广州市银行业的空间布局特征与模式

doi:10.13249/j.cnki.sgs.2016.05.012

摘要/Abstract

摘要：

以广州都市区2013年全部类别银行的1 637个银行网点为基本数据,利用平均最邻近距离、核密度函数、缓冲区分析、空间模式提炼等方法探索广州市银行业的空间布局特征及其类别差异,总结其空间分异模式。结果表明：① 广州市银行业空间不均衡性布局显著,并呈现中心集聚特征;② 不同类型银行的分布特征差异显著。国有商业银行的服务便利性和数量等级高,网点密度大,构成了广州市银行业的主体;③ 广州市银行业布局总体呈现由中心向外围逐渐递减的“圈层+扇形”空间模式。其中,核心商圈是银行业高度集聚区,中心城区密度递减最为显著,近郊区密度最低;④ 不同类型银行的空间密度模式差异显著。国有商业银行、全国性股份制银行和城市商业银行分别呈现由中心到外围非均匀递减的倒“S”型、“L”型和“阶梯型”曲线模式。外资港资银行呈现为核心商圈集聚模式。农村商业银行为均质的“一”字型直线模式。

关键词: 金融地理学, 银行业, 银行网点, 核密度函数, 广州

Abstract:

In this article, based on the average nearest neighbor method, kernel density function, buffer analysis and spatial pattern extraction method, we explore the characteristics of spatial layout and class differences of the banking industry in Guangzhou City and summarize its spatial differentiation model. All of the data are from 1 637 banking outlets distributed in Guangzhou metropolitan areas. The results are shown as follows: 1) The spatial layout of Guangzhou banking shows a significant imbalance and center cluster characteristic. 2) Significant difference is found in distribution characteristics of different types of banks. State-owned commercial bank constitutes the main body of the banking sector in Guangzhou for its convenient service, enormous quantity, high dot density and high grade. 3) The quantity of bank outlets has diminished gradually from the city center to the periphery and shows a ‘circle layer + fan shaped’ space model: the core commercial circle is banking highly concentrated area, the city center is the most significant regional banking density decrease area and the least number of bank is located in the suburb. 4) Different types of banks have different spatial density model. The spatial density of state-owned commercial banks, national joint-stock banks and city commercial banks present non-uniform decline from center to the periphery, and respectively show inverted ‘S’ type, ‘L’ type and ‘ladder’ type curve model. Foreign funded banks and Hong Kong funded banks present a core business agglomeration mode, while the rural commercial bank presents a homogeneous linear model.

Key words: Financial Geography, banking industry, bank outlets, kernel density function, Guangzhou City

中图分类号:

K902

王洋, 杨忍, 李强, 席文凯. 广州市银行业的空间布局特征与模式[J]. 地理科学, 2016, 36(5): 742-750.

Yang Wang, Ren Yang, Qiang Li, Wenkai Xi. The Spatial Layout Features and Patterns of Banking Industry in Guangzhou City, China[J]. SCIENTIA GEOGRAPHICA SINICA, 2016, 36(5): 742-750.

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参考文献 34

[35]	广州市城市规划勘测设计研究院. 广州市城市总体规划(2011-2020年)[J/OL]. .
	[Guangzhou Urban Planning Survey and Design Institute. Guangzhou City Master Plan (2011-2020). ]
[36]	Clark P J, Evans F C Distance to nearest neighbor as a measure of spatial relationships in populations[J]. Ecology,1954,35: 445-453.
[37]	田光进, 沙默泉. 基于点状数据与 GIS 的广州大都市区产业空间格局[J]. 地理科学进展, 2010, 29(4): 387-395.
	[Tian Guangjing, Sha Moquan.The spatial pattern of Guangzhou metropolitan area industry based on point data and GIS. Progress in Geography, 2010, 29(4): 387-395.]
[38]	Chu Honejay, Liau Churnjung, Lin Chaohung et al. Integration of fuzzy cluster analysis and kernel density estimation for tracking typhoon trajectories in the Taiwan region[J]. Expert Systems with Applications, 2012, 39(10): 9451-9457.
[39]	王洋,方创琳,盛长元. 扬州市住宅价格的空间分异与模式演变[J]. 地理学报, 2013, 68(8):1082-1096.
	[Wang Yang, Fang Chuanglin, Sheng Changyuan.Spatial differentiation and model evolution of housing prices in Yangzhou. Acta Geographic Sinica, 2013, 68(8): 1082-1096.]
[1]	Martin R.Money and the space economy[M]. London: John Wiley & Sons, 1999.
[2]	Porteous D J.The geography of finance: Spatial dimensions of intermediary behaviour[M]. Aldershot: Avebury, 1995.
[3]	Clark G L.London in the European financial services industry: locational advantage and product complementarities[J]. Journal of Economic Geography, 2002, 2(4): 433-453.
[4]	Polèse M. Culture, Language,the Location of High-Order Service Functions: The Case of Montreal and Toronto[J]. Economic Geography, 2004, 80(4): 329-350.
[5]	彭宝玉, 李小建. 1990 年代中期以来中国银行业空间系统变化研究[J]. 经济地理, 2009, 29(5): 765-770.
	[Peng Baoyu, Li Xiaojian.Changes of Chinese banking spatial system since the middle 1990s. Economic Geography, 2009, 29(5): 765-770.]
[6]	Shyu J, Chiang T.Measuring the true managerial efficiency of banking outlets in Taiwan: A three-stage DEA analysis[J]. Expert Systems with Applications, 2012, 39(13): 11494-11502.
[7]	Marshall J N.Financial institutions in disadvantaged areas: a comparative analysis of policies encouraging financial inclusion in Britain and the United States[J]. Environment and Planning A, 2004, 36(2): 241-262.
[8]	Clark G L.Money flows like mercury: the geography of global finance[J]. Geografiska Annaler: Series B, Human Geography, 2005, 87(2): 99-112.
[9]	Bassens D, Derudder B, Witlox F.Searching for the Mecca of finance: Islamic financial services and the world city network[J]. Area, 2010, 42(1): 35-46.
[10]	Clark G L, Wójcik D.Path dependence and financial markets: the economic geography of the German model, 1997-2003[J]. Environment and Planning A, 2005, 37(10): 1769.
[11]	Dixon A D.Function before form: macro-institutional comparison and the geography of finance[J]. Journal of Economic Geography, 2012, 12(3): 579-600.
[12]	Cheng S, Stough R R.Location decisions of Japanese new manufacturing plants in China: a discrete-choice analysis[J]. The Annals of Regional Science, 2006, 40(2): 369-387.
[13]	Liang H Y, Ching Y P, Chan K C.Enhancing bank performance through branches or representative offices? Evidence from European banks[J]. International Business Review, 2013, 22(3): 495-508.
[14]	Cairncross F.The death of distance: How the communications revolution is changing our lives[M]. Boston: Harvard Business Press, 2001.
[15]	Alamá L, Tortosa-Ausina E.Bank branch geographic location patterns in Spain: some implications for financial exclusion[J]. Growth and Change, 2012, 43(3): 505-543.
[16]	Yeung G.Hybrid property, path dependence, market segmentation and financial exclusion: the case of the banking industry in China[J]. Transactions of the Institute of British Geographers, 2009, 34(2): 177-194.
[17]	Joassart-Marcelli P, Stephens P.Immigrant banking and financial exclusion in Greater Boston[J]. Journal of Economic Geography, 2010, 10(6): 883-912.
[18]	Wójcik D.The East Asian banking sector—overweight?[J]. Environment and Planning A, 2000, 32(1): 4-8.
[19]	李小建. 金融地理学理论视角及中国金融地理研究[J]. 经济地理, 2006, 26(5): 721-725.
	[Li Xiaojian.A theoretical review of financial geography and study of financial geography in China. Economic Geography, 2006, 26(5): 721-727.]
[20]	Morrison P S, O’Brien R. Bank branch closures in New Zealand: the application of a spatial interaction model[J]. Applied Geography, 2001, 21(4): 301-330.
[21]	林彰平, 闫小培. 转型期广州市金融服务业的空间格局变动[J]. 地理学报, 2006, 61(8): 818-828.
	[Lin Zhangping, Yan Xiaopei.Analysis on the change of the spatial pattern of financial service industry in Guangzhou during the transition period. Acta Geographica Sinica, 2006, 61(8): 818-828.]
[22]	林彰平, 闫小培, 方远平. 东莞市金融服务业分散化空间格局——企业金融服务消费行为视角[J]. 地理研究, 2007, 26(1): 168-178.
	[Lin Zhangping, Yan Xiaopei, Fang Yuanping.The decentralized spatial pattern of the financial service industry in Dongguan: a perspective of consumer behavior of enterprises' financial services. Geographical Research, 2007, 26(1): 168-178.]
[23]	杨香花. GIS 辅助下的金融网点选址研究——以广州市农业银行网点布局调整为例 [D]. 长春: 东北师范大学, 2003.
	[Yang Xianghua.Studies for location selection for financial facility based on GIS: A case of branch planning and adjustment of Agricultural Bank of China in Guangzhou. Changchun: Northeast Normal University, 2003.]
[24]	柳宗伟, 毛蕴诗. 基于GIS 与神经网络的商业银行网点选址方法研究[J]. 商业经济与管理, 2004, (9): 55-59.
	[Liu Zongwei, Mao Yunshi.A research on location selected of banking on the basis of GIS and neural networks. Journal of Business Economics, 2004, (9): 55-59.]
[25]	顾萌. 基于城市密度分析下的金融网点布局研究[D].长春: 东北师范大学, 2009.
	[Gu Meng.Research on the arrangement of facilities based on city density: the arrangement of Agricultural Bank of China in Changchun’s example. Changchun: Northeast Normal University, 2009.]
[26]	林善浪, 王健. 上海市金融服务业区位选择研究[J].上海金融, 2010, (2): 19-22.
	[Lin Shanlang, Wang Jian.Shanghai financial services location selection research. Shanghai Finance, 2010, (2): 19-22.]
[27]	黄飞. 人口学视角下的北京市银行网点选址, 布局分析[D].北京: 首都经济贸易大学, 2011.
	[Huang Fei.Beijing bank branch location, arrangement analysis from Demographic perspective. Beijing: Capital University of Economics and Business, 2011.]
[28]	徐峰. 银行网点选址因素的实证研究[D]. 杭州: 浙江工业大学, 2009.
	[Xu Feng.Study on effect factors of bank branch location. Hangzhou: Zhejiang University of Technology, 2009.]
[29]	徐艳会, 元媛, 路紫. 中国大都市内部银行网点空间布局形态分析[J]. 沈阳师范大学学报: 自然科学版, 2009, 27(1): 119-123.
	[Xu Yanhui, Yuan Yuan, Lu Zi.Analysis of bank sites spatial arrangement patterns in China' s Metropolis. Journal of Shenyang Normal University: Nat Sci Ed, 2009, 27(1): 119-123.]
[30]	李峰, 薛耀文. 基于复杂网络的银行网点布局研究[J]. 复杂系统与复杂性科学, 2011, 8(2): 64-70.
	[LI Feng, Xue Yaowen.Study of bank nodes allocation based on complex network. Complex Systems and Complexity Science, 2011, 8(2): 64-70.]
[31]	刘伟伟. 北京市银行业空间布局研究[D]. 北京: 首都师范大学, 2011.
	[Liu Weiwei.Beijing banking spatial arrangement. Beijing: Capital Normal University, 2011.]
[32]	李翠敏. 城市银行网点的空间分析——以上海市中心城区为例[D].上海: 上海师范大学, 2005.
	[Li Cuimin.Spatial analysis of urban bank branches in Shanghai center city. Shanghai: Shanghai Normal University, 2005.]
[33]	郭小萍. 商业银行网点空间布局影响因素研究[D]. 合肥: 安徽大学, 2010.
	[Guo Xiaoping.Study on effect factors of Commercial Bank branch location. Hefei: Anhui University, 2010.]
[34]	广州年鉴编委会.广州年鉴2013[M].广州: 广州年鉴编委会, 2013.
	[Guangzhou Yearbook Editorial Board. Guangzhou Yearbook. Guangzhou: Guangzhou Yearbook Editorial Board, 2013.]

数量等级	网点个数	银行名称
1	>200	中国工商银行、广州农村商业银行
2	100~200	中国农业银行、中国建设银行、中国银行、中国邮政储蓄银行
3	50~100	广州银行、交通银行
4	10~50	广发银行、招商银行、平安银行、中国民生银行、上海浦东发展银行、中信银行、兴业银行、中国光大银行、华夏银行
5	<10	恒生银行、汇丰银行、东亚银行、花旗银行、星展银行、渣打银行、永亨银行、东莞银行、湛江市商业银行、渤海银行、大新银行、南洋银行、法兴银行、广东华兴银行、九江银行、南昌银行、长沙银行

银行名称	网点数/个	中心城区网点数/个	近郊区网点数/个	中心城区网点比重/%	平均邻近距离/m	比率R	p值	分布特征	500 m网点覆盖率/%	1000 m网点覆盖率/%
中国工商银行	291	232	59	79.73	688.47	0.6980	0.0000	强烈集聚	16.07	34.43
中国农业银行	192	146	46	76.04	912.95	0.7519	0.0000	强烈集聚	12.02	30.21
中国建设银行	191	156	35	81.68	820.65	0.6741	0.0000	强烈集聚	11.65	25.37
中国银行	172	137	35	79.65	885.99	0.6906	0.0000	强烈集聚	10.71	25.18
交通银行	65	55	10	84.62	1174.73	0.5629	0.0000	强烈集聚	4.78	13.87
中国邮政储蓄银行	124	91	33	73.39	1154.48	0.7641	0.0000	强烈集聚	9.14	26.99
广州银行	74	64	10	86.49	1276.07	0.6524	0.0000	强烈集聚	5.57	14.96
广州农村商业银行	270	94	176	34.81	965.22	0.9427	0.0714	一般集聚	19.44	55.32