微观尺度下基于商圈的北京市商业空间结构优化

doi:10.11821/dlyj201709008

Abstract

Abstract:

Urban commercial districts are concentrated areas for shopping, leisure, business and other activities. For urban planners, the layout of commercial districts should not only be appropriately concentrated to realize economic benefit, but also properly dispersed to accommodate the distribution of the population. Taking Beijing as a case study, this paper conducted a small-scale research of trade areas by utilizing the open source big data, such as POI (Point of Information) and real estate information websites. We created a model of spatialization of the population on a residential block scale as well as a combined measure of Huff model and Voronoi diagram. These methods were used to systematically analyze the commercial spatial structure from the viewpoint of a small area in Beijing. We explored the layout and population of trade areas of five different functional types of commercial districts based on our previous related research, including dietary and cultural commercial districts, franchise-type commercial districts, shopping commercial districts, convenience commercial districts, and complex commercial districts. The results reveal that different kinds of trade areas have different spatial distribution features. Problems were also found: the areas of commercial trade areas at the urban fringes and the number of people they serve are too large; there are blind spots in the urban center; and there is incongruity between the commercial district type and population layout. Based on these findings, we propose several measures to optimize the commercial spatial structure: promoting the development of commerce in the outer space of the central city; making up for the layout shortage of commercial districts in the central city; defining the direction and development of the commercial districts based on the functional type; improving the urban commercial planning based on the functional and spatial structures.

Key words: trade area, commercial district, residential block, spatial structure optimization, Beijing

Fang WANG, Fangqu NIU, Zhiqiang WANG. Commercial spatial structure optimization based on trade area analysis from a micro-scale perspective in Beijing[J].GEOGRAPHICAL RESEARCH, 2017, 36(9): 1697-1708.

Figures/Tables 10

Fig. 1

Fig. 3

Tab.1

Fig. 2

Fig. 4

Tab.2

Tab.3

Tab.4

Tab.5

Tab.6

References 35

[1]	赵丹, 张京祥. 消费空间与城市发展的耦合互动关系研究: 以南京市德基广场为例. 国际城市规划, 2015, 30(3): 53-58.
	[Zhao Dan, Zhang Jingxiang.The overall logic of the coupling and interacting relationship between consumption space and city development: Taking Deji Plaza as an example. Urban Planning International, 2015, 30(3): 53-58.]
[2]	仵宗卿, 戴学珍. 北京市商业中心的空间结构研究. 城市规划, 2001, 25(10): 15-19. doi: 10.3321/j.issn:1002-1329.2001.10.003
	[Wu Zongqing, Dai Xuezhen.The study on the spatial structure of Beijing's commercial centers. City Planning Review, 2001, 25(10): 15-19.] doi: 10.3321/j.issn:1002-1329.2001.10.003
[3]	王芳, 高晓路. 北京市商业空间格局及其与人口耦合关系研究. 城市规划, 2015, 39(11): 23-29. doi: 10.11819/cpr20151105a
	[Wang Fang, Gao Xiaolu.Structure of commercial space and its coupling relationship with population distribution in Beijing. City Planning Review, 2015, 39(11): 23-29.] doi: 10.11819/cpr20151105a
[4]	张小虎, 张珣, 钟耳顺, 等. 基于建筑物空间特征的北京市城市空间结构及其机制分析. 地理研究, 2013, 32(11): 2055-2065. doi: 10.11821/dlyj201311008
	[Zhang Xiaohu, Zhang Xun, Zhong Ershun, et al.Study on the spatial structure and driving force of urban areas in Beijing based on building space structure, Geographical Research, 2013, 32(11): 2055-2065.] doi: 10.11821/dlyj201311008
[5]	Jackson P, Thrift N.Geographies of consumption. In: Miller D (ed.).Consumption:Critical Concepts in the Social Sciences.London:Routledge, 2001: 383-409.
[6]	黄晓冰, 陈忠暖. 基于信息熵的地铁站点商圈零售业种结构的研究: 以广州15个地铁站点商圈为例. 经济地理, 2014, 34(3): 38-44.
	[Huang Xiaobing, Chen Zhongnuan.The retail business structure of the metro site based on the information entropy: A case study of the 15 subwaysites in Guangzhou. Economic Geography, 2014, 34(3): 38-44.]
[7]	Burcu H, Cigdem V, Ozge Y.Do shopping centers abate the resilience of shopping streets? The co-existence of both shopping venues in Ankara, Turkey. Cities, 2014, 36(2): 145-157. doi: 10.1016/j.cities.2012.10.003
[8]	Wang F, Li Y, Gao X.A SP survey-based method for evaluating environmental performance of urban commercial districts: A case study in Beijing. Habitat International, 2016, 53(2): 284-291. doi: 10.1016/j.habitatint.2015.11.039
[9]	王芳, 高晓路, 许泽宁. 基于街区尺度的城市商业区识别与分类及其空间分布格局: 以北京为例. 地理研究, 2015, 34(6): 1125-1134.
	[Wang Fang, Gao Xiaolu, Xu Zening.Identification and classification of urban commercial districts at block scale. Geographical Research, 2015, 34(6): 1125-1134.]
[10]	王海忠. 商圈研究的理论模型. 市场与人口分析, 1999, 5(3): 23-25.
	[Wang Haizhong.The theoretical model of commercial trade areas. Market and Demographic Analysis, 1999, 5(3): 23-25.]
[11]	Huff D L.Parameter estimation in the Huff model. .
[12]	蒋海兵, 白光润. 商业微区位中的生态学视角. 商业时代, 2005, (35): 11-12. doi: 10.3969/j.issn.1002-5863.2005.35.006
	[Jiang Haibing, Bai Guangrun.The ecological perspective of commercial micro-location. Business Age, 2005, (35): 11-12.] doi: 10.3969/j.issn.1002-5863.2005.35.006
[13]	Matthias D B, Dirk V P, Nico V W.An extended Huff model for robustly benchmarking and predicting retail network performance. Applied Geography, 2014, 46(1): 80-89. doi: 10.1016/j.apgeog.2013.09.026
[14]	Christoph T, Jonathan E.Managing the attractiveness of evolved and created retail agglomerations formats. Marketing Intelligence & Planning, 2010, 28(1): 25-45. doi: 10.1108/02634501011014598
[15]	Eva M G, Margarita O G.A segmentation study of Mexican consumers based on shopping centre attractiveness. International Journal of Retail & Distribution Management, 2012, 40(10): 759-777. doi: 10.1108/09590551211263173
[16]	鲁成, 汪泓, 柳琳. 零售商圈辐射范围比较模型构建与上海商圈实证. 经济地理, 2015, 35(11): 133-137.
	[Lu Cheng, Wang Hong, Liu Lin.Retail district range compare model construction and Shanghai districts demonstration. Economic Geography, 2015, 35(11): 133-137.]
[17]	Wan N, Zou B, Sternberg T.A three-step floating catchment areamethod for analyzing spatial access to health services. International Journal of Geographical Information Science, 2012, 26(6): 1073-1089. doi: 10.1080/13658816.2011.624987
[18]	Bruno G, Improta G.Using gravity models for the evaluation of new university site locations: A case study. Journal of Computers and Operations Research, 2008, 35(22): 436-444. doi: 10.1016/j.cor.2006.03.008
[19]	Davis P.Spatial competition in retail markets: Movie theaters. The Rand Journal of Economics, 2006, 37(6): 964-982. doi: 10.1111/j.1756-2171.2006.tb00066.x
[20]	Birkin M, Clarke G, Clarke M.Refining and operationalizing entropy-maximizing models for business applications. Geographical Analysis, 2010, 42(2): 422-445. doi: 10.1111/j.1538-4632.2010.00801.x
[21]	Dolega L, Pavlis M, Singleton A.Estimating attractiveness, hierarchy and catchment area extents for a national set of retail centre agglomerations. Journal of Retailing & Consumer Services, 2016, 28(1): 78-90. doi: 10.1016/j.jretconser.2015.08.013
[23]	柳思维, 吴忠才. 引入基础设施和新增固定资产因素的城市商圈发展实证研究. 南京财经大学学报, 2009, (1): 22-26.
	[Liu Siwei, Wu Zhongcai.An empirical study on trade area of city by applying of the infrastructure and newly increased fixed assets. Journal of Nanjing University of Finance and Economics, 2009, (1): 22-26.]
[24]	李永浮, 潘浩之, 田莉, 等. 哈夫模型的修正及其在城市商业网点规划中应用: 以江苏省常州市为例. 干旱区地理, 2014, 37(4): 802-811.
	[Li Yongfu, Pan Haozhi, Tian Li, et al.Modification of Huff model and its application in urban commercial network planning: A case of Changzhou city, Jiangsu province. Arid land Geography, 2014, 37(4): 802-811.]
[25]	Long Y, Han H, Yu X.Discovering functional zones using bus smart card data and points of interest in Beijing. .
[26]	禹文豪, 艾廷华. 核密度估计法支持下的网络空间POI点可视化与分析. 测绘学报, 2015, 44(1): 82-90. doi: 10.11947/j.AGCS.2015.20130538
	[Yu Wenhao, Ai Tinghua.The visualization and analysis of POI features under network space supported by kernel density estimation. Acta Geodaetica et Cartographica Sinica, 2015, 44(1): 82-90.] doi: 10.11947/j.AGCS.2015.20130538
[27]	张子民, 周英, 李琦, 等. 城市局域动态人口估算方法与模拟应用. 地球信息科学学报, 2010, 12(4): 503-509.
	[Zhang Zimin, Zhou Ying, Li Qi, et al.An estimation method of dynamic population within an urban local area. Journal of Geo-information Science, 2010, 12(4): 503-509.]
[28]	Qi W, Liu S, Gao X, et al.Modeling the spatial distribution of urban population during the daytime and at night. Journal of Geographical Sciences, 2015, 25(6): 756-768. doi: 10.1007/s11442-015-1200-0
[29]	王法辉. 基于GIS的数量方法与应用.姜世国,滕骏华, 译. 北京:商务印书馆 , 2009.
	[Wang Fahui.Quantitative Methods and Applications Based on GIS. Translated by Jiang Shiguo, Teng Junhua. Beijing: The Commercial Press, 2009.]
[30]	Berry B J L, Parr J B, Epstein B J, et al. Market centers andretail location: Theory and applications. Englewood Cliffs, NJ: Prentice Hall, 1988.
[31]	吴忠才. 基于哈夫修正模型再修正的城市商圈区位模型. 吉首大学学报: 自然科学版, 2009, 30(2): 108-111. doi: 10.3969/j.issn.1007-2985.2009.02.030
	[Wu Zhongcai.Remodified model of location of urban trade areas based on Huff modified model. Journal of Jishou University: Natural Science Edition, 2009, 30(2): 108-111.] doi: 10.3969/j.issn.1007-2985.2009.02.030
[32]	朱求安, 张万昌, 赵登忠. 基于PRISM和泰森多边形的地形要素日降水量空间插值研究. 地理科学, 2005, 25(2): 233-238.
	[Zhu Qiuan, Zhang Wanchang, Zhao Dengzhong.Topography-based spatial daily precipitation by means of PRISM and Thiessen polygon analysis. Scientia Geographica Sinica, 2005, 25(2): 233-238.]
[33]	Guruprasad K R, Ghose D.Heterogeneous locational optimisation using a generalised Voronoi partition. International Journal of Control, 2013, 86(6): 977-993. doi: 10.1080/00207179.2013.768775
[34]	Zhao J, Sun Q.Model and Simulation of Data Aggregation Based on Voronoi Diagram in Hierarchical Sensor Network. New York: Springer, 2012. doi: 10.1007/978-1-4614-5803-6_11
[35]	罗彦, 周春山. 城市商业空间结构问题与优化探讨. 商业经济与管理, 2005, (1): 22-26. doi: 10.3969/j.issn.1000-2154.2005.01.005
	[Luo Yan, Zhou Chunshan.The problem and method on optimization of urban commercial spatial. Business Economics and Administration, 2005,(1): 22-26.] doi: 10.3969/j.issn.1000-2154.2005.01.005

	功能特征	主要商业网点	空间分布特征	数量(人)	平均面积(km²)	典型商业区
饮食文化型商业区	以饮食服务为主	各类餐饮店	一级和二级饮食文化商业区多分布在三环和四环附近,三级商业区的分布则相对分散	240	0.015	如魏公村附近
专营型商业区	以某一类专营服务为主	家电电子商场、家居建材市场等	主要集中在三、四环附近以及五环外	264	0.068	如四惠建材城附近
购物中心型商业区	以高档、综合性购物为主	大型商场、购物中心、商业街等	该类一级和二级商业区主要集中二、三环附近;二三级在五环外也有分布	350	0.121	如王府井、西单
便利型商业区	以基本生活服务为主	超市、便利店、餐饮店等	空间分布较为分散,无明显集聚区	120	0.011	如看丹路附近
综合型商业区	职能最为综合,提供多种商业服务	各类专业店、综合市场、餐饮店、超市等	主要布局在城市居住区附近和人流相对集中的区域	89	0.051	如回龙观批发市场附近

空间范围	商业区数量(个)	平均服务面积(km²)	平均服务人口(人)
二环内	30	2.03	42221
二环到三环	72	1.47	34202
三环到四环	64	2.71	43364
四环到五环	47	11.56	78936
五环外	27	72.72	182707

空间范围	商业区数量(个)	平均服务面积(km²)	平均服务人口(人)
二环内	20	2.78	54474
二环到三环	30	2.72	71396
三环到四环	71	3.88	79685
四环到五环	79	5.71	59193
五环外	64	41.72	70487

空间范围	商业区数量(个)	平均服务面积(km²)	平均服务人口(人)
二环内	48	1.69	52539
二环到三环	68	1.82	47557
三环到四环	81	6.61	50950
四环到五环	71	4.74	37652
五环外	82	28.01	73922

空间范围	商业区数量(个)	平均服务面积(km²)	平均服务人口(人)
二环内	5	7.13	157222
二环到三环	14	9.28	211669
三环到四环	18	6.20	113274
四环到五环	48	11.08	78812
五环外	35	56.20	154606

Commercial spatial structure optimization based on trade area analysis from a micro-scale perspective in Beijing

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 35

Related Articles 15

Metrics

Comments

Recommended 10

空间范围	商业区数量(个)	平均服务面积(km²)	平均服务人口(人)
二环内	14	4.14	97260
二环到三环	22	5.6	113150
三环到四环	22	8.1	126393
四环到五环	17	52.05	214694
五环外	14	111.28	311640

[1]	Jiao HUANG, Bingying MA, Shuangcheng LI. Agricultural multifunctionality and land use management in metropolitan areas: A framework and a case study [J]. GEOGRAPHICAL RESEARCH, 2019, 38(7): 1791-1806.
[2]	Xiaofeng TANG. Traditional urban space governance in Beijing: Heritage and challenge [J]. GEOGRAPHICAL RESEARCH, 2019, 38(6): 1290-1298.
[3]	Sha ZHU, Shan JIANG, Li TAO. Side-bet theory: How do B&B owners make commitment to tourism development in outer suburbs of Beijing ? [J]. GEOGRAPHICAL RESEARCH, 2019, 38(5): 1208-1221.
[4]	Jintao LI, Yuanyuan YANG, Ning JIANG. Mode of rural revitalization and its approaches in Beijing-Tianjin-Hebei metropolitan area: A case study of Jinghai District in Tianjin [J]. GEOGRAPHICAL RESEARCH, 2019, 38(3): 496-508.
[5]	Yuanyuan YANG, Yuzhu ZANG, Jintao LI. Rural revitalization mode in Beijing-Tianjin-Hebei from the perspective of urban-rural transformation functional zoning [J]. GEOGRAPHICAL RESEARCH, 2019, 38(3): 684-698.
[6]	Fang FANG, Renwei HE, Lina LI. Research of the regional mode of rural revitalization in Beijing-Tianjin-Hebei Region: Based on the spatial effect between rural off-farm employment and farmers' income growth [J]. GEOGRAPHICAL RESEARCH, 2019, 38(3): 699-712.
[7]	Jing WANG, Benteng LIU, Yurui LI. Spatial-temporal characteristics and influencing factors of population distribution and floating changes in Beijing-Tianjin-Hebei region [J]. GEOGRAPHICAL RESEARCH, 2018, 37(9): 1802-1817.
[8]	Xiaoquan LIU, Tieshan SUN, Guoping LI. Spatial restructuring of manufacturing industries in Beijing [J]. GEOGRAPHICAL RESEARCH, 2018, 37(8): 1575-1586.
[9]	Meifeng ZHAO, Shenghe LIU, Wei QI. Spatial identification and scale effects of floating population agglomerations at the community scale: A case study of Beijing [J]. GEOGRAPHICAL RESEARCH, 2018, 37(6): 1208-1222.
[10]	Xin CHEN, Jian PENG, Yanxu LIU, Yunqian CHEN, Tianyi LI. Measuring spatial expansion and correlations of cities in Beijing-Tianjin-Hebei Urban Agglomeration using DMSP/OLS nighttime light data [J]. GEOGRAPHICAL RESEARCH, 2018, 37(5): 898-909.
[11]	Xinyue GAO, Junhu DAI, Mingqing ZHANG. Responses of variations of plant ornamental period to climate change in the west suburbs of Beijing from 1965-2014 [J]. GEOGRAPHICAL RESEARCH, 2018, 37(12): 2420-2432.
[12]	Jiaming LI, Wei SUN, Wenzhong ZHANG. Comparative study on micro-scale location choice of typical industries: The case study of management service and automobile manufacturing in Beijing [J]. GEOGRAPHICAL RESEARCH, 2018, 37(12): 2541-2553.
[13]	Siyao GAO, Yang CHENG. Willingness to relocation of the older people within Beijing [J]. GEOGRAPHICAL RESEARCH, 2018, 37(1): 119-132.
[14]	Jintao LI, Yansui LIU, Yuanyuan YANG, Jilai LIU. Spatial-temporal characteristics and driving factors of urban construction land in Beijing-Tianjin-Hebei region during 1985-2015 [J]. GEOGRAPHICAL RESEARCH, 2018, 37(1): 37-52.
[15]	Yongqiang LV, Xinqi ZHENG, Lin ZHOU. Relationships between street centrality and spatial distribution of functional urban land use: A case study of Beijing central city [J]. GEOGRAPHICAL RESEARCH, 2017, 36(7): 1353-1363.