Influencing Factors And Multi-path Research Of Local Government Policy Diffusion In China

The opening of government data has the major economic and social significance of deepening "Internet + government affairs",improving government transparency and work efficiency,accelerating the transformation of government public services,and occupying new economic growth points.In addition,in the current data open cities,the urban open routes and backgrounds are not the same.There are cities with strong economic bases such as Beijing and Shanghai,and cities with such weak economic bases as Guiyang and Wuhai.The opening situation is diverse and complex,so Investigating factors affecting the openness of data,further research on different open routes of cities is needed to promote urban data more specifically.However,from a general perspective,the opening of government data is still in its infancy in China,and the data opening situation is still not ideal,and the policy of data openness is “one size fits all”.Therefore,how to recognize the current data open model and further promote the openness of data is a major problem that needs to be solved urgently.This paper firstly summarizes the existing theoretical literature,reconstructs the theoretical model with TOE theory and innovation diffusion theory,and classifies the influencing factors into internal and external dimensions.Based on the idea of causality,this paper first analyzes 281 cities through logistic regression to identify the information foundation,financial dependence,social appeal,provincial pressure and official stability of existing theories.Probability has a significant impact.On this basis,through the rough and precise matching,the variables and the research objects are further focused.Through qualitative comparison analysis,the current government data is divided into four types: economic cost type,resource mining type,internal and external interaction type and politically dominant type.Types of open cities and unopened cities have put forward targeted policy recommendations to promote the sustainable development of government data.