Adam Pentek

The accelerating pace of digital and environmental transformation presents both opportunities and challenges for small- and medium-sized enterprises (SMEs) across the European Union. While digital tools like data analytics can significantly boost operational efficiency and sustainability, many SMEs lack the internal capabilities to fully leverage them. This study investigates how upskilling employees in digital competencies can help SMEs enhance their digital maturity and achieve long-term resilience. A descriptive trend analysis was based on Eurostat datasets focusing on enterprise size categories and examining indicators such as data analytics activities, the prevalence of ICT training, and difficulties encountered in recruiting ICT specialists. Visualized through Tableau, the data reveal notable disparities: in 2023, only 14.5% of small and 33.8% of medium-sized enterprises with high digital maturity performed data analytics, compared to 59.4% of large enterprises. Despite clear demand, only 5% of small and 20% of medium enterprises attempted to recruit ICT-skilled personnel, frequently citing a lack of qualified candidates or unaffordable salary expectations. SMEs rely on their own staff for data analytics tasks, yet many still do not offer structured training. While countries like Finland stand out, with 61.7% of medium enterprises providing ICT upskilling, others fall well below the EU average. These results underscore that internal skill development is not just a workaround but a strategic necessity for SMEs striving to keep pace with digital demands, overcome labor market constraints, and build a foundation for sustainable growth.

Type of the article: Research Article

Abstract
The ongoing process of digitalization presents both opportunities and challenges for small and medium-sized enterprises (SMEs), particularly when it comes to integrating corporate mobile applications into daily operations. This study examines the key factors that influence employees’ acceptance of, and their actual use of, employer-provided mobile applications.
Primary data were collected via a structured questionnaire survey conducted between March and July 2024 in Hajdú-Bihar County, Hungary. The target population comprised employees of SMEs and micro-enterprises who had access to such applications. Non-probability purposive sampling was employed to ensure relevance, yielding a total of 161 valid responses. Quantitative data were analyzed using structural equation modelling via the partial least squares method.
The results demonstrate that performance expectancy, facilitating conditions, hedonic motivation, and price value have a statistically significant positive impact on behavioral intention, which in turn is the strongest predictor of actual use. The model explains 69% of the variance in behavioral intention and 87.2% of the variance in actual use, which highlights the robustness of the findings. Conversely, social influence and effort expectancy played no meaningful role in this context, suggesting that adoption is shaped less by peer pressure or perceived ease of use and more by perceived benefits, organizational support, and motivational factors. From a management perspective, the findings emphasize the importance of investing in digital infrastructure, providing organizational support, and improving perceived value and user experience. Such measures are crucial for supporting effective implementation and fostering sustainable digital transformation in SMEs.

Acknowledgment
Supported by the University of Debrecen Program for Scientific Publication.