The spatio-temporal characteristics and influencing factors of Taobao village's"growth-disappearance"in China
Based on the data of Taobao village issued by Ali Research Institute,"growth-disap-pearance rate"calculation,nuclear density analysis method and optimized hot spot analysis are used to analyze the spatio-temporal characteristics and influencing factors of Taobao village's"growth-disappearance"in China from 2009 to 2020.The results show that:①From the perspec-tive of time dimension,Taobao village in China has experienced the germination period,growth period and the rapid expansion period at the present stage.However,the"disappearance/growth"presented a"broken line"change trend of"steep at first,then slow down and then steep",indicating that the disappeared Taobao villages"increased at first,then decreased and then increased".② From the perspective of spatial characteristics,using four time sections in 2014,2016,2018 and 2020,it is found that the"growth-disappearance"of Taobao village in Chi-na gradually expanded to the central and western parts of the eastern coastal areas,which devel-oped from"dot"to"ribbon".In terms of spatial distribution,agglomeration and correlation,the"growth-disappearance"distribution of Taobao villages in 2020 shows a pattern of"decreasing from the east to the west,and deepening from the north to the south(coastal areas),the hot spots are concentrated and the cold spots are scattered".③ From the perspective of survival type,most of the Taobao villages in the eastern region are growth type,followed by low flow type,and a few areas are recession type.The central and western regions are mostly growth and low flow,followed by high flow and recession.④ From the perspective of influencing factors,ho-mogenization competition,industry involution,business operation skills,e-commerce transfor-mation and market sensitivity are the main reasons for the disappearance of Taobao village.The results of this study provide reference for the healthy development of Taobao village in rural ar-eas and the optimization of government policies.
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