Abstract

Employment is one of key parameters of the economy, which characterizes its efficiency, possibility of using the labour potential and growth of population’s well-being. The level of employment is the most important indicator of the effectiveness of socio-economic policy of the state. A high level of employment in high-tech and science-intensive business areas is a driver of sustainable economic development of countries, increasing labour productivity, ensuring leadership in the market, and reducing the productions costs. Thus, the assessment of the effectiveness of population employment in high-tech and science-intensive service areas is significant today, as it is a comprehensive assessment of the country’s development, its current state in high technologies and further prospects for working with them. The research purpose consists in determining the maximum, most effective value of the population employment efficiency index in high-tech and science-intensive service spheres based on cross-country cluster analysis. The sample of countries all over the world were divided into 3 clusters, taking into account the rating value of the following indices: employment in high- and medium-high-tech production sectors and science-intensive business service spheres; enterprises that conducted training to develop / improve the ICT skills of their personnel; new registered enterprises. During the research there were statistical data analysis, cluster analysis using Ward’s method and software Statgraphics, optimization method using Frontier Analyst software. As a result, the efficiency of population employment in high-tech and science-intensive business service sectors of 36 countries in 2021 was determined, and accordingly reference countries with high population employment in this research sphere were identified. The potential reserves for increasing the targeted value of the population employment index in high-tech and science-intensive sectors were also characterized. The obtained results can be useful for business managers, they can adopt the experience of doing business in countries with more effective indicators, with the aim of developing employees, providing them with new training and knowledge that will facilitate doing business in the future.

Keywords: economic growth, efficiency, innovation, labour potential, new business, population employment, research, sustainable development, technologies.

JEL Classification: J21, J24, O11, O32.

Cite as: Koibichuk, V., Samoilikova, A., and Habenko, M. (2022). The effectiveness of employment in high-tech and science-intensive business areas as important indicator of socio-economic development: cross-country cluster analysis. SocioEconomic Challenges, 6(4), 106-115. https://doi.org/10.21272/sec.6(4).106-115.2022

This work is licensed under a Creative Commons Attribution 4.0 International License

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