Vladyslav Smiianov
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Digital skills composition and adult learning: Human capital in the knowledge economy
Bakhytzhamal Zhumatayeva
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Oksana Herasymenko
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Vladyslav Smiianov
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Aliya Myrzabekovna Atenova
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Vahe Mikayelyan
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Svitlana Cherkasova
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Oleksandr Firstenko
doi: http://dx.doi.org/10.21511/kpm.10(3).2026.15
Knowledge and Performance Management Volume 10, 2026 Issue #3 pp. 242-262
Views: 27 Downloads: 4 TO CITE АНОТАЦІЯType of the article: Research Article
Digital skills anchor human-capital policy in the European knowledge economy, yet which dimension of digitalization moves lifelong learning remains unsettled, as connectivity, specialist, and training targets are pursued in parallel. The paper aims to quantify the association between the workforce’s digital-skills composition and adult participation in learning across 31 European economies, using an unbalanced annual 2015–2023 panel supplemented by DigComp 2.0 waves for 2021–2025, and to draw implications for human-capital policy. Both are estimated with two-way fixed-effects models, lagged regressors, country-clustered standard errors, and an audit of survey redesigns. The lagged employment share of ICT specialists is positively associated with adult learning: a one-percentage-point increase corresponds to a 1.38-point gain (β = 1.379, p = 0.034; wild-cluster bootstrap p = 0.077). Diffusion-type measures – daily internet use and online health-information seeking – show no such link (β = 0.021 and 0.025), although the specialist coefficient is not statistically distinguishable from theirs. The coefficient stays positive across estimators and samples (0.44–1.76) and significant in the pre-break 2015–2020 window (β = 1.536, p = 0.024); a formal test does not reject constancy across the 2021 EU-LFS redesign. Direct skills measures point the same way but stay insignificant (β = 0.042–0.121); unemployment is counter-cyclical (β = 0.583–0.694). The evidence is consistent with rebalancing policy from connectivity targets towards workforce skills composition – a margin unmeasured in Ukraine, Kazakhstan, and Armenia – with specialist pipelines as the instrument most directly supported and enterprise ICT training as a possible, not yet established, channel.
Acknowledgment
Vladyslav Smiianov contributed to this article within the framework of the research project “Modelling the impact of economic digitalization on public health in Ukraine in the context of preserving human capital”, funded by the Ministry of Education and Science of Ukraine (State Registration No. 0126U001085).
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