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作 者:何静[1] 旷开源[2] HE Jing;KUANG Kaiyuan(Zhejiang Technical Institute of Economics,310018,Hangzhou,Zhejiang,China;Administration School,Zhejiang University of Finance and Economy,310018,Hangzhou,Zhejiang,China)
机构地区:[1]浙江经济职业技术学院,浙江杭州310018 [2]浙江财经大学管理学院,浙江杭州310018
出 处:《特区经济》2024年第4期59-62,共4页Special Zone Economy
摘 要:“郡县数治”是我国古代郡县制与大数据技术相融合的智慧管理系统。本文在相关理论回顾的基础上,通过实地调查和追踪研究,分析了“郡县数治”技术应用从1.0版本“政务云服务”和2.0版本“政务云服务+征信云服务”到3.0版本“政务云服务+征信云服务+金融云服务”的演进过程,并基于推拉理论分析了郡县制与大数据技术融合的拉力因素、推力因素和中间障碍因素,构建了相关模型探究其得以实现融合的内在机理。研究认为,“郡县数治”是政府职能转变、城市治理生态体系的优化以及评价机制民主化等拉力因素,经济发展、技术进步、组织和个人服务预期、社会公平与效率预期、组织规模扩大等推力因素以及传统观念、管理风险和监督成本等中间障碍因素相互作用的结果。“Digital governance of prefectures and counties”is an intelligent management system which fuses the system of prefectures and counties in ancient China with modern big data technology.Based on the review of relevant theories,field investigation and tracking study,this paper analyzes the evolution process of the technology application of“digital governance of prefectures and counties”from 1.0 version of“govern-ment cloud services”and 2.0 version of“government cloud services+credit cloud services”to 3.0 version of“government cloud services+credit cloud services+financial cloud services”.Then based on the push and pull theory,it analyzes pull factors,push factors and intermediate obstacle factors of the fusion of big data technology and the system of prefectures and counties.After that,it builds the relevant model and ex-plores its internal mechanism to achieve fusion.The study finds that digital governance of prefectures and counties is the interaction result of pull factors such as the transformation of government functions,the optimization of urban governance ecosystem and the democratization of evaluation mechanism,push factors such as economic development,technological advances,organizational and personal service expectations,so-cial equity with efficiency expectations and the expansion of organizational scale,and intermediate ob-stacle factors such as traditional concepts,management risks and supervision costs.
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