Differences in AI Adoption and Labour Productivity in EU Countries

Show simple item record
dc.contributor.authorMartinčík, David
dc.contributor.authorMartinčíková Sojková, Olga
dc.contributor.authorProcházka, Václav
dc.contributor.editorKresa, Zdeněk
dc.date.accessioned2026-01-22T09:42:10Z
dc.date.available2026-01-22T09:42:10Z
dc.date.issued2025
dc.description.abstract-translatedThis paper explores cross–border patterns in the adoption of artificial intelligence technologies (AI) and their association with labour productivity across the European Union. Using Eurostat data covering 27 EU member states between 2000 and 2024, we construct an unbalanced panel dataset and estimate several panel data models to identify determinants of productivity growth. After comparing pooling, fixed–effects, and random–effects models, the random-effects model is determined as the most fitting and reliable. Labour productivity growth is modeled as a function of Research & Development expenditure and tertiary education employment, from which country-specific intercepts are extracted to form an adjusted productivity indicator. These adjusted productivity values are then combined with the most recent AI adoption rates to identify regional patterns using k-means clustering. The results reveal three distinct clusters of EU countries: (1) Southern Europe, characterized by low AI adoption and low productivity growth; (2) Eastern Europe, showing low AI adoption but high productivity growth consistent with catch–up dynamics; and (3) Northern Europe, combining high AI adoption with stable productivity performance. The findings suggest that AI adoption alone does not automatically translate into higher productivity. Complementary conditions such as digital infrastructure and workforce skills play a crucial role. The study highlights significant regional disparities and provides a foundation for future research using firm–level microdata and longer AI time series.en
dc.description.sponsorshipSVK1-2025-002 XB-CON, SGS-2024-030en
dc.format14 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.24132/ZCU.XB-CON.2025.421-436
dc.identifier.isbn978-80-261-1341-6 (print)
dc.identifier.isbn978-80-261-1342-3 (online)
dc.identifier.urihttp://hdl.handle.net/11025/64518
dc.language.isoenen
dc.publisherUniversity of West Bohemia in Pilsenen
dc.rights© University of West Bohemia in Pilsenen
dc.rights.accessopenAccessen
dc.subjectumělá inteligencecs
dc.subjectshluková analýzacs
dc.subjectEvropská uniecs
dc.subjectproduktivita prácecs
dc.subjectpanelová analýza datcs
dc.subject.translatedartificial intelligenceen
dc.subject.translatedcluster analysisen
dc.subject.translatedEuropean Unionen
dc.subject.translatedlabour productivityen
dc.subject.translatedpanel data analysisen
dc.titleDifferences in AI Adoption and Labour Productivity in EU Countriesen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.statusPeer revieweden
dc.type.versionpublishedVersionen
local.files.count2*
local.files.size5762282*
local.has.filesyes*

Files

Original bundle
Showing 1 - 2 out of 2 results
No Thumbnail Available
Name:
978-80-261-1342-3-431-446.pdf
Size:
659.41 KB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
978-80-261-1342-3-uvod.pdf
Size:
4.85 MB
Format:
Adobe Portable Document Format
Download
License bundle
Showing 1 - 1 out of 1 results
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Opportunities and Threats to Current Business Management in Cross-border Comparison 2025