Abstract
Purpose. The aim of the article is to assess the impact of Industry 4.0 on employment in Ukraine and the world. The following tasks are set to achieve this goal: to analyse the historical impact of industrial revolutions on employment, including the characteristics of changes in its structure, as well as professional composition; highlight how the fourth industrial revolution differs from the previous three; consider the structure of available vacancies in Ukraine and assess how the national labour market is subject to automation. Methodology of research. This article uses the historical and logical unity method to analyse the impact of industrial revolutions on employment, as well as a comparison method to highlight the distinguishing features of Industry 4.0. A graphical method is applied to assess the sectorial structure of vacancies prone to automation in Ukraine. Findings. Industry 4.0 has been found to have common and distinctive features of the impact on employment with the previous three industrial revolutions. The structure of employment at different historical stages is analysed. It was found out that its structure is actively changing now; new professions and whole branches of application of human labour are appearing. The structure of the labour market in Ukraine is considered. It has been proved that Industry 4.0 can exacerbate inequalities between different sections of the population and lead to the disappearance of a large number of occupations, which today employ half of the workforce of national economies. Originality. An analytical approach to the definition of professions that are most prone to automation in the context of the fourth industrial revolution in the Ukrainian labour market has received further development. This approach simultaneously takes into account modern foreign practices and the national statistical base. Practical value. The obtained results in the course of the study can be used in the development of state programs to support employment in the national economy. Since people will require retraining and additional training due to the special propensity of their professions to automation and computerization. In addition, the obtained data can be used to determine the priority areas of state funding for educational institutions, which in the future will reduce youth unemployment. Key words: employment, the fourth industrial revolution, Industry 4.0, national economy, influence, industry structure, automation, computerization.
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