A Comparative Data Analysis of the E-Commerce Market in Europe: During and Post-COVID-19 Trends and Insights

Abstract

To provide a comparative data analysis of the evolution of e-commerce in Europe during the COVID-19 pandemic, addressing both short-term adaptations and long-term strategic shifts. This study adopts a novel approach that integrates a systematic literature review guided by PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), bibliometric network analysis (using VOSviewer), and machine learning-based topic modeling (Latent Dirichlet Allocation). Insights were synthesized from forty peer-reviewed articles across seven academic databases, revealing four key themes: (1) digitalization, business transformation, and EU strategy; (2) sustainability, economic growth, and remote work; (3) logistics, supply chains, and regional disparities; and (4) consumer behavior, digitalization, and social trends. The findings show that the pandemic initially sparked immediate changes in consumer behavior and logistics, which later evolved into broader strategic concerns such as digital governance, regional resilience, and sustainability. Of particular significance, the analysis uncovered region-specific vulnerabilities within Europe, such as those observed in Poland and Ukraine. By triangulating automated and visual analytic methods, this research offers a comprehensive framework for literature reviews and delivers actionable insights for businesses and policymakers responding to digital transitions in times of crisis. Leveraging machine learning enhanced both the depth and reliability of the findings, ultimately supporting future research and informed decision-making as trade continues to evolve toward a digital economy in emergency contexts.