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2022 , Vol. 45 >Issue 1: 277 - 286

DOI: https://doi.org/10.12118/j.issn.1000–6060.2021.162

区域发展

关中平原城市群经济联系网络结构演变及对经济增长影响研究

  • 叶珊珊 ,
  • 曹明明 ,
  • 胡胜
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  • 1.西北大学城市与环境学院,陕西 西安 710127
    2.陕西省发展和改革研究中心,陕西 西安 710016
叶珊珊（1985-）,女,副研究员,博士研究生,主要从事区域经济、城市与区域规划等方面的研究. E-mail: 402880740@qq.com

收稿日期: 2021-04-10

  修回日期: 2021-05-19

  网络出版日期: 2022-01-21

基金资助

陕西省可持续发展实验区建设相关技术集成研究项目(2018K01-117);陕西省科技厅攻关项目(2019K13-G18);西北大学科研启动基金项目(360051900075)

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Evolution of economic connection network structure in the Guanzhong Plain City Cluster and its impact on economic growth

  • Shanshan YE ,
  • Mingming CAO ,
  • Sheng HU
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  • 1. College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, Shaanxi, China
    2. Shaanxi Provincial Development and Reform Research Center, Xi’an 710016, Shaanxi, China

Received date: 2021-04-10

  Revised date: 2021-05-19

  Online published: 2022-01-21

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摘要

引用城市流强度修正传统引力模型构建经济联系矩阵,运用社会网络分析方法对2008—2018年关中平原城市群经济联系网络结构演变特征及对经济增长的影响进行分析。结果表明：（1） 城市群中心性水平较弱,经济网络处于极化发展期,区域发展不平衡问题突出。（2） 西安影响力不断增大,非核心城市影响力降低,在区域内形成“灯影效应”。（3） 凝集子群内部的集聚程度由松散向紧密发展,城市三级凝聚子群与城市所在省级行政区划分由不耦合演变为全部耦合。（4） 城市群平均核心度值水平较低且逐渐升高,核心区域由西安单核心演变为西安、咸阳双核心发展结构。（5） 城市的中心性、影响力及集聚性对城市经济增长的影响存在差异。

关键词： 经济联系; 网络结构; 经济增长; 社会网络分析; 关中平原城市群

本文引用格式

叶珊珊 , 曹明明 , 胡胜 . 关中平原城市群经济联系网络结构演变及对经济增长影响研究[J]. 干旱区地理, 2022 , 45(1) : 277 -286 . DOI: 10.12118/j.issn.1000–6060.2021.162

Abstract

The Guanzhong Plain City Cluster is located in northwest China, in the provinces of Shaanxi, Shanxi, and Gansu, a less developed region of China. The Guanzhong Plain City Cluster, the second-largest in inland China and one of the country’s eight most important city clusters serve as a vital gateway to western China. The development of the Guanzhong Plain City Cluster plays an important exemplary role and is strategically significant for regional harmonious development, new urbanization construction, and the Belt and Road Initiative. The research used UCINET and ArcGIS to analyze the evolution of 11 cities’ economic network structure in the Guanzhong Plain City Cluster from centrality, influences, “core-peripheral” structure, and cohesive subgroups by social network analysis using city economic data from 2008 to 2018. Then the regression model is constructed to analyze the influence of network structure properties on economic growth, and the suggestions to improve regional economic growth has been put forward from the perspective of economic network structure. The findings indicate that (1) the centrality of the city cluster’s network is insufficient with a decreasing trend, city centrality degree varies greatly, and the changes in centrality are different in different cities; regional sub-centers are severely underdeveloped, and the development of the economic network is dominated by polarization effect, indicating that regional development is unbalanced. (2) Xi’an has the greatest efficiency and lowest constraint, as well as the greatest influence with a growing trend in the city cluster, while the influence of non-core cities is relatively declining, which causes the “shadow effect” on surrounding cities. (3) The internal agglomeration of cohesive categories evolves from loose to close; in 2018, the cohesive subgroup presents a significant hierarchy, displaying a “pyramid” distribution; city subgroups and administrative division evolve from uncoupled to fully coupled, indicating that geographical proximity and administrative division are endogenous driving forces for the development of an economic network of the Guanzhong Plain City Cluster. (4) Based on the “core-peripheral” structure analysis, the city cluster has a low level of mean coreness with the growing trend which means that the degree of agglomeration in the economic network is gradually increasing; The economic network developed a core-peripheral structure, first with Xi’an as the core in 2008, and then with Xi’an and Xianyang as the core group between 2013 and 2018. (5) Regression analysis results show that the centrality, influence, and agglomeration of urban nodes have different effects on urban economic growth; more specifically, centrality and efficiency have a significant and positive correlation with economic growth, the constraint has a positive correlation with economic growth and coreness is non-significant.

Key words： economic connection; network structure; economic growth; social network analysis; the Guanzhong Plain City Cluster

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