商圈划分中多元市场域的界定与实证

doi:10.3969/j.issn.1004-9479.2022.02.2020715

世界地理研究 ›› 2022, Vol. 31 ›› Issue (2): 338-349.DOI: 10.3969/j.issn.1004-9479.2022.02.2020715

商圈划分中多元市场域的界定与实证

岳丽莹¹(), 李山²^,³^,⁴(), 李开明⁵, 张颖⁶, 刘杰⁶

^1.华东师范大学，社会发展学院，上海 200241
^2.华东师范大学，地理信息科学教育部重点实验室，上海 200241
^3.华东师范大学，地理科学学院，上海 200241
^4.华东师范大学崇明生态研究院，上海 200062
^5.同济大学建筑与城市规划学院，上海 200092
^6.上海世脉信息科技有限公司，上海 200433

收稿日期:2020-08-19 修回日期:2020-10-16 出版日期:2022-03-15 发布日期:2022-03-22
通讯作者: 李山
作者简介:岳丽莹（1988-），女，博士研究生，主要研究方向为人文地理学，E-mail： 52183500010@stu.ecnu.edu.cn。
基金资助:
教育部人文社会科学研究规划基金项目(16YJA790021)

The definition and demonstration of multi-market areas in the trade area subdividing

Liying YUE¹(), Shan LI²^,³^,⁴(), Kaiming LI⁵, Ying ZHANG⁶, Jie LIU⁶

^1.a School of Social Development, 1b. Key Laboratory of Geographic Information Science, 1c. School of Geographic Sciences, East China Normal University, Shanghai 200241, China
^2.Institute of Eco-Chongming, East China Normal University, Shanghai 200062, China
^3.College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
^4.Shanghai Citybeats Information Technology Co. , Limited, Shanghai 200433, China

Received:2020-08-19 Revised:2020-10-16 Online:2022-03-15 Published:2022-03-22
Contact: Shan LI

摘要/Abstract

摘要：

对商业设施的商圈进行科学识别与划分是分析其商业前景、优化商业空间结构的基础。本研究首先提炼和界定了商圈划分的两种类型、四种市场域方法，分别是基于到访比例的邻近型与份额型市场域、基于出行概率的共享型和首位型市场域，通过比较其优劣发现这四种视角仅能反映商圈的某一特征，无法刻画出商圈空间分布全貌。据此，尝试提出了一种新的复合型市场域模型，并应用手机信令数据，以上海市商业中心为例，对其商圈划分进行了实证检验。研究发现：复合型市场域模型可以综合反映空间距离、客流规模和惠顾概率等要素对商圈的影响，可以弥补单一市场域视角下商圈划分方法的不足。与传统邻近型相比，基于复合市场域模型识别划分的商圈不仅重叠度低，而且其空间分布更加符合实际。

关键词: 零售业, 零售商圈, 商业中心, 店铺选址, 上海

Abstract:

The trade area hierarchical division has always been a hot issue for business practitioners and scholars. Under the background of urban commercial space expansion, traditional hierarchical division of trade areas from a single perspective can no longer meet commercial market segmentation needs. Trade areas can be affected by many factors, and the scientific identification and division of them need multi perspective cross analysis, which is the basis for analyzing commercial prospects and optimizing commercial space structures. This will provide scientific basis for the healthy development of commercial facilities and efficient utilization of urban commercial space, and help to solve the problems of overlapping and excessive competition in the rapid development of urban commerce. In terms of model definition, we refines and defines two types and four market area methods, which are distance proximity, quotient, ratio, primacy ratio, respectively. By comparing their advantages and disadvantages, it is found that these four perspectives can only reflect a certain feature of trade areas, but can not depict the overall spatial distribution of trade areas, so we systematically construct the interactive model of multi-market areas. In case study, we carry out empirical research by using mobile phone signaling data in Shanghai, taking Xujiahui commercial center, Lujiazui commercial center and East nanjing road commercial center as examples. The results show that: the composite market area model can comprehensively reflect the influence of spatial distance, passenger flow and patronage probability on trade areas, and can make up for the deficiency of the trade areas division method from the perspective of single market areas. Compared with the traditional adjacent trade area, the new model not only has low overlapping degree, but also its spatial distribution is more in line with the reality. In commercial practical application, business practitioners can flexibly combine different market areas according to market demand, which has certain universality.

Key words: retail industry, retail trade area, commercial center, store location selection, Shanghai

岳丽莹, 李山, 李开明, 张颖, 刘杰. 商圈划分中多元市场域的界定与实证[J]. 世界地理研究, 2022, 31(2): 338-349.

Liying YUE, Shan LI, Kaiming LI, Ying ZHANG, Jie LIU. The definition and demonstration of multi-market areas in the trade area subdividing[J]. World Regional Studies, 2022, 31(2): 338-349.

图/表 11

参考文献 37

1	王德,王灿,谢栋灿,等.基于手机信令数据的上海市不同等级商业中心商圈的比较——以南京东路、五角场、鞍山路为例.城市规划学刊,2015(3):50-60.
	WANG D, WANG C, XIE D, et al. Comparison of retail trade areas of retail centers with different hierarchical levels: A case study of east Nanjing road, Wujiaochang, Anshan road in Shanghai. Urban Planning Forum, 2015(3):50-60.
2	王芳,牛方曲,王志强.微观尺度下基于商圈的北京市商业空间结构优化.地理研究,2017,36(9):1697-1708.
	WANG F, NIU F, WANG Z. Commercial spatial structure optimization based on trade area analysis from a micro-scale perspective in Beijing. Geographical Research, 2017,36(9):1697-1708.
3	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 C, WANG H, LIU L. Retail district range compare model construction and Shanghai districts demonstration. Economic Geography, 2015,35(11):133-137.
4	张小英,巫细波.广州购物中心时空演变及对城市商业空间结构的影响研究.地理科学,2016,36(2):231-238.
	ZHANG X, WU X. Spatial-temporal evolution of malls in Guangzhou city and its impact on urban commercial spatial structure. Scientia Geographica Sinica, 2016,36(2):231-238.
5	陈玉慧,陈剑健.城市传统商业中心内部结构及形成机制研究——以厦门市中山商圈为例.世界地理研究,2008,17(04):104-114.
	CHEN Y, CHEN J. The study of the internal structure and the formation mechanism in the city-level commercial center--A case of Zhongshan district. World Regional Studies, 2008,17(04):104-114.
6	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 H. The theoretical model of commercial trade areas. Market and Demographic Analysis, 1999,5(3):23-25.
7	王铮,丁金宏.理论地理学概论.北京:科学出版社,2000.
	WANG Z, DING J. Theoretical Geography. Beijing: Beijing Science Press, 2000.
8	APPLEBAUM W. Methods for determining store trade areas, market penetration, and potential sales. Journal of Marketing Research, 1966,3(2):127-141.
9	PAULER G, MINAKSHI T, DINESH K G. Assessing store performance models. European Journal of Operational Research, 2009,197(1):349-359.
10	O'KELLY M E, MILLER H J. A synthesis of some market area delimitation models. Growth & Change, 2010,20(3):14-33.
11	吴小丁,王锐,王晓彦.零售业过度竞争的理论界定及判断标准.财贸经济,2007(8):99-103.
	WU X, WANG R, WANG X. The theoretical definition and judgment criteria of excessive competition in retail industry. Finance&Trade Economics, 2007(8):99-103.
12	杜漪,颜宏亮.我国城市商圈内的零售业态趋同现象研究.商业经济与管理,2006(3):11-15.
	DU Y, YAN H. The research on the phenomenon of retail business modes' convergence of city commercial circle in China. Business Economics and Administration, 2006(3):11-15.
13	王德,张晋庆.上海市消费者出行特征与商业空间结构分析.城市规划,2001,25(10):6-14.
	WANG D, ZHANG J. The analysis of consumer trip characteristics and spatial structure of commercial facilities in Shanghai. City Planning Review, 2001,25(10):6-14.
14	林瑶云.上海市购物中心的区位选择分析.上海:华东师范大学,2015.
	LIN Y. Location selection analysis of shopping mall in Shanghai. Shanghai: East China Normal University,2015.
15	周素红,郝新华,柳林.多中心化下的城市商业中心空间吸引衰减率验证——深圳市浮动车GPS时空数据挖掘.地理学报,2014,69(12):1810-1820.
	ZHOU S, HAO X, LIU L. Validation of spatial decay law caused by urban commercial center's mutual attraction in polycentric city: Spatio-temporal data mining of floating cars' GPS data in Shenzhen. Acta Geographica Sinica, 2014,69(12):1810-1820.
16	韩会然,焦华富,王荣荣,等.城市居民购物消费行为研究进展与展望.地理科学进展,2011,30(8):1006-1013.
	HAN H, JIAO H, WANG R, et al. Progress and prospects of the research on shopping behavior of urban residents. Progress In Geography, 2011,30(8):1006-1013.
17	傅辰昊,周素红,闫小培,等.广州市零售商业中心消费活动时变模式及其影响因素.地理科学, 2018,38(1): 20-30.
	FU C, ZHOU S, YAN X, et al. Temporal variation patterns and influencing factors of consuming activity in retailing centers: A case study of Guangzhou, China. Scientia Geographica Sinica, 2018,38(1):20-30.
18	BARAY J M, CLIQUET G. Delineating store trade areas through morphological analysis. European Journal of Operational Research, 2007,182(2):886-898.
19	JONES K, Location SIMMONS J., location, location : Analyzing the retail environment. Nelson Canada: International Thomson Publisher, 1993.
20	唐红涛.商圈时空动态性研究.吉首大学学报(社会科学版),2007(1):105-109.
	TANG H. Study on spatiotemporal dynamics of trade area. Journal of Jishou University, 2007(1):105-109.
21	丁鹏飞,王远飞.基于Relly法则与加权Voronoi图的连锁超市商圈分析.上海商学院学报,2005(4):18-22.
	DING P, WANG Y. A chain store trade area analysis based on Voronoi diagram and Relly law. Journal of Shanghai Business School, 2005(4):18-22.
22	王新生,余瑞林,姜友华.基于道路网络的商业网点市场域分析.地理研究,2008,27(1):85-92.
	WANG X, YU R, JIANG Y. Delimitating the store market field based on the metric of the city-block distance. Geographical Research, 2008,27(1):85-92.
23	蒋海兵,徐建刚,祁毅,等.基于时间可达性与伽萨法则的大卖场区位探讨——以上海市中心城区为例.地理研究,2010,29(6):1056-1068.
	JIANG H, XU J, QI Y, et al. The quantitative analysis of large scale supermarkets location based on time accessibility and Gasa rules. Geographical Research, 2010,29(6):1056-1068.
24	KIM P, KIM W, CHUNG W, et al. Using new Huff model for predicting potential retail market in South Korea. African Journal of Business Management, 2011,5(5):1543-1550.
25	YUE Y, WANG H, HU B, et al. Exploratory calibration of a spatial interaction model using taxi GPS trajectories. Computers, Environment and Urban Systems, 2012,36(2):140-153.
26	BEULE M D, POEL D V D, WEGHE N V D. An extended Huff-model for robustly benchmarking and predicting retail network performance. Applied Geography, 2014,46(1):80-89.
27	MURAD A K A. Creating a GIS application for retail centers in Jeddah city. International Journal of Applied Earth Observation and Geoinformation, 2003,4(4):329-338.
28	武占云,王远飞.购物中心商圈结构特征研究——以上海市购物中心为例.经济论坛,2010(2):30-35.
	WU Z, WANG Y. Study on the structural characteristics of shopping center trade area: Based on shopping centers in Shanghai. Economic Forum, 2010(2):30-35.
29	DREZNER T. Derived attractiveness of shopping malls. IMA Journal of Management Mathematics, 2006,17(4):349-358.
30	王铮,周嵬,李山,等.基于铁路廊道的中国国家级风景名胜区市场域分析.地理学报,2001(2):206-213.
	WANG Z, ZHOU W, LI S, et al. An analysis for market area of Chinese national park based on railway corridor. Acta Geographica Sinica, 2001(2):206-213.
31	YOUNG, W J. Delimiting shopping center trade areas with a Huff model. Annuls of the Association of American Geographers, 1972(1):132-136.
32	DOLEGA L, PAVLIS M, SINGLETON A. Estimating attractiveness, hierarchy and catchment area extents for a national set of retail center agglomerations. Journal of Retailing and Consumer Services, 2016(28):78-90.
33	丁亮,钮心毅,宋小冬.上海中心城区商业中心空间特征研究.城市规划学刊,2017(1):63-70.
	DING L, NIU X, SONG X. A study on spatial characteristics of commercial centers in the shanghai central city. Urban Planning Forum, 2017(1):63-70.
34	齐晓斋.城市商圈发展概论.上海:上海科学技术文献出版社,2007.
	QI X. An introduction to the development of urban trade area. Shanghai: Shanghai science and technology academic press, 2007.
35	王曙光.国外商业规划流程和内容概述.国际城市规划,2014,29(3):8-14.
	WANG S. An overview of the retail planning process and tasks in foreign countries. Urban Planning International, 2014,29(3):8-14.
36	岳丽莹.商圈分析的多元市场域模型.上海:华东师范大学,2016.
	YUE L. Multiple market area model of trading area analysis: A case study of Shanghai. Shanghai: East China Normal University, 2016.
37	裘炜毅,刘杰,张颖.手机大数据视角下的工业区职住平衡分析方法//中国城市规划学会,等. 2015中国城市规划年会论文集.北京:中国建筑工业出版社,2015. [
	QIU W, LIU J, ZHANG Y. Analysis of job balance in industrial area from the perspective of mobile phone data // Urban Planning Society of Chinaet al. The proceedings of 2015 China urban planning annual conference. Beijing: China Architecture & Building Press, 2015.]

属性	基于到访比例的市场域模型		基于出行概率的市场域模型
属性	邻近型市场域	份额型市场域	共享型市场域	首位型市场域
视角	供给主体	供给主体	需求主体	需求主体
划分标准	距离邻近	客流份额	惠顾概率	最大惠顾概率
主导因素	空间距离	需求规模	相互竞争关系	相互竞争关系
商圈层次	三层	三层	三层	一层
圈层结构	嵌套同心圆	变形	变形	变形

属性	基于到访比例的市场域模型		基于出行概率的市场域模型
属性	邻近型市场域	份额型市场域	共享型市场域	首位型市场域
视角	供给主体	供给主体	需求主体	需求主体
划分标准	距离邻近	客流份额	惠顾概率	最大惠顾概率
主导因素	空间距离	需求规模	相互竞争关系	相互竞争关系
商圈层次	三层	三层	三层	一层
圈层结构	嵌套同心圆	变形	变形	变形

类型	陆家嘴∩徐家汇		南京东路∩徐家汇		南京东路∩陆家嘴		徐家汇	陆家嘴	南京东路
类型	街道/个	占比/%	街道/个	占比/%	街道/个	占比/%	街道/个	街道/个	街道/个
邻近型市场域	39	59/58	51	76/64	64	81/97	67	66	79
复合型市场域	5	15/13	7	9/18	19	25/57	38	33	77

类型	陆家嘴∩徐家汇		南京东路∩徐家汇		南京东路∩陆家嘴		徐家汇	陆家嘴	南京东路
类型	街道/个	占比/%	街道/个	占比/%	街道/个	占比/%	街道/个	街道/个	街道/个
邻近型市场域	39	59/58	51	76/64	64	81/97	67	66	79
复合型市场域	5	15/13	7	9/18	19	25/57	38	33	77

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商圈划分中多元市场域的界定与实证

The definition and demonstration of multi-market areas in the trade area subdividing

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Metrics

商圈结构	邻近型市场域		份额型市场域		共享型市场域		首位型市场域		复合型市场域
商圈结构	客流/%	街镇/个	客流/%	街镇/个	客流/%	街镇/个	客流/%	街镇/个	客流/%	街镇/个
核心商圈	50	28	50	16	56	24	63	39	40	10
次级商圈(Ⅰ)	20	39	20	24	12	34	--	--	14	13
次级商圈(Ⅱ)	20	39	20	24	12	34	--	--	14	15
边缘商圈	20	47	20	58	22	103	--	--
总计	90	114	90	98	90	161	63	39	68	38