摘要
深入解析各政府省际总体差异、区域差异及动态演进趋势,有助于缩小政府数据开放差异,推动政府数据开放均衡发展,加快政府数字化转型。基于中国政府数据开放评估报告,运用面板熵值法测算我国21个省份的政府数据开放综合指数及四个子维度指数,并借助Dagum基尼系数和Kernel密度估计分析我国省际政府数据开放发展的区域差异及演进趋势。研究发现中国政府数据开放水平呈增长态势,政府数据开放水平存在明显的区域差异并逐渐扩大,四个子维度的区域差异情况各异,除西部区域以外,东部和中部区域的绝对差异均呈扩大趋势。本研究创新性地将基尼系数运用于政府数据开放均衡的主题中,并组合熵值法、Dagum基尼系数和Kernel密度估计三种方法,以递进方式研究政府数据开放总体差异、区域差异及未来演进动态,可较为完整全面地把握实际的政府数据开放差异情况。
This study delves into the overall differences,regional differences,and dynamic evolution trends of interprovincial government data openness in China,with the aim of narrowing these differences,promoting balanced development in government data openness,and accelerating the digital transformation of government.Based on the Chinese Government Data Openness Evaluation Reports,the study employs the panel entropy method to calculate the comprehensive index of government data openness and four sub-dimensional indices across 21 provinces.Additionally,the study utilizes the Dagum Gini coefficient and Kernel Density Estimation to analyze the regional differences and evolution trends of government data openness across different regions.The findings reveal that the level of government data openness in China is on the rise,with significant and gradually widening regional differences.The differences across the four sub-dimensions vary,and except for the western region,the absolute differences between the eastern and central regions are expanding.This study innovatively applies the Gini coefficient to the theme of government data openness and equilibrium and integrates the entropy method,Dagum Gini coefficient,and Kernel density estimation to provide a progressive and comprehensive analysis of the overall differences,regional disparities,and future evolution dynamics of government data openness.
作者
高凡
徐思佳
李易衡
Gao Fan;Xu Sijia;Li Yiheng(School of Public Administration,Southwest Jiaotong University,Chengdu,611731;School of Public Administration,University of Electronic Science and Technology of China,Chengdu,610031;School of Management,Beijing Institute of Technology,Beijing,100081)
出处
《信息资源管理学报》
CSSCI
2024年第5期59-74,90,共17页
Journal of Information Resources Management
关键词
数字政府
政府数据开放
区域差异
动态演进
Digital government
Open government data
Regional differences
Dynamic evolution
