We apply methods of exploratory spatial data analysis (ESDA) to examine variation in logistics industry in south China based on the characteristics of regional logistics. This paper investigates the regional disparities at city level in south China by global and local spatial autocorrelation analysis, with the support of Arc Map and Geoda software. It visualizes the regional distribution of logistics industry by box map, and analyzes the statistical data of south China logistic industry by Moran's I scatter plots and Local Indicators of Spatial Association (LISA) map. The results show that the Moran's I for per capita GDP is higher than that for logistics industry in south China. The paper has derived some implications for policy makers at the end.
Published in:
Knowledge Acquisition and Modeling (KAM), 2011 Fourth International Symposium on
Date of Conference: 8-9 Oct. 2011