Location Orientation of E-shops in China's Major Cities Based on Neighborhood Facilities: Case Studies of Shanghai, Shenzhen, Tianjin and Beijing

Expand
  • 1. School of Tourism, Faculty of Resources and Environment Science, Hebei Normal University, Shijiazhuang 050016, China;
    2. School of Geography, Planning and Environmental Management, University of Queensland, Queensland 4072, Australia

Received date: 2010-07-17

  Revised date: 2010-12-24

  Online published: 2011-06-20

Supported by

National Natural Science Foundation of China, No.40971073

Abstract

This paper employs two basic approaches: fuzzy location-orientation method based on neighborhood facilities and fuzzy multiple attribute decision making (MADM) method. The study focuses on spatial agglomeration analysis of e-shops which have tangible stores at Taobao website. The Taobao e-shops located in Beijing, Shanghai, Shenzhen and Tianjin have six categories of goods: digital products, household collections, clothing, skin care, stationery and sports. These e-shops can be divided into four location types: complete, overlapping, transitional and partial. Based on these four types, this paper reveals the biased characteristics of location-orientation of various e-shops and the changes of location orientation influence factors in information era, and further explores the optimal location choices of digital product e-shops which have obvious location distribution. The research findings are as follows. (1) Different goods categories have significant differences on e-services network location choice (ESNLC), and decentralization and agglomeration coexist. Agglomeration only happens at precious commodities such as digital categories and it still relies on traditional neighborhood facilities. By contrast, the majority of ordinary commodity e-shops barely have overlapping location layout, and have already shown a new location-oriented regular pattern, which no longer follows the traditional location theory. (2) The e-services network location choices under different commercial models differ from each other. The influences on ESNLC of c2c e-commerce model tend to be more different from the traditional location choice, which indicates that c2c e-commerce is the foundation of changes of location-orientation influence factors of e-shops. In addition to the old transmission network, sources of supply, market concentration factors, skilled labor factors and trust factors would become the mainstream. (3) Triangular fuzzy numbers can be used to calculate the optimal location of precious goods e-shops, such as digital product category, which have aggregated neighborhood facilities and obvious location orientation. The optimal location is selected from the overlap location to complete location. The larger the number of neighborhood facilities is, the stronger the location-orientation is. (4) In the electronic age, the traditional location theory will be extended or improved to be fully interpreting the location phenomenon of electronic service network.

Cite this article

LU Zi, LI Xiaonan, YANG Lihua, YANG Dong, DENG Lili . Location Orientation of E-shops in China's Major Cities Based on Neighborhood Facilities: Case Studies of Shanghai, Shenzhen, Tianjin and Beijing[J]. Acta Geographica Sinica, 2011 , 66(6) : 813 -820 . DOI: 10.11821/xb201106010

References

[1] Henry Bakis, Lu Zi. The change from the geographical space to geocyberspace: Review on the western scholars on regionaleffects by telecommunication. Acta Geographica Sinica, 2000, 55(1): 104-111. [H·巴凯斯, 路紫. 从地理空间到地理网络空间的变化趋势: 兼论西方学者关于电信对地区影响的研究. 地理学报, 2000, 55(1): 104-111.]



[2] Burt S, Sparks L. E-commerce and the retail process: A review. Journal of Retailing and Consumer Services, 2002, 10(5):275-286.



[3] Wrigley N, Lowe M, Currah A. Retailing and e-tailing. Urban Geography, 2002, 23(2): 180-197.



[4] Hashimoto K. Information network and the distribution space in Japan: A case study of consumer goods manufacturers inJapan. NETCOM, 2002, 16(1/2): 17-28.



[5] Mark IW. Real places and virtual spaces. NETCOM, 2003, 17(3/4): 139-148.



[6] Lu J, Lu Z. Development, distribution and evaluation of online tourism services in China. Electronic Commerce Research,2004, 3: 221-239.



[7] Lorentzon Sten. The creation of Gothia Science Park: an example of the application of the triple helix model in a Swedishcontex. NETCOM, 2006, 20: 163-179.



[8] Wang Donggen, Li Jiukun. A model of household time allocation taking into consideration of hiring domestic helpers.Transportation Research Part B: Methodological, 2009, 43(2): 204-216.



[9] Yoshio A. Geolocation technologies and local information in mobile telephony. NWTCOM, 2006, 20: 139-148.



[10] Lu Zi, Fan Lili. An evaluation in service functions and development strategy for small-medium size tourism website: Thecase of Leyou Outdoors Club. Human Geography, 2005, 20(1): 103-106. [路紫, 樊莉莉. 中小型旅游网站服务功能与商业模式的区位问题: 以乐游户外运动俱乐部旅游网站为例. 人文地理, 2005, 20(1): 103-106.]



[11] Han Bing, Lu Zi. The forum function evaluation and the guide of interaction function of outdoor sports website forum topersonal journey. Human Geography, 2007, 22(1): 58-62. [韩冰, 路紫. 户外运动网站论坛功能评估及其互动作用对个人出行行为的导引. 人文地理, 2007, 22(1): 58-62.]



[12] Jiven J, Larkham P J. Sense of place, authenticity and character, a commentary. Journal of Urban Design, 2003, 8: 67-81.



[13] Miriam Billig. Sense of place in the neighborhood, in locations of urban revitalization. GeoJournal, 2005, 64: 117-130.



[14] Yoshio Arai, Kazuhiro Sugizaki. Concentrations of call center in peripheral areas: Cases in Japan. NETCOM, 2003, 17:187-202.



[15] Sener B, Suzen L, Doyuran V. Landfill site selection by using geographic information systems. Environmental Geology,2006, 49: 376-388.



[16] He Dehua, Lu Yaobin, Zhou Deyi. Empirical study of consumers’purchase intentions in C2C electronic commerce.Tsinghua Science and Technology, 2008, 13(3): 287-292.



[17] Jesse W J Welteverden, Orit Rotem-Mindali. Mobility effects of b2c and c2c e-commerce in the Netherlands: Aquantitative assessment. Journal of Transport Geography, 2009, 17: 83-92.



[18] Wang Zheng, Mao Kejing, Liu Xiao et al. An analysis for location factors that cause industrial agglom. Acta GeographicaSinica, 2005, 60(4): 567-576. [王铮, 毛可晶, 刘筱等. 高技术产业集聚区形成的区位因子分析. 地理学报, 2005, 60(4):567- 576.]



[19] Lu Jie, Bai Chenggang, Zhang Guangquan. Cost-benefit factor analysis in e-services using bayesian networks. ExpertSystems with Applications, 2009, 36(3): 4617-4625.



[20] Han Ruiling, Sun Jingyi, Duan Jie. Location selection of outdoor sport club websites in cities that based on neighborhood facilities. Economic Geography, 2009, 29(4): 551-555. [韩瑞玲, 孙静怡, 段洁等. 基于邻域设施的城市户外运动俱乐部网站的区位取向. 经济地理, 2009, 29(4): 551-555.]



[21] Yamamoto H, Ishida K, Ohta T. Modeling reputation management system on online c2c Market. Computational andMathematical Organization Theory, 2004, 10(2): 165-178.



[22] Kiku Jones, Lori N K Leonard. Trust in consumer-to-consumer electronic commerce. Information & Management, 2008,45: 88-95.



[23] Lu Zi, Han Ruiling, Duan Jie. Analyzing the effect of website information flow on realistic human flow using intelligentdecision models. Knowledge-Based Systems, 2010, 23(1): 40-47.



[24] Lu Zi, Zhao Yahong, Wu Shifeng et al. The time distribution and guide analysis of visiting behavior of tourism websiteusers. Acta Geographica Sinica, 2007, 62(9): 621-630. [路紫, 赵亚红, 吴士峰等. 旅游网站访问者行为的时间分布及导引分析. 地理学报, 2007, 62(9): 621-630.]
Outlines

/