文章基本信息

标题：Human Capital in Digital Economy: An Empirical Analysis of Central and Eastern European Countries from the European Union
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作者：Adriana Grigorescu ; Elena Pelinescu ; Amalia Elena Ion 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2021
卷号：13
期号：4
页码：2020
DOI：10.3390/su13042020
语种：English
出版社：MDPI, Open Access Journal
摘要：The hypercompetitive global economy of the 21st century is a hub of innovation, technology, talent, skills, speed, efficiency, productivity, and satisfaction. Within this context, the organizations are looking intensely for people with skills and talents that can differentiate themselves in all that noise. The human capital became slowly but surely a mean of efficiency and growth, especially through the premises of digitization, and a key issue of sustainability. The current research is meant to identify and highlight any correlations that might appear between the population’s welfare of 11 Central and Eastern European Countries (CEECs) which are members of the European Union (EU), and the components of the digitization trend, including the new human cloud industry, ICT, and the connectivity to the Internet of Things. In order to achieve the needed insights, the multiple regression analysis was employed, and the latter tested the panel models with fixed effects, both from a temporal and country perspective. The results showcased a positive connection between the dependent and independent variables, confirming that the digitization of the economy and the developed human capital will ultimately lead to the increase of population’s welfare. Moreover, the findings are consistent with specific insights for each of the 11 CEECs, showing that digitization and the influence of human capital is differentiated across the latter in terms of their overall effect and amplitude. The research is limited by the timeframe and countries included in the study, and it can be furthered by determining the impact of digitization on the economies of the EU28 countries grouped by level of development, and by using other significant indicators for analysis.