| The development of digital economy is a driving force to optimize economic structure,enhance regional competitiveness and promote high-quality economic development.However,China’s digital economy started late,and the distribution of digital dividends is more in the east than in the west,leading to a significant digital divide.In order to realize the coordinated development of digital economy,it is necessary to break down administrative barriers to form a joint force of development.Therefore,it is necessary to clarify the status,relationship connection and role of provinces in the digital economy network,and to identify the factors that may affect the province’s digital economy cooperation,which is the key to bridge the digital divide and promote the coordinated development of digital economy.Based on this,on the basis of using Arc GIS spatial visualization,Kernel density function and Moran index to describe spatial pattern,distribution dynamic evolution and spillover effects of digital economy,this paper uses the modified gravity model and social network analysis method to investigate the evolution characteristics of network from the perspective of whole network and node network,and explores the influencing factors of network formation based on exponential random graph model.The main conclusions are as follows:(1)The development of digital economy is gradually improving,and the growth rate in the central and western regions is faster.Except for the central region,the Kernel density function of the country and other regions is multi-peak.The main wave peaks are all located in the low-value area,and the internal differences of the main groups in the national,eastern and western regions is increase,and the internal differences in the central and northeastern regions become smaller.The development of the digital economy has significant spillover effects.(2)The network density is small,and the tightness tends to increase.Network efficiency and network hierarchy are declining year by year.(3)Jiangsu,Shandong and Guangdong have become the core of the network.Guizhou,Guangxi,Sichuan,Shaanxi show strong advantages of resource control in the later stage.(4)Bidirectional overflow plate and the net spillover plate have the greatest spillover effect on the net spillover into the plate,the internal spillover effect of the broker plate is the lowest,and the one-way connection of the net spillover into the plate is improved.(5)The spatial association network is transitive and tends to form an open triangular configuration.The improvement of economic strength,tertiary industry development level,scientific and technological innovation and information development level can increase the connection probability between nodes,while the high dependence of foreign capital inhibits the formation of cooperative relations,and the urbanization rate plays a negative role in the early stage of network evolution and becomes positive in the later stage.The formation of spatial association network is also affected by regional homogeneity and geographical proximity.Based on the conclusions,the following policy suggestions are put forward: the government should pay attention to the spatial linkage effect of the development of digital economy,and form the idea of coordinated development of digital economy “from part to whole”.The government should fully aware of the status and role of each province in the network as well as the function of the block.The government should consider all kinds of factors affecting the structure of digital economy correlation network,for example,the matthew effect should be used to enhance the cooperation intensity of the digital economy,and the compensation mechanism should be introduced to narrow the gap between provinces in economic strength,the development speed of the tertiary industry,the intensity of scientific and technological research and development,and the level of information and communication.Regional and neighboring provinces should overcome the sense of competition and establish a long-term cooperation mechanism. |