Forecasting of the employment rate in the EU ICT field - Tetiana Zatonatska; Yuriy Klapkiv; Oleksandr Dluhopolskyi; Olha Fedirko (Comparative Economic Research. Central and Eastern Europe, 2022)
The ingrained tendency to implement information and communication technologies (ICT) in EU enterprises over the last decade has caused dramatic changes in the labor market. Since the demand for ICT personnel is growing, there is still a need to create a comprehensive strategy to effectively manage ICT specialists when restructuring enterprises. The aim of the research is to identify transferring processes between low- and high-skilled ICT personnel and predict the employment rate in the ICT field until 2025. A Markov chain was used as the method of analysis. Using statistical data about the employment rate of ICT personnel by education attainment level, we have built a Markov chain model that describes the processes of ICT personnel with different levels of education. Data from 2005 to 2019 was used to build forecasting because of the absence of the latest information. We demonstrate that with the help of digitalization, the employment rate of ICT staff in 2025 will increase by 64% compared to 2018. The research verifies that ICT personnel will be in great demand until 2023 and, importantly, low- and middle-skilled personnel will be in demand, as well as high-skilled personnel. The employment rate in the ICT field will be at its highest level in 2022 as the favorable economic conditions for ICT adoption will help it. The growing demand for low- and medium-skilled ICT staff are met both by staff relocation processes and by the increasing digitalization of business units and public sector institutions. The added value of the analysis is the prediction that the largest growth in ICT personnel employment will occur by 2023, but employment growth will slow down after that. The main obstacle to employment growth through digitalization is the global economic crisis because of different reasons.
Keywords: J23; F17; F66; O32; O52; 330; adoption; digitalization; employment management; labor demand; Markov chain