## 5 Discussion
### Policy Implications  
To sum up, the current results suggest that cloud adoption is shaped by a combination of structural readiness, national context, and temporal evolution. Policymakers aiming to boost digital uptake should therefore consider not only investments in infrastructure and skills but also country-specific conditions and trends that may influence adoption trajectories. Importantly, our Random Forest model with country dummies reveals substantial cross-national heterogeneity in predictive influence. Country indicators such as geo_LU (Luxembourg) and geo_FI (Finland) had among the highest importance scores, reflecting advanced infrastructure and digital maturity. Conversely, dummies for geo_BG (Bulgaria) and geo_RO (Romania) also emerged as significant, but in the context of lower adoption baselines--suggesting structural challenges that still materially shape outcomes. These results highlight the need for differentiated, nation-specific policy strategies. For instance, countries in Southern and Eastern Europe with lower digital workforce capacity and broadband saturation may require greater investment in ICT skill-building and last-mile infrastructure. In contrast, high-performing nations like Finland and Luxembourg may benefit more from innovation incentives and policy harmonization. Several broader empirical patterns further contextualize these findings. For instance, the digital divide in Europe is multidimensional and persistent. Internet access or adoption is considered the first-level digital divide in Europe [76]. The Digital Agenda for Europe aimed to enhance internet access and adoption among all European people, particularly through initiatives that promote digital literacy and accessibility [77]. While the Digital Agenda for Europe and the EU Digital Decade Policy Programme have emphasized universal access, disparities remain pronounced in rural and underserved regions, especially in Eastern and Southern Europe. Furthermore, online engagement and the range of activities performed are identified as the second-level digital divide. Education and income are the most consistent predictors of internet engagement: better educated people have stronger internet awareness and are more capable of evaluating online material, whereas less educated people have weak internet abilities [78]. The digital gap in Europe is tangible and multifaceted, as indicated by empirical data [79]. Current studies indicate that digital inequality leads to disparities in digital human capital [80]. In this context, our models identify ICT specialist density and higher education as consistent, high-impact predictors of cloud adoption. This underscores the continued importance of investing in human capital and digital skills, particularly in Southern and Eastern European countries that score lower on these metrics. Notably, although Romania and Bulgaria exhibit strong technical indicators in some domains, these have not yet translated into equivalent levels of adoption, suggesting a need for broader socio-institutional reforms [81]. Likewise, Portugal's high school dropout rate [76] may help explain its relatively lagging performance, despite otherwise improving digital infrastructure. In contrast, advanced digital economies such as Finland and Luxembourg should now focus on consolidating leadership positions through policy harmonization, institutional streamlining, and strategic innovation incentives. Additionally, while this study focuses on socio-technological determinants of adoption, our findings conceptually align with research on system-level efficiency, such as [PERSON] et al. [82], whose VMR algorithm addresses quality-of-service and energy-aware orchestration in cloud environments. Both perspectives emphasize the need for intelligent infrastructure planning, whether through backend orchestration or national readiness initiatives.