Spatial–temporal evolution of the distribution pattern of customer sources in tea trade of Fujian enterprise supply chain.

The temporal and spatial operation of commodity business activities is neither random nor accidental. It is characterized by inner laws and features. Based on spatio-temporal analysis in GIS, the objective of this study was to use spatial autocorrelation method and kernel density estimation to study the temporal and spatial distribution pattern of customer sources in tea trade extracted from enterprise supply chains in Fujian Province, China. Using data of Fujian tea business as an example, customer sources showed a typical clustered pattern overall that could be classified into several hot areas. The distribution of customer sources is dynamic along with time. These hot areas spread from coastal cities to inland cities, ranging from urban to suburban. Meanwhile, it showed a relatively irregular distribution in suburban areas with aggregation distribution near urban areas. This study applied GIS spatio-temporal analysis technology to the analysis of an enterprise supply chain, synthesizing both spatial and temporal information and successfully integrating business with geography. [ABSTRACT FROM AUTHOR]