Author
Listed:
- József Poór
(Department of Leadership and Management, Hungarian University of Agricultural and Life Sciences, 2100 Godollo, Hungary)
- Allen Engle
(Department of Management, Marketing, and International Business, Eastern Kentucky University, Richmond, KY 40475, USA)
- Szonja Jenei
(Kautz Gyula Faculty of Business and Economics, Széchenyi István University, 9026 Gyor, Hungary)
- Szilvia Módosné Szalai
(Kautz Gyula Faculty of Business and Economics, Széchenyi István University, 9026 Gyor, Hungary)
- Zdeněk Caha
(Department of Human Resource Management, Faculty of Corporate Strategy, Institute of Technology and Business, 37001 Ceske Budejovice, Czech Republic)
Abstract
The employment and labor market landscape has undergone significant transformations globally, including the three Central European countries examined in this study. Over the past decades, organizations in this region have transitioned from a state of full employment to labor shortages, raising the question: What factors have driven these changes? Our study aims to present a theoretical framework highlighting key macro-level factors, such as demographic trends, economic development, labor market dynamics, the impact of the COVID-19 pandemic, and the role of robotization and artificial intelligence. Based on two empirical studies conducted in 2019 and 2022 among Czech, Hungarian, and Slovak organizations, we analyzed the extent and causes of labor shortages, as well as the labor market effects of robotization. Using descriptive and non-parametric statistical methods, including frequency analysis and Mann–Whitney U tests, the study examined key trends and compared the two periods to identify significant shifts. The analytical approach of this study primarily aims to compare perceptions across occupational groups and between the two survey waves (2019 and 2022). Because most variables were measured on ordinal Likert-type scales and the datasets represent independent cross-sectional samples rather than a panel dataset, non-parametric methods were considered the most appropriate. More advanced causal modeling techniques, such as regression or factor analysis, were not applied because the objective of the research was exploratory and comparative rather than to establish causal relationships between variables. The findings reveal significant shifts in the perceived causes of labor shortages across occupational groups in the surveyed Central European organizations. In particular, increasing labor shortages were observed in specific job categories, alongside changes in the relative importance of the underlying drivers of labor shortages. While adopting robotization and artificial intelligence has been positively received, demographic decline and emigration remain critical challenges. The study provides practical insights for policymakers and corporate leaders regarding labor market challenges, workforce planning, and the potential role of robotization and artificial intelligence in addressing labor shortages. Although the research is based on a non-representative sample, it offers valuable insights into the Central European region’s employment and labor market trends. Future research could examine whether, in hard-to-fill positions, robotization and AI primarily provide indirect support by augmenting and reallocating human work, or whether they may serve as direct substitutes.
Suggested Citation
József Poór & Allen Engle & Szonja Jenei & Szilvia Módosné Szalai & Zdeněk Caha, 2026.
"Shifting Employment: Labor Challenges in Czechia, Hungary and Slovakia Beyond the Pandemic,"
Administrative Sciences, MDPI, vol. 16(5), pages 1-23, April.
Handle:
RePEc:gam:jadmsc:v:16:y:2026:i:5:p:210-:d:1931322
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