Digital Literacy and Enterprise Innovation: Regional-Level Evidence from Kazakhstan
Artykuł w czasopiśmie
MNiSW
0
brak dyscyplin
| Status: | |
| Autorzy: | Sadenova Assel, Denissova Oxana, Suieubayeva Saltanat, Kulisz Monika, Rakhmetullina Zhenisgul, Kuur Olga |
| Dyscypliny: | |
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| Rok wydania: | 2026 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Numer czasopisma: | 2 |
| Wolumen/Tom: | 34 |
| Strony: | 191 - 197 |
| Web of Science® Times Cited: | 0 |
| Bazy: | Web of Science |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Witryna wydawcy |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 30 kwietnia 2026 |
| Abstrakty: | angielski |
| The aim of this study is to identify the relationship between the level of digital literacy among the population and the innovation activity of enterprises across different regions of Kazakhstan. The research is motivated by the growing significance of digital competencies in enhancing innovation capacity, particularly in the context of regional disparities in technological readiness. A mixed-method approach was applied, including correlation analysis and structural equation modeling (SEM), using regional statistical data for the period 2021-2023. Key variables included R&D expenditures, digital infrastructure accessibility, and indicators of enterprise innovation activity. Data normalization (Z-score) and region grouping were used to ensure the comparability of results across newly established administrative boundaries. The results reveal a nuanced relationship that differs markedly across regions. In major urban centers such as Almaty and Astana, a clear and strong link is observed between digital literacy and innovation activity. In contrast, in many other regions, this relationship appears weak or even negative. Among the most impactful variables are household Internet access, external R&D funding, and the presence of innovation-oriented enterprises. Structural equation modeling highlights the indirect influence of digital infrastructure and innovation density on this relationship. Model fit statistics (CFI = 0.921; p = 0.207) support the adequacy of the analytical framework. These findings point to the importance of developing tailored strategies at the regional level – ones that address specific digital skill gaps and innovation barriers. The study offers practical implications for policymakers and enterprise leaders seeking to strengthen regional innovation ecosystems through targeted digital development. |
