SCIENTIA GEOGRAPHICA SINICA ›› 2020, Vol. 40 ›› Issue (6): 928-938.doi: 10.13249/j.cnki.sgs.2020.06.008

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Influencing Factors of Online Shopping Frequency of Residents and Spatial Differences of These Factors in Guangzhou City

Deng Qinghua1,2(), Xue Desheng1,*(), Gong Jianzhou2   

  1. 1. School of Geography and Planning, Sun Yat-Sen University,Guangzhou 510275, Guangdong, China
    2. School of Geographic Sciences, Guangzhou University, Guangzhou 510006, Guangdong, China
  • Received:2019-07-30 Online:2020-06-01 Published:2020-12-07
  • Contact: Xue Desheng;
  • Supported by:
    National Natural Science Fundation of China (41201103).


Online shopping has now become an important channel for residents to shop. To clarify the influencing factors of online shopping behavior is helpful to the formulation of e-commerce development strategy and the layout planning of physical business. Based on 1 156 online shopping behavior questionnaires of Guangzhou residents on November 2015 and March 2016 and the data of Point of Interest (POI) in 2016, this article explores the influence of 4 factors including 17 indicators on the online shopping frequency: personal socio- economic attributes, commodity characteristics, spatial environment and logistics express delivery, by using ordinal logistic regression model from whole city and different locations of Guangzhou. The results show that: 1) There are differences in the number, intensity and direction of influencing factors in different spatial scales and locations. The number of influencing factors is the largest in the whole city and the least in the outer suburbs. The effect of each factor is strong in the inner suburb and the whole city, but weakest in the outer suburb. The importance of return service plays an opposite role in the inner suburb and the central area. 2) Some spatial environmental indicators have an impact on the online shopping frequency. Urbanization level and accessibility of commercial centers have an impact on the whole city. Residents in higher urbanization level region and closer to the commercial center have higher online shopping frequency, which supports innovation diffusion hypothesis. The number of express delivery points has an impact on the central area. Residents with more express delivery points in residential areas have higher online shopping frequency. Other spatial environmental factors have no significant impact. 3) Personal socio-economic attributes have greater impact on the online shopping frequency than spatial environmental factors. Gender and age are the most important indicators, followed by education, occupation and monthly income. Women, young people, highly educated, upper-middle income residents have higher online shopping frequency. Commodity characteristics and express logistics indicators have a greater impact on the online shopping frequency in different regions. Residents who pay more attention to commodity characteristics have higher online shopping frequency. Residents with higher acceptance of the proportion of freight to transaction and express time have higher online shopping frequency.

Key words: online shopping frequency, Point of Interest (POI), ordinal logistic regression, Guangzhou

CLC Number: 

  • K902