Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 1461-1467, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1461-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 1461-1467, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1461-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Sep 2017

14 Sep 2017

ANALYSIS OF SPATIAL PATTERN AND INFLUENCING FACTORS OF E-COMMERCE

Y. Zhang, J. Chen, and S. Zhang Y. Zhang et al.
  • School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

Keywords: E-commerce, spatial pattern, spatial autocorrelation, influencing factor, geographical weighted regression

Abstract. This paper aims to study the relationship between e-commerce development and geographical characteristics using data of e-commerce, economy, Internet, express delivery and population from 2011 to 2015. Moran’s I model and GWR model are applied to analyze the spatial pattern of E-commerce and its influencing factors. There is a growth trend of e-commerce from west to east, and it is obvious to see that e-commerce development has a space-time clustering, especially around the Yangtze River delta. The comprehensive factors caculated through PCA are described as fundamental social productivity, resident living standard and population sex structure. The first two factors have positive correlation with e-commerce, and the intensity of effect increases yearly. However, the influence of population sex structure on the E-commerce development is not significant. Our results suggest that the clustering of e-commerce has a downward trend and the impact of driving factors on e-commerce is observably distinct from year to year in space.