2020, 22(5): 1023-1032.

ZHAO X. Urban economic interaction and industrial structure of urban agglomeration: an empirical study based on the data of Pearl River Delta urban agglomeration [J]. South Economic, 2016(10): 109-120.

DENG C Y. Industrial circle construction research of central PRD based on space link [J]. Modern Urban Research, 2009, 24(7): 75-81.

LI H J, LI S H. Gravity model based on spatial connection of urban agglomeration economies: an empirical study of the Pearl River Delta city group [J]. Journal of South China University of Technology (Social Science Edition), 2011, 13(1): 19-24.

ZHANG J Y, MAO Y H. An empirical analysis of spatial linkages in the Pearl River Delta economic zone [J]. Urban Problems, 2012(10): 2-8.

FANG C L. China’s urban agglomeration and metropolitan area construction under the new development pattern [J]. Economic Geography, 2021, 41(4): 1-7.

ZHOU Y X. Theory of the direction of major economic relations [J]. City Planning Review, 1998(2): 22-25.

MIAO C H, WANG H J. On the direction and intensity of urban economic contacts in Henan Province [J]. Geographical Research, 2006, 25(2): 222-232.

GAO P, HE D, NING Y M, et al . Community structure and proximity mechanism of city clusters in middle reach of the Yangtze River: based on producer service firms’ network [J ] . Scientia Geographica Sinica, 2019, 39(4): 578-586.

ZHANG R T. Urban Agglomeration spatial network structure spatial-temporal evolution in the Yangtze River Delta [J]. Economic Geography, 2017, 37(2): 46-52.

WANG F F, YANG H H. Study on network structure and influencing factors of urban agglomeration spatial economy in Guangdong-Hong Kong-Macao Greater Bay Area: based on network analysis method [J]. Journal of south China Normal University (Social Science Edition), 2018(4): 110-120.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

双模态迭代交叉注意力融合集成框架

基于AAGV-YOLOX模型的输电线路异物检测研究

具守恒量波动方程的循环双子网物理信息神经网络

SCA-YOLO: 基于可变形卷积与上下文感知注意力的实时目标检测

人工噪声辅助无人机太赫兹安全通信的鲁棒设计