Search results

The purpose of this paper is to determine the priorities of formation of competencies during training of digital personnel for industry 4.0.

The author performs two experiments for determining the scenario according to which industry 4.0 develops and will develop: the first experiment is aimed at determining the influence of the number of robots at unemployment level in 2019 and 2022 with the help of regression and correlation analysis (regression curves are built). The second experiment is connected to evaluation of the ratio of the number of robots to the number of population in 2019 and 2022. The research objects are countries with the highest number of robots in the world – i.e. with the highest level of development of industry 4.0; the information and empirical basis is materials of the International Federation of Robotics and the International Monetary Fund for 2019 and their forecasts for 2022.

The results of the performed experiments showed that in 2019 and 2022 the level of robotization of socio-economic systems of the countries of the world will be very low, and robotization will not cause growth of unemployment. Based on this, it is concluded that industry 4.0 will be developing according to the scenario of moderate automatization and robotization with preservation of domination of human labor in most business processes and spheres of economy. Communications with people will constitute the basis of the activities of digital personnel, and social competencies (with obvious significance of technical competencies) will be of top priority for them.

It is substantiated that technical competencies, with their large importance, will move to the background, while the key task will be society’s adaptation to the new technological mode and making social competencies the highest priority. The social and technical competencies of digital personnel in view of the performed tasks for industry 4.0 are determined.

This paper aims to determine the trends and prospects of the development of social entrepreneurship in Russia and Asian countries.

The methodology includes trend, regression, and correlation analysis and scenario (imitation) modeling and elaborates on perspectives and recommendations for further development of social entrepreneurship in Russia and Asia.

Despite the active development of social entrepreneurship in Russia and Asian countries (its share in the structure of GDP of these countries constituted 2.6% on average in 2018), it accounts for a small contribution to domestic development of socio-economic systems. These countries of Asia in 2018 were peculiar for low level of social freedoms (70th position in the world), low level of healthcare (51st position), moderate level of ecological effectiveness (61.33 points out of 100), moderate level of education (0.767 points out of 1) and low level of development of infrastructure (39 points out of 100). In the provision of social freedoms and healthcare, social entrepreneurship is least developed and is peculiar for a tendency for a decrease. The difference between demand and offer of social entrepreneurship causes an imbalance of the market of social (non-profit, volunteer and charity) services in these countries. This imbalance is to be overcome with the recent tendency of digitization of social entrepreneurship in Russia and Asian countries.

Digitization occupies the last position among the factors of the development of social entrepreneurship. Tax stimulation of social entrepreneurship is preferable, so it is recommended to pay primary attention to it until 2022, for the provision of the balance of the market of social services.

The purpose of this article is to determine the future proportion and variants of usage of human intellect and artificial intelligence (AI) in entrepreneurship of industry 4.0 that fits social entrepreneurship the most. It could be convergence (simultaneous utilization during the same entrepreneurial processes with the emphasis on unique features by the terms of the competition) or divergence (usage during different business processes by the terms of labor division).

The authors determine the influence of usage of human capital and AI on the efficiency of social entrepreneurship. The authors identify the perspective directions of usage of AI in social entrepreneurship and evaluate the readiness and interest in the implementation of these directions of concerned parties. The authors also model the optimal proportions and the variant of usage of human intellect and AI in social entrepreneurship in the conditions of Industry 4.0 in the future (until 2030).

It is found that social entrepreneurship will use the opportunities of Industry 4.0 for optimization of its activities until 2030, but will refuse from full automatization, using human intellect and AI at the same time.

The most perspective directions of application of AI at social companies are a collection of social goods and services, marketing studies and promotion of social goods and services. Neither convergence nor divergence of human and artificial intellectual capital does not fully conform to the interests of concerned parties. The most preferable (optimal) variant of usage of human intellect and AI in social entrepreneurship in the Industry 4.0 is human intelligent decision support.

This paper aims to solve the problem of reduction of disproportions of the global economy and overcoming the underrun of Asian countries from Europe. The author offers a hypothesis that the reason of such underrun is the existence of “underdevelopment whirlpools” in Asian countries. The purpose of this paper is to verify this hypothesis and to determine problems and perspectives of economic growth in Asian countries.

As tools for verification of this hypothesis, the author uses the methodology of analysis of “underdevelopment whirlpools”, aimed at the determination of problems and perspectives of economic growth in countries of Asia; methodology of strengths, weaknesses, opportunities, threats (SWOT) analysis for determination of key factors of economic growth in countries of Asia; instrumentarium of theory of games for the evaluation of effectiveness of the use of various strategies of economic development of Asian countries.

As a result of the research, the author proves the offered hypothesis and offers – as a solution to the problem of the existence of “underdevelopment whirlpools” in Asian countries – the use of new models of economic development in view of specifics of Asian countries, aimed at transition to new quality of economic growth.

A certain limitation of the conducted research is primarily theoretical substantiation of the necessity for overcoming the “underdevelopment whirlpools” in Asian countries and framework character of the offered recommendations. Therefore, during further research in this sphere, it is expedient to focus the efforts on the development of the system of practical measures for achievement of this purpose.

Practical significance of the author’s conclusions and recommendations consists in the possibility for their use during the development of state economic policy in Asian countries in the interests of overcoming the “underdevelopment whirlpools” and transition to the new quality of economic growth.

At the time of preparation of this paper, the concept “underdevelopment whirlpool” is rather new, and application of methodology of their calculation by the example of Asian countries in the context of analysis of problems and perspectives of economic grows constitutes the basis for originality, scientific value and novelty of the performed research.

The purpose of this paper is to determine the perspectives and to adapt the analysis of “underdevelopment whirlpools” to the current needs of state management of digital modernization of the regional market of educational services in the aspect of determination and assessment of its disproportions as a tool of managing the regional market of education and managing the process of reorganization of regional universities in the conditions of transition to Industry 4.0.

Analysis of “underdevelopment whirlpools”, adapted by the authors to the specifics of the regional market of educational services, is used. The statistical basis for this paper includes the information and analytical materials as a result of monitoring the effectiveness of activities of educational organizations of higher education and the materials of the Federal State Statistics Service of the Russian Federation.

“Underdevelopment whirlpools” of the Kirov branch of St. Petersburg University of the Humanities and Social Sciences are analyzed, and reorganization of this university is recommended. “Underdevelopment whirlpools” in Kirov Oblast are analyzed, and an increase of regulation of this market is recommended.

It is substantiated that the method of analysis of “underdevelopment whirlpools” could be a tool of managing the regional educational market and managing the process of reorganization of regional universities in the conditions of transition to Industry 4.0. The advantage of analysis of “underdevelopment whirlpools”, as compared to the existing similar methods of assessment of disproportions in the development of the regional market of educational services (e.g. comparative analysis and plan-fact analysis), is the possibility not only to evaluate the static underrun from the model/plan but also to study its dynamics (depth and speed of sucking into “underdevelopment whirlpool”), which allows achieving high precision of the results of assessment.

The purpose of this paper is to specify the conceptual foundations of educational cooperation of universities and companies of Industry 4.0 for maximizing its efficiency.

For determining the efficiency of educational cooperation of universities and companies of Industry 4.0 in modern Russia, the authors use the information and analytical materials on the results of monitoring of effectiveness of the activities of educational organizations of higher education in 2018. They use the indicators of the number of cooperation agreements and efficiency of cooperation – employment of graduates and the share of non-budget assets in revenues from the educational activities. These indicators are studied with the help of the method of regression analysis. The objects of the research are the flagship universities of the Central and the Southern Federal District of the Russian Federation.

Low efficiency of the educational cooperation of universities and companies of Industry 4.0 in modern Russia is observed. The authors show by the example of the flagship universities of the Central and Southern Federal Districts of the Russian Federation in 2018 that multiple agreements on their cooperation with the companies of regions in which they are located do not ensure high values of the indicators of employment of their graduates and the share of non-budget assets in revenues from the educational activities.

An algorithm of developing the educational cooperation of universities and companies of Industry 4.0 and a model of educational cooperation of universities and companies of Industry 4.0 are offered. The authors’ recommendations specify the conceptual foundations of the educational cooperation of universities and companies of Industry 4.0, as they orient the participants of this cooperation at achievement of specific formalized results and show the mechanism of achieving them.

The purpose of the paper is to model the modern global practice of social management of human capital – at the state and corporate levels – to determine the perspectives of its optimization and to develop the basic principles of a new methodological approach to social management of human capital, which is preferable in the conditions of social market economy.

The author uses mathematical tools, including correlation and regression analysis. These are applied to determine the influence of each of the 12 indicators for the labor market that are presented as part of The World Economic Forum's (WEF’s) ”The Global Competitiveness Report 2019” on The United Nations Development Programme's (UNDP) Human Development Index. The research objects are countries from each of the four categories of nations, as distinguished by UNDP, in the Human Development Index. By unifying the 2019 data from UNDP and WEF, a data set is formed.

It is substantiated that in modern economic practice, it is impossible to achieve the “ideal” conditions necessary for applying existing methodological approaches to the social management of human capital, which reduces how effectively current approaches function. Foundation on the existing methods leads to uncertainty as to management of human capital, which is social by 95.14% in 2019. Though the achieved value of the social management of human capital is close to being optimal, it is still not enough to achieve a high level of human development, which was 0.685 on average for the global economy in 2019 and is likely to increase by 31.43% until 2025, for acknowledging the social market status of the modern economy.

It is proven that there is a need for a new, mixed, methodological approach to the social management of human capital, which would optimally combine the best practices of both state and corporate management. The principles for the practical implementation of such an approach are offered, and proposals are developed to substantiate the contribution of this approach to the achievement of the global goals of sustainable development.