Tag: R23

DIGITALIZATION OF ECONOMY AND LIVING STANDARDS OF POPULATION IN RUSSIAN REGIONS

Nadezda Vasilievna SEDOVA

Dr. Plekhanov Russian University of Economics, Russia

nadseva@mail.ru

Lidia Sergeevna ARKHIPOVA

Ph.D. Plekhanov Russian University of Economics, Russia

Arkhipova.LS@rea.ru

Darya Mikhailovna MELNIKOVA

Ph.D. Plekhanov Russian University of Economics, Russia

Melnikova.D@rea.ru

Irina Fedorovna ALESHINA

Ph.D. Plekhanov Russian University of Economics, Russia

Aleshina.IF@rea.ru

Abstract

The study of territorial inequality in the modern economic space corroborates the relevance of the strategic goals of enhancing the living standards of the population amid digitalization of the economy. Despite the regional disparities in the social and economic development of the Russian regions, favorable factors for the responsiveness to digitalization in various economic and social spheres formed. They include the high quality of human capital, a relatively sufficient level of Internet access among population, modern infrastructure in a significant number of the regions, increased organizational costs for the introduction and use of digital technologies, etc. Therefore, the purpose of the research is to assess the indicators of digitalization in the regions, their territorial disparities and model the indicators of living standards as well as the use of information and communication technologies by the population and in organizations. The research features a typology of regions according to the main indicators of digitalization with the identification of the top regions, where capital territorial entities of the Russian Federation and the northern regions with a high household income, an economy dominated either by processing and knowledge-intensive industries, or with a raw-material focus, stand out. It has been noted that over the past fifteen years, interregional differentiation by digitalization indicators has been decreasing, however, problems persist in the eastern remote and underdeveloped regions in the south of the country. The research is of practical value in terms of economic and mathematical modeling of digitalization and internetization process in relation to living standards of the population.

Keywords: digitalization, region (RF subject), indicators, human capital, internetization, modeling

JEL classification: R23, J610

 pp. 47-65

read more

TERRITORIAL DIFFERENTIATION OF LABOR AS A FACTOR IN THE SUSTAINABILITY OF REGIONAL ECONOMIES

Lidia S. ARKHIPOVA

PhD in Economics, Associate Professor, Department of National and Regional Economics, Plekhanov Russian University of Economics, Moscow, Russia

lidia.arkhipova@mail.ru

Abstract

One of the factors influencing the sustainability of economic processes is the level of labor force territorial differentiation across the country. In locations with high employment rate among the working-age population, as a rule, the indicators of economic efficiency and sustainability are high. The outflow of labor, in its turn, contributes to a shortage of personnel, a reduction in production and an influx of migrants. Therefore, despite the replaceability of the labor force by robotics and digital technologies, for Russia with its vast space, studying the consequences of interregional inequality can identify strategic areas for economic development. Thus, the purpose of the research is to assess the degree of inter-regional inequality in the provision of the country’s regions with labor as one of the economic sustainability factors. The study of territorial inequalities in the economic space promotes the understanding of the importance of the strategic tasks in economic development of a complex, subordinate and multicomponent regional system of the Russian Federation. The processes of territorial inequality are greatly influenced by the migration flows, expressed in the outflow of the population mainly from the eastern regions. Significant migrations are common among rural migrants from the Far Eastern, Siberian and Urals Federal Districts. Therefore, the main influx of migrants is characteristic of the Central, North-Western and Southern districts. The contribution of the present research to economic science consists in justifying the prioritized support and development of the territories that are losing population and, accordingly, labor force.

Keywords: region (RF subject), territorial differentiation, labor force, development factors.

JEL classification: R23, J610

read more

PATTERNS OF MAINLY TOURISM SECTORS AT LOCAL LEVEL BY EMPLOYEE’S CHARACTERISTICS USING GIS MULTIVARIATE CLUSTERING ANALYSIS – ROMANIA CASE STUDY

Cristina LINCARU

Dr, FeRSA, Department of Labour Market, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0001-6596-1820

cristina.lincaru@yahoo.de

Speranța PÎRCIOG

Dr, Scientific Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0003-0215-038X

pirciog@incsmps.ro

Draga ATANASIU

Senior Researcher, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0002-9695-8592

incsmps1@incsmps.ro

Cristina STROE

Senior Researcher, Department of Social Policies, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0001-8384-6084

cristinaradu@incsmps.ro

Vasilica CIUCĂ

Dr, Dr, General Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0003-4687-6377

silviaciuca@incsmps.ro

Adriana GRIGORESCU

Dr., Department of Public Management, National University of Political Studies and Public Administration,  Correspondent Member of Academy of Romanian Scientists, Bucharest, Romania ORCID ID: 0000-0003-4212-6974

adrianagrigorescu11@gmail.com

Abstract

The tourism sector, before the Corona Strikes, works as a inclusive development engine for many countries’ economies and labour markets. In a global world, with increasing travel opportunities, tourism offers both labours intensive and knowledge-intensive activities, across many economic sectors. Tourism is a spatially dependent sector and also a tradable one. The Methodology for tourism statistics (Eurostat 2014),  Tourism Satellite Accounts (TSA 2010) and The International Recommendations for Tourism Statistics 2008 (IRTS 2008) differentiate the “mainly tourism” industries at four digits. We identify the natural cluster by number and pattern, at 3189 local spatial units (NUTS 5) by eight attribute variable employees: gender (male, female), age (youth, adult and aged) and education detained level (low, medium and high). Sectors are detailed at two digits only (H51- Air transport, I55 – Hotels and other accommodation facilities and N79-Activities of tourist agencies and tour operators; other reservation services and tourist assistance). Romanian National Institute of Statistics provides 2011 Census data. We apply the Multivariate Clustering Analysis with K Means algorithm as a Spatial Statistical Tool in Arc Gis Pro 2.3, an unsupervised machine learning an Artificial Intelligence technique, appropriate for Big Data. Clusters resulted illustrates natural hidden patterns of local labour markets pooling in the sense of Urban& Jacobian economies, but also some insight regarding the Morettian externalities sources. These results are useful for Regions Smart Specialisation Strategies development of human resources & talents to increase innovation capabilities and inclusive job creation, but also for a prompt recovery post-Covid Pandemic.

Keywords: tourism, labour force characteristics, Multivariate Clustering Analysis, local labour markets, regional specialisation, education level, age and gender analysis

JEL classification: J210, C38, R23

read more