DESI Integration and Enterprise Productivity in the EU: A Business Model Innovation Perspective on Digital Transformation

Digital transformation reshapes firms into more digital, data-driven, and customer-centric organizations. Because it often supports innovation, firms are widely expected to benefit from higher performance and productivity. However, it remains unclear whether higher national levels of digital integration translate into higher aggregate enterprise productivity. This study adopts a socio-technical and ecosystem perspective to examine the relationship between digital technology integration and enterprise labor productivity across the 27 EU member states, while also considering the role of key ecosystem enablers. A balanced country-year panel of data (N = 162) was constructed from Eurostat Structural Business Statistics on the apparent labor productivity of total enterprises, together with Digital Economy and Society Index (DESI) indicators on the integration of digital technology, human capital, connectivity, and Gross Domestic Product (GDP) per capita, covering the period from 2017 to 2022. To this end, fixed-effects regression models were estimated using robust standard errors clustered by country and combined with correlated random effects (CRE/Mundlak) decomposition. This methodological approach was adopted to distinguish short-run within-country dynamics from persistent between-country differences. The study contributes to ecosystem-level DESI research by using this distinction to assess how country-level digital integration is associated with enterprise productivity. The fixed-effects results provide no evidence that year-to-year changes in digital technology integration, on their own, are associated with higher enterprise productivity. Additionally, no statistically significant interaction effect was observed with either human capital or digital connectivity. By contrast, GDP per capita was found to be a robust positive predictor of enterprise productivity. The CRE/Mundlak results indicate that the majority of between-country productivity differences are attributable to differences in economic development. Furthermore, there is evidence of a positive association between the average level of digital technology integration and human capital. Taken together, these findings suggest that national digital technology integration reflects business environment conditions at the ecosystem level. While it may create opportunities for enterprise business model innovation, its productivity implications are more likely to emerge gradually through stronger absorptive capacity and complementary capabilities. Consequently, the study suggests that enterprise digital transformation policies should be aligned with investments in digital skills and broadband infrastructure. These policies should also support process redesign, greater interoperability, and the implementation of AI-enabled technologies.

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Journal
Systems
Published
2026-03-26
DOI
https://doi.org/10.3390/systems14040354
Primary Topic
Digital Transformation in Industry
Type
article
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article

DESI Integration and Enterprise Productivity in the EU: A Business Model Innovation Perspective on Digital Transformation

Ofelia Ema Aleca, Florin Mihai
Systems
Digital Transformation in Industry
article

DESI Integration and Enterprise Productivity in the EU: A Business Model Innovation Perspective on Digital Transformation

Ofelia Ema Aleca, Florin Mihai
article en

Abstract

Digital transformation reshapes firms into more digital, data-driven, and customer-centric organizations. Because it often supports innovation, firms are widely expected to benefit from higher performance and productivity. However, it remains unclear whether higher national levels of digital integration translate into higher aggregate enterprise productivity. This study adopts a socio-technical and ecosystem perspective to examine the relationship between digital technology integration and enterprise labor productivity across the 27 EU member states, while also considering the role of key ecosystem enablers. A balanced country-year panel of data (N = 162) was constructed from Eurostat Structural Business Statistics on the apparent labor productivity of total enterprises, together with Digital Economy and Society Index (DESI) indicators on the integration of digital technology, human capital, connectivity, and Gross Domestic Product (GDP) per capita, covering the period from 2017 to 2022. To this end, fixed-effects regression models were estimated using robust standard errors clustered by country and combined with correlated random effects (CRE/Mundlak) decomposition. This methodological approach was adopted to distinguish short-run within-country dynamics from persistent between-country differences. The study contributes to ecosystem-level DESI research by using this distinction to assess how country-level digital integration is associated with enterprise productivity. The fixed-effects results provide no evidence that year-to-year changes in digital technology integration, on their own, are associated with higher enterprise productivity. Additionally, no statistically significant interaction effect was observed with either human capital or digital connectivity. By contrast, GDP per capita was found to be a robust positive predictor of enterprise productivity. The CRE/Mundlak results indicate that the majority of between-country productivity differences are attributable to differences in economic development. Furthermore, there is evidence of a positive association between the average level of digital technology integration and human capital. Taken together, these findings suggest that national digital technology integration reflects business environment conditions at the ecosystem level. While it may create opportunities for enterprise business model innovation, its productivity implications are more likely to emerge gradually through stronger absorptive capacity and complementary capabilities. Consequently, the study suggests that enterprise digital transformation policies should be aligned with investments in digital skills and broadband infrastructure. These policies should also support process redesign, greater interoperability, and the implementation of AI-enabled technologies.

SystemsVol. 14(4)
Bucharest University of Economic Studies (RO)
Decent work and economic growth
Openalex Percentile: Top 6%
Digital Transformation in Industry
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