摘要
当前政府大数据治理能力还有较大的提升空间。首先,识别了政府大数据治理能力关键影响因素,确定了主要影响因素间的相互关系,为提升政府大数据治理能力指明了方向。其次,基于文献分析法和德尔菲法,从政府体系内部和外部两个角度提取了10个政府大数据治理能力影响因素,采用ISM模型分析了政府大数据治理能力影响因素之间的层次关系。最后,应用MICMAC模型计算出各因素的驱动力和依赖性,并据此进行分类。研究结果表明:公众需求、政策制度、大数据治理意识和经济发展水平是最重要的驱动型因素,对其他因素的影响较大,其中公众需求为最根源的影响因素。研究结论对提升政府大数据治理能力具有理论参考价值。
At present,the government big data governance capability still has significant room for improvement.Firstly,the key influencing factors of government big data governance capability were identified,the interrelationships between the main influencing factors were determined,providing the direction for improving government big data governance capability.Secondly,based on literature analysis and the Delphi method,10 factors affecting government big data governance capabilities were extracted from both the internal and external perspectives of the government system,and then the ISM model was used to deeply analyze the hierarchical relationship between the factors affecting government big data governance capabilities.Finally,the MICMAC model was applied to calculate the driving force and dependence of each factor,and classify them accordingly.The research results show that public demand,institutional policies,big data governance awareness and economic development level are the most important driving factors,which have a greater impact on other factors,among which public demand is the most fundamental influencing factor.The research conclusions have theoretical reference value for improving the government big data governance capability.
作者
罗康明
周利平
苏红
LUO Kangming;ZHOU Liping;SU Hong(Department of Economic and Trade,Jiangxi Biotech Vocational College,Nanchang 330200,China;School of Humanities and Public Administration,Jiangxi Agricultural University,Nanchang 330045,China;School of Marxism,East China Jiaotong University,Nanchang 330013,China)
出处
《河北科技大学学报（社会科学版）》
2024年第3期23-31,共9页
Journal of Hebei University of Science and Technology:Social Sciences
基金
江西省学位与研究生教育教学改革研究项目(JXYJG-2019-073)
江西省教育科学“十四五”规划项目(21YB030)
江西省教育厅高校人文社会科学项目(GL1554)。
