数字化对欧盟国家公共行政、经济发展和福祉的影响

IF 1.6 Q3 PUBLIC ADMINISTRATION Central European Public Administration Review Pub Date : 2022-11-28 DOI:10.17573/cepar.2022.2.01
Armenia Androniceanu, I. Georgescu, O. Sabie
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引用次数: 8

摘要

目的:近年来,数字化一直是创造就业机会和促进经济增长的驱动因素。然而,国家和部门的数字化程度参差不齐。本文重点讨论了影响欧盟国家经济发展和福祉的各种因素。其目的是展示欧盟国家在数字化转型方面的演变,以及电子政务、人类发展指数、劳动生产率和经济增长等其他指标如何影响2019-2020年欧盟国家的福祉。设计/方法/方法:该数据集由从欧统局和世界银行数据库中提取的15个数字指标组成。我们采用主成分分析和聚类分析。研究结果和实际意义:主要研究结果表明,第一个维度——被命名为创新对幸福感的影响——主要由电子政务、信息和通信技术专家总数的百分比、个人互联网使用、人类发展指数、数字化指数、幸福指数、人力资本和数字技术的整合决定。第二个维度的特点是政府支出和生产力。最后,第三个维度由GDP增长率主导。77.67%的总方差由前三个主成分解释。独创性:利用K-means聚类算法识别出四个聚类。所有四个集群都已确定,其中包括三个北欧国家的集群1排名第一,其次是发达国家的集群3和主要包括新兴经济体的集群4。
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The Impact of Digitalization on Public Administration, Economic Development, and Well-Being in the EU Countries
Purpose: Digitalization has been the driving change in creating jobs and increasing economic growth in recent years. However, the digitalization of countries and sectors is uneven. The paper focuses on various factors that have an impact on the economic development and well-being in EU countries. Its purpose is to show the evolution of EU countries in terms of digital transformation and how other indicators, such as e-government, human development index, labour productivity, and economic growth influenced the well-being in EU countries in 2019–2021.Design/methodology/approach: The dataset consists of 15 numerical indicators extracted from Eurostat and World Bank databases. We apply principal component analysis and cluster analysis.Findings and Practical Implications: The main research results show that the first dimension – named the impact of innovation on well-being – is dominated by e-government, the percentage of ICT specialists in total, internet use by individuals, the Human Development Index, the Digitalization Index, the Happiness Indicator, human capital, and the integration of digital technology. The second dimension is characterized by government expenses and productivity. Finally, the third dimension is dominated by the GDP growth rate. 77.67% of the total variance is explained by the first three principal components.Originality: Four clusters have been identified by means of the K-Means clustering algorithm. All four clusters are well determined, with cluster 1 including the three Nordic countries ranking first, followed by cluster 3 of well-developed countries and cluster 4 containing mainly emerging economies.  
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CiteScore
2.10
自引率
28.60%
发文量
7
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