地理科学 ›› 2015, Vol. 35 ›› Issue (2): 144-150.doi: 10.13249/j.cnki.sgs.2015.01.144

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金融空间联系及K-means聚类中心等级识别研究——以长三角为例

杨志民1,2, 化祥雨2(), 叶娅芬1,3, 邵元海1   

  1. 1. 浙江工业大学之江学院,浙江 杭州 310024
    2. 浙江工业大学经贸管理学院,浙江 杭州 310023
    3. 浙江大学经济学院,浙江 杭州 310023
  • 收稿日期:2014-01-12 修回日期:2014-05-06 出版日期:2015-02-15 发布日期:2015-02-15
  • 作者简介:

    作者简介:杨志民(1957-),男,河北邯郸人,教授,博士生导师,主要从事金融地理学、技术经济与管理、数据挖掘研究。E-mail:yzm9966@126.com

  • 基金资助:
    国家自然科学基金项目(10926198、11201426)、教育部人文社会科学研究青年基金项目(13YJC910011)、浙江省自然科学基金项目(LQ12A01020、LQ14G010004)、浙江省大学生科技创新活动计划(新苗人才计划)项目(2014R403063)资助

Spatial Combination of Finance and Center Level Identify Based on K-means Clustering: A Case Study of the Changjiang River Delta

Zhi-min YANG1,2, Xiang-yu HUA2(), Ya-fen YE1,3, Yuan-hai SHAO1   

  1. 1 .College of Zhijiang, Zhejiang University of Technology, Hangzhou,Zhejiang 310024,China
    2. College of Economics and Management, Zhejiang University of Technology, Hangzhou, Zhejiang 310023,China
    3. College of Economics, Zhejiang University, Hangzhou, Zhejiang 310023, China
  • Received:2014-01-12 Revised:2014-05-06 Online:2015-02-15 Published:2015-02-15

摘要:

以2001年、2006年、2011年长三角城市金融机构人民币存款、贷款额数为样本,构建金融空间联系模型,定量分析长三角城市金融空间联系分异特征。在此基础上构建K-means金融中心等级识别模型,识别长三角城市金融中心等级。研究表明:① 2001-2011年长三角城市金融“质量”空间趋势较为稳定,总体呈现东部高于西部,中部高于南、北部的倒U形分布。② 金融空间联系最大引力线联结格局较为稳定。③ 金融空间联系网络结构格局变化显著,主要从简单的“折线型”空间结构逐渐发展成简单的、复杂的“网络型”空间结构。④ 长三角金融城市中心等级空间分布格局稳定,以上海市金融中心最为突出。

关键词: 金融, 空间联系, 中心等级识别, 引力模型, K-means

Abstract:

The article constructs the financial spatial combination model and analyzes quantitatively the spatial differentiation characteristics of spatial combination by applying the number of financial institutions RMB deposit and loan in 2001, 2006 and 2011, taking cities in the Changjiang River Delta as examples. Based on the analysis, the financial center level identifying model with K-means is built to identify the financial center level of the cities in the Changjiang River Delta. The conclusions can be drawn as follows: 1) The spatial trend of the cities’ finance “quality” in the Changjiang River Delta is relatively stable, showing overall that the finance “quality” of the cities in the east is bigger than that of the cities in the west, and the finance “quality” of the cities in the center is bigger than those of the cities in the south and north, presenting the down “U” shaped distribution in the past ten years. 2) On the whole, the largest attracting linkages pattern of finance spatial combination is relatively stable. The largest attracting linkages pattern of finance spatial combination of Shanghai changes significantly, decreasing mainly the connection with the Zhejiang Province. The largest attracting linkages pattern of finance spatial combination of Jiangsu Province is relatively stable, meanwhile, that of Zhejiang Province has been strengthened. 3) The network structure of finance spatial combination has changed significantly. It was mainly a simple “polyline-based” spatial network structure with integrated financial cities among “Shanghai-Suzhou-Wuxi” in 2001. Then it was mainly developed into a simple “network-based” spatial network structure with networked finance cities, covering the partial cities around the core city Shanghai in 2006. In 2011, it has been developed into a complex “network-based” spatial network structure with regionalized financial cities, covering most of the cities in Changjiang River Delta. 4) The spatial distribution pattern of the financial center level is stable, Shanghai is the most prominent financial center, and Suzhou, Wuxi and Hangzhou were followed.

Key words: finance, spatial combination, center level identify, gravity model, K-means

中图分类号: 

  • F830