Digitalization of the EU Economies and People at Risk of Poverty or Social Exclusion

Abstract

<jats:p>Despite the fact that a comprehensive analysis of digitalization processes in the EU member states has been carried out, the impact of a country’s digitalization level on the risks of poverty and social exclusion requires further investigation. The purpose of the paper is to verify a hypothesis that a higher level of national digitalization provides positive trends in reducing the risks of poverty and social exclusion for the population. The Digital Economy and Society Index (DESI) was used to evaluate the digitalization levels of the EU countries. The indicator “People at risk of poverty or social exclusion” (AROPE) was applied to estimate the poverty level. As the main research methods, the authors used a comparative and correlation analysis with respect to the above-mentioned indicators, as well as the Monte Carlo method in order to evaluate the probability of a change in the indicator “population at risk of poverty or social exclusion” in 2021. The EU countries with higher digitalization levels have a lower percentage of the population at risk of poverty and social exclusion. However, a higher digitalization level of the EU member states does not provide an accelerated risk reduction of poverty and social exclusion. Statistical calculations with respect to the entire population of these countries mainly indicate reverse processes. At the same time, a further reduction of poverty and social exclusion level is less probable in the countries with a higher level of digitalization. For relatively poor segments of the population (the 1st and 2nd quintiles by income) in the EU member states, the level of digitalization does not play a significant role. For relatively wealthy segments of the population (the 3rd and 4th quintiles by income) the authors noticed a pattern: the higher the level of digitalization is, the lower the risk of poverty and social exclusion becomes. A pairwise comparison of countries with initially similar AROPE values showed that in most cases (3 out of 5), the countries with higher levels of digitalization showed a more significant reduction in poverty and social exclusion. However, the probability of further positive changes in this area is higher for the countries with a lower level of digitalization.</jats:p>

International Tourism Development in the Context of Increasing Globalization Risks: On the Example of Ukraine’s Integration into the Global Tourism Industry

“…Kyrylov et al (2020) and Von Essen et al (2020) argue that entrepreneurship in the field of green tourism is a specific type of tourism activity that has a social, environmental, and economic impact on the rural areas' development in the region. Dalevska et al (2019); Kharazishvili et al (2019Kharazishvili et al ( , 2020; and Kwilinski et al (2020) offered a methodology and instruments for economic-mathematical modeling to evaluate the degree of the development of international commercial and investment relationships, the degree of a lifespan, living standards and prosperity of international structures, the development of international tourism under the influence of sources for economic growth. In his research, Dzwigol (2020) uses the model of fuzzy logic to determine the level of regions' investment attractiveness, taking into consideration the factors of "security of investment activities" (criminogenic, environmental, and political), that allow determining unquestionable leaders of a region.…”

Macro Factors Influencing the Formation of Standardized Management Systems of an Enterprise

“…Quality management and environmental management systems are the most widespread in Europe and worldwide Kwilinski, Vyshnevskyi, Dzwigol issues are foremost associated with environmental socio-cultural factors. This group of factors also encompasses concepts such as leadership, rationality, material well-being, the importance of human rights, and hierarchical status, etc.…”

Eco-Efficiency and Human Capital Efficiency on the Example of Small and Medium-Sized Family Farms in the Selected European Countries

“…Even though unambiguous definitions of human capital are known, its measurement itself turns out to be a complicated process, due to the different factors used to measure it and the difficulty in expressing these factors numerically. The following are used as determinants of human capital: leadership experience, length of service, work experience in line with the speciality, organisational commitment of employees, IT skills, education, employee skills, attitudes, motivation, and international experience [17,18]. Despite the broad catalogue of listed variables, it is not a closed set and the use of further variables depends on the researchers and the compatibility of the variables used with the idea of human capital itself.…”