Transformations  in
Business & Economics

NO ONE LEFT BEHIND: ENABLING DIGITAL TRANSFORMATION OF HUMAN EUROPEAN WORKERS²
Benjamin Duke, Adriana Grigorescu, Cristina Lincaru, Vasilica Ciuca, Mihai Silviu Dragomir

ABSTRACT: Digital transformation generates rapid and radical structural changes, increasing the need to leave no one behind during the Industrial Revolution 4.0. New categories of workers are generated, and we can talk about the bots/robots as Digital Workers, the employees who are using digital facilities and have a digital education as Digital Human Workers, and the Human Workers who are not using digital instruments. Human Workers are the most exposed to being left behind once digital transformation is adopted by almost all the actors of the social and economic environment. Therefore, we find it urgent to dimension the scale of digital skills demanded at the EU level for the persons at risk of being left behind and estimate the average costs of transformative action at the enterprise level used for digital skills development. Public Employment Services have an important role among the enablers meant to accelerate digital skills for workers. Its primary target is the most vulnerable categories of workers. The study estimates the financial effort of continuous vocational training using a Linear Mixed Model on panel data from Eurostat. The results highlighted the new role of Public Employment Services as enablers of the Digital Transformation of Human European Workers, creating digital skills as portable skills that enhance the intersectoral mobility of Human Workers. Estimating the cost impact is relevant for policymakers and public decision-makers to create the framework of no one left behind. The findings contribute to a better understanding of the implementation effort for Enabling the Digital Transformation of Human European Workers.

KEYWORDS:  digital transformation, human workers, cost impact, risk of exclusion.

JEL classification:  J24, J62, M53, O33

²Acknowledgments:  This work was supported by a grant from the Romanian Ministry of Research, Innovation, and Digitalisation, Programme NUCLEU, 2022-2026, Spatio-temporal forecasting of local labour markets through GIS modelling [P5] /Previziuni spatio-temporale pentru pietele muncii locale prin modelare în GIS [P5] PN 22_10_0105.