A Comparative Analysis Of Innovative Production Factors In The Russian Federation Regions
The hypothesis, according to which the direction of financial capital flows and the transfer of high technologies in developed national economies are mainly determined by the potential of human capital located in a specific territory, is tested in the article. In the era of the fourth industrial revolution, human capital becomes a strategic production factor for innovative economic growth. This study is aimed at analyzing the relevance of the current state of human capital of the Russian Federation regions to the level of innovative development of regional economies. To test the working hypothesis, an analytical algorithm was used to structure the data by factors of monitoring the development of the information society in the Russian Federation and the main indicators of science, innovations and advanced manufacturing technologies in the Russian Federation. The specifics of the development of this approach is the formation of a factor structure in the format of many clusters of the Russian Federation regions, differing in the level of development of human capital and the use of the advantages of disruptive technologies. A comparative analysis was carried out according to the following groups of factors for the Russian Federation regions: human capital, innovative capacity, science, innovations and advanced manufacturing technologies. The working hypothesis of the study, tested on the statistical data of the Russian Federation regions, is only partially confirmed.
Keywords: Human capitalinnovative growthdigital economyregional economy
The sustainable production growth of new qualitative characteristics of human capital is an important component of the strategy of innovative development of the world economy in the era of Industry 4.0. The prevalent success factor of innovative ventures in the territories is the concentration of highly qualified human resources acting as generators of innovative activity of strategic importance for the development of regional high-tech production. A number of researchers argue that economies "compete through people", sustainable innovative development depends on human capital, as well as the ability to manage talent (Chiappori, Galichon, & Salanié, 2019). The practice of capitalizing the workers’ research and productive capacity has a direct impact on the current state and development prospects of the high-tech sector of the economy in specific territories (Fletcher & Han, 2019).
In developed countries, during the era of the fourth industrial revolution, individuals equipped with developed human capital, combining both cognitive and non-cognitive skills, become a strategic production factor in the competitiveness of the economy. The winner in the competition is the economy, where not only new business ideas are generated, but also permanent processes of commercialization of innovations and their implementation in economic activity are organized. Human capital becomes a trigger for economic growth in the context of the fourth industrial revolution (Bucci, 2015; Lucas, 2018).
World practice of implementing the Industry 4.0 concept in industrial production confirms the hypothesis that human capital is becoming one of the main factors affecting investment decisions to localize high-tech production activities in a specific territory. Today, inter-territorial flows of financial capital and transfer of disruptive technologies are oriented not so much to territories rich in natural resources as carriers of human capital. Until recently, one of the main motives for making investment decisions was the availability of cheap labour in the territory. Whereas at the present time, highly qualified human resources and the availability of a local research base are becoming a priority resource that shapes decisions to invest in innovative industries. The territorial concentration of skilled workers, their knowledge and skills determine the investment attractiveness of the territory (Acemoglu & Restrepo, 2018).
The growth of global mobility of production and the short life cycle of innovative products leads to the fact that new industries are located where the concentration of human capital is high (Cauchie & Vaillant, 2016). The most important role of human capital is due to the fact that the most advanced industries and technologies are knowledge-consumptive, and they determine the dynamics of innovative growth (Ehrlich, Li, & Liu, 2017). Undoubtedly, factors such as the sales market, operating costs, national tax laws, and logistics are important when deciding on the location of a business. However, even the most favourable conditions do not facilitate the inflow of investments without the presence of human capital equipped with high-tech professional competencies.
The objectivity of the research of disruptive technologies in Industry 4.0, together with the economic analysis of human capital, is reflected in the International Digital Economy and Society Index (I-DESI), which is used in world practice to measure the progress of countries in the development of the digital economy and society. The index values for countries in 2016 are presented in Table
In Russia, there is a gap in the values of the I-DESI index (0.47) and the Human Capital subindex (0.63) of this index. Cross-country analysis of the ratio of these values has shown that Russia is superior to many economies developed in the field of high-tech in terms of the Human Capital subindex, in particular, the USA, EU-28 countries, Canada, China, Australia, New Zealand and is inferior to these countries in terms of development digital economy and society. The proportion of people employed in the information and communication technology sector in the total number of employed people in Russia during the period from 2010 to 2018 remains as low as at 1.6% (Federal State Statistic Service of Russian Federation, 2018a).
Human capital is primarily a carrier of skilled labour and technological knowledge, which form the basis of scientific and technological progress (Angelopoulos, Malley, & Philippopoulos, 2017). It plays a decisive role in the development of modern disruptive technologies and is an important factor in their effective use. "This means that the more important are no longer the technologies, but the people who develop them" (Zhudro & Zhudro, 2017, p.84). The development of telecommunication and information technologies requires that their creators and users have a high technological IQ and an appropriate level of interdisciplinary competencies, creating a qualification profile of the territorial "attraction" of investments. Today, such a qualification profile of the territory is crucial for the location of high-tech activities.
The current state of the constituent entities of the Russian Federation (RF) in terms of human capital development and digitalization of the economy is heterogeneous. Changes in the method and structure of production and employment in the constituent entities of the Russian Federation, as well as the widespread penetration of digital technologies and skills in all spheres of life are strategic challenges that regional authorities must meet in the era of digital globalization, which intensifies competition at the mesoscale.
Purpose of the Study
The purpose of this study is to test the relevance of the global trend of dependence of inter-territorial flows of financial capital and the transfer of high technologies largely on the potential of human capital located in a specific territory. This study is aimed at analysing the relevance of the current state of human capital of constituent entities of the Russian Federation to the level of innovative development of regional economies.
To achieve this goal, an analytical algorithm was used for structuring data by factors of monitoring the development of the information society in the Russian Federation (Federal State Statistic Service of Russian Federation, 2018a) and the main indicators of science, innovations and advanced production technologies in constituent entities of the Russian Federation for the period of 2010 – 2018 (Federal State Statistic Service of Russian Federation, 2018b). The specifics of the development of this approach consists in the shaping of a factor structure in the format of many clusters of the constituent entities of the Russian Federation, differing in the level of development of human capital and the use of the advantages of disruptive technologies.
Cluster formation is based on the analysis of statistical data by factors of human capital development and digitalization in the constituent entities of the Russian Federation through the method of cluster analysis, which allows identifying internal, directly immeasurable relationships between correlating factors. The procedure for cluster analysis of multidimensional data was carried out by the method of EM (Expectation Maximization). The method was implemented in the integrated development environment Rstudio using the mclust library, designed for statistical data processing and graphics.
A comparative analysis was carried out according to the following groups of factors for all constituent entities of the Russian Federation:
Science, innovation and advanced manufacturing technologies.
According to the factors of the groups “Innovative Capacity” and “Human Capital”, there is mainly a mismatch in the composition of entities that form clusters of the same rating. The number of matches in cluster composition is only 19 (22.6% of the total number of constituent entities of the Russian Federation, Table
A relatively full compliance in the cluster ratings was established for the following constituent entities of the Russian Federation: Moscow and St. Petersburg, Voronezh Region, Rostov Region, Chelyabinsk Region, Novosibirsk Region, Omsk Region, Tomsk Region, Lipetsk Region, Tula Region, Yaroslavl Region, Penza Region, Sakhalin Region, Trans-Baikal Territory, Amur Region, Kamchatka Territory, Khanty-Mansiysk Autonomous Region, Republic of Ingushetia, Chechen Republic. In the Kaliningrad Region and the Republic of Kalmykia, on the contrary, asymmetries were revealed in terms of the rating of human capital development (ranking No. 2) and innovative capacity (ranking No. 7). The serial numbers of the constituent entities of the Russian Federation are presented in Table
According to the factors of the groups “Science, Innovations and Advanced Manufacturing Technologies” and “Human Capital”, there is also a low degree of compliance in the composition of entities that form clusters of the same rating. The number of matches in the constituent entities of the Russian Federation that form clusters makes less than one third of the total number of constituent entities of the Russian Federation.
The results of the comparative analysis demonstrate a low degree of matching between the levels of accumulation and effective use of human capital and the levels of innovative capacity and the development of science, innovations and the use of advanced manufacturing technologies of the constituent entities of the Russian Federation. The working hypothesis of the study, according to which the direction of financial capital flows and the transfer of advanced technologies are mainly determined by the available potential of human capital localized in a specific territory, tested on the statistics of the constituent entities of the Russian Federation, is only partially confirmed. Therefore, when making a managerial decision on the creation and development of high-tech innovative industries in the constituent entities of the Russian Federation, the significance of the presence of developed human capital in the territory currently makes up from 20 to 30% of the total number of administrative, financial, natural, social and other factors affecting the investment attractiveness of the region.
- Abdrakhmanova, G. I., Vishnevskiy, K. О., Volkova, G. L., Gokhberg, L. M., Demyanova, A. V., … Shmatko, N. A. (2018). Digital economy indicators: 2018: Statistical compendium. Мoscow: HSE.
- Acemoglu, D., & Restrepo, P. (2018). Low-skill and high-skill automation. Journal of Human Capital, 2(2), 204-232. DOI: 10.1086/697242
- Angelopoulos, K., Malley, J., & Philippopoulos, A. (2017). Human capital accumulation and transition to skilled employment. Journal of Human Capital, 11(1), 72-105. DOI: 10.1086/690445
- Bucci, A. (2015). Product proliferation, population, and economic growth. Journal of Human Capital, 9(2), 170-197. DOI: 10.1086/680861
- Cauchie, G., & Vaillant, N. G. (2016). New firm survival: Isolating the role of founders. Human capital in accounting for firm longevity. Journal of Human Capital, 10(2), 186-211. DOI: 10.1086/686153
- Chiappori, P.-A., Galichon, A., & Salanié, B. (2019). On human capital and team stability. Journal of Human Capital, 13(2), 236-259. DOI: 10.1086/702925
- Ehrlich, I., Li, D., & Liu, Z. (2017). The role of entrepreneurial human capital as a driver of endogenous economic growth. Journal of Human Capital, 11(3), 310-351. DOI: 10.1086/693718
- Federal State Statistic Service of Russian Federation (2018a) Monitoring the development of the information society in the Russian Federation. Retrieved from http://www.gks.ru/free_doc/ new_site/figure/anketa1-4.html Accessed: 01.11.2019.
- Federal State Statistic Service of Russian Federation (2018b). Russian statistics yearbook. Мoscow: Rosstat.
- Fletcher, J., & Han, J. (2019). Intergenerational mobility in education: Variation in geography and time. Journal of Human Capital, 13(4), 585-634. DOI: 10.1086/705610
- Lucas, R. E. (2018). What was the industrial revolution? Journal of Human Capital, 12(2), 182-203. DOI: 10.1086/697243
- Zhudro, M. K., & Zhudro, N. V. (2017). Smart economy design - A new challenge for economic thought. In V. N. Shimov et al (Eds.), X International Scientific-Practical Conference “The Economic Growth of the Republic of Belarus: Globalization, Innovativeness, Sustainability” (pp. 84-85). Minsk: Belarusian State Economic University.
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