地球信息科学学报

地球信息科学学报 ›› 2013, Vol. 15 ›› Issue (5): 712-718.doi: 10.3724/SP.J.1047.2013.00712

• 地理空间分析综合应用 • 上一篇    下一篇

国有商业银行与股份制商业银行的空间布局特征分析——以南京市江南8区为例

苏曦1,2, 陈江龙1   

  1. 1. 中国科学院南京地理与湖泊研究所, 南京 210008;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2013-01-14 修回日期:2013-04-01 出版日期:2013-09-29 发布日期:2013-09-29
  • 通讯作者: 陈江龙(1974-),男,福建厦门人,副研究员,主要从事土地利用和区域发展研究。E-mail:JLchen@niglas.ac.cn E-mail:JLchen@niglas.ac.cn
  • 作者简介:苏曦(1989-),女,江苏泰州人,硕士生,主要从事土地利用和区域发展研究。E-mail:suxisunny@163.com
  • 基金资助:

    中国科学院知识创新工程重要方向项目(KZCX2-YW-339);国家自然科学基金项目(70873120、70503026、41130750)。

Characteristics of Spatial Distribution of State Owned Commercial Bank and Joint-stock Commercial Bank Outlets: A Case Study in Nanjing

SU Xi1,2, CHEN Jianglong1   

  1. 1. Nanjing Institute of Geography and Limnology, CAS, Nanjing 210008, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2013-01-14 Revised:2013-04-01 Online:2013-09-29 Published:2013-09-29

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摘要：

以南京市江南8区380家国有商业银行网点,211家股份制商业银行网点为研究样本数据,综合运用缓冲区分析、Ripley's K函数和空间热点探测方法,分析了国有商业银行和股份制商业银行网点的空间布局特征。结果表明:两类商业银行均呈现出一定的中心集聚态势,但“向心”程度、集聚的广度与强度存在差异。缓冲区分析表明,股份制商业银行由市中心向外呈现明显递减的特点,但国有商业银行在前3个缓冲圈层内分布比较均匀;Ripley's K函数方法表明,两类商业银行均呈现先增后减的倒“U”型空间集聚特征,但股份制商业银行集聚范围小于国有商业银行;空间热点探测方法表明,两类商业银行热点区域集聚强度相异,国有商业银行低于股份制商业银行。分析空间热点重叠部位,将国有商业银行与股份制商业银行空间布局导向分为商业中心导向、高新技术-商业中心导向和人力资本-政府机构-商业中心导向。

关键词: 缓冲区分析, 南京市, 商业银行网点空间布局, 空间热点探测, Ripley's K函数

Abstract:

We selected 380 state owned commercial bank outlets and 211 nation-wide joint-stock commercial bank outlets in eight districts (located in south of the Yangtze River) of Nanjing as the study samples. Using buffer analysis and Ripley's K (d) function and spatial hot spot detection method, we analyzed the distribution characteristics of these outlets. Firstly, we studied the density characteristics of these outlets in different buffer zones by the spatial analysis module of ArcGIS 9.3. Secondly, Ripley's K (d) function is applied to measure whether the commercial bank outlets are clustered distribution and their cluster range. Thirdly, we used hot spot detection method to detect the commercial bank outlets clustered hot spots in the eight districts. The results showed that, generally speaking, both of the commercial banks tend to cluster in the center of Nanjing, while the tendency towards the CBD differs. Joint-stock commercial bank outlets show a decreasing tendency from inside to outside, which accord to the circle structure with Xinjiekou as the center with 2 km, 4 km, 6km and 8 km as the radius buffer zones, while state owned commercial bank outlets show a homogeneous distribution in the first three buffer zones. Outlets of both the banks show the way of increasing first and then decreasing as an inverted "U" -shaped structure, but the spatial scale differs, i.e., state owned commercial bank outlets concentrated in a larger scale compared to joint-stock commercial bank outlets. Joint-stock commercial bank outlets show a "small area, large cluster" mode in Nanjing, while state owned commercial bank outlets present a "large area, low cluster" mode. By analyzing the overlaying zones of the hot spots, the location choosing of outlets of the two commercial banks can be divided into 3 types: business center oriented, labor-governmental agency-business center oriented and high-tech-business center oriented.

Key words: Ripley's K function, spatial distribution of commercial bank outlets, spatial hot spot detection, Nanjing City, buffer analysis