The Impact of Digital Transformation on Organizational Agility: A Study of SMEs in the Post-Pandemic Era

Digital transformation has emerged as a critical driver of organizational agility for SMEs in the post-pandemic era, yet the measurement of agility and its predictors remains underexplored at scale. This study addresses this gap by leveraging a comprehensive, cross-national dataset of 491,636 SME technology adoption records, distinguishing between production and consumption technologies. Using advanced machine learning techniques—including Random Forest, XGBoost, and ensemble models—the research systematically evaluated the predictive power of technology adoption indicators on organizational agility outcomes. The Random Forest model achieved the highest test R2 (0.6249), demonstrating superior ability to capture the complex, non-linear relationships that characterize SME digitalization and agility. Key findings reveal that production technologies, such as automation and digital infrastructure, are stronger predictors of agility than widely adopted consumption technologies, challenging prevailing assumptions about the primacy of customer-facing digital tools. These insights not only advance theoretical understanding by integrating the Technology-Organization-Environment and dynamic capability frameworks, but also offer actionable guidance for SME leaders and policymakers. The results underscore the need for targeted investment in foundational digital capabilities and workforce upskilling to foster resilience and adaptability. Ultimately, this study demonstrates the transformative potential of machine learning in guiding data-driven digitalization strategies, equipping SMEs to navigate uncertainty and drive sustainable recovery in a rapidly evolving business landscape.