近年来,随着网络的普及、公众对网络购物认识程度的提高、物流业和经济环境的支持,以淘宝网为代表的C2C电子商务在中国呈现出迅猛发展的态势.本研究基于中国最大的C2C电子商务网站——淘宝网的数据,以中国大陆354 个地级城市为研究对象,利用GIS工具和空间计量经济学中的四分位分布、Cartogram 分布、Moran’sI 指数等方法,对淘宝网的网络店铺进行地理分布的实证研究.研究结果表明,中国的C2C电子商务发展和当地的经济发达程度非常相关.经济发展程度越高、物流业越发达的地区,其C2C淘宝网店数量越多.淘宝店铺的数量分布呈现出自东部沿海向内陆地区明显的梯度降低趋势.东部地区,尤其是以上海和杭州为核心的长江三角洲、以广州和深圳为核心的珠江三角洲地区,C2C网络店铺数量众多,网络购物经济非常发达.西部地区除了若干地区的省会城市之外,大部分地区的C2C电子商务均处于非常落后的状态.对354 个城市的空间自相关分析结果表明,中国的C2C电子商务发展存在着非常显著的、正的空间自相关性.即使是考虑人均指标,发展的空间集聚程度仍然非常之高.

The recent years have witnessed a popularity of Internet and on-line shopping. With the improvement of the public’s awareness of shopping on line, and supported by the highly developed logistics and economic environment, the C2C e-commerce is developing rapidly in China. Based on the data of the online stores on the largest C2C e-commerce website, Taobao.com, by using methods of Quartile map, Cartogram map, Moran’s I index et al in GIS tools and spatial econometrics, this paper studies 354 prefecture-level cities and discusses the development of C2C Taobao online stores of China. The results show that the C2C e-commerce is highly relevant to the economic development of the city. And the well-developed economic environment and logistics industry have promoted the boom of C2C e-commerce. In addition, in China, there tends to be a decreasing geographical distribution from the eastern coastal areas to inland areas. The C2C e-commerce is active in eastern China, especially in the Yangtze River Delta with Shanghai and Hangzhou at the center and the Pearl River Delta with Guangzhou and Shenzhen at the center. And the on-line shopping has become a well-developed industry. On the contrary, in western China, the C2C e-commerce is still in a very backward state except in some capital cities. The spatial autocorrelation analysis on 354 cities shows that there is a significant and positive spatial autocorrelation in the development of C2C e-commerce of China. Even taking the per capita index into consideration, we believe the C2C e-commerce still has a fairly centralized distribution.