Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Exploring the laws and mechanisms of the diffusion of government big data policies, which can not only provide theoretical support for the formulation of future government big data policies, but also improve the effectiveness of policy implementation.[Method/process] The social network analysis method and thematic analysis method were used to analyze 213 government big data policies. This paper constructed a reference relationship network between policies, and analyzed the time characteristics, spatial characteristics and theme features of policy diffusion based on this.[Result/conclusion] In the time dimension, China's government big data policy presents a typical S-curve diffusion feature; in the spatial dimension, it has geographically unbalanced distribution characteristics and hierarchical shading characteristics; in the subject dimension, it has the characteristics of integration with inheritance and innovation, the value of the core value of the reference policy in the process of diffusion has been inherited.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] The hierarchical relationship of the factors affecting the initial public acceptance behavior of government open data is clarified, which can improve the public acceptance and use efficiency of government open data. It can also provide theoretical support for the formulation and improvement of the government's open data related strategy.[Method/process] Based on the situational theory, 13 factors affecting the initial public acceptance behavior of government open data were extracted by the expert survey method. Using the model of interpretation structure model, the relationship structure model of the factors affecting the public acceptance of government open data was constructed.[Result/conclusion] The results show that, the relationship structure model of the public acceptance of government open data includes 5 levels, which can be divided into 3 levels:representation layer, intermediate layer and fundamental layer. The representational factors include system resources, task urgency, and platform operations; the intermediate factors include requirements clarity, task topics, information awareness, information knowledge and information capabilities; the fundamental factors include education, age, policies and regulations, social influence and platform design.
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