This study evaluates the operational and performance outcomes of railway freight market liberalization across 28 European countries from 2013 to 2024, moving beyond simple operator counts to analyze key traffic, economic, and infrastructure metrics. To control for structural variation, we classified countries into small, medium, and large networks using K-means clustering based on railway route length. A Mixed-Design Repeated-Measures ANOVA was conducted to analyze temporal trends, network-scale impacts, and their interactions. The results reveal that while the total number of active operators rose steadily after 2018, other performance indicators showed an inverse relationship from 2020 onward. The network cluster had a highly significant main effect across all performance indicators, with the largest effect sizes for infrastructure access charges (partial η2 = 0.638), freight train-kilometres (partial η2 = 0.610), and net tonne-kilometres (partial η2 = 0.585). The interaction between year and network cluster was also statistically significant, most notably for net tonne-kilometres (partial η2 = 0.583). Underperformance was prominent in small networks, where market entry did not prevent long-term declines in traffic volume, whereas large networks achieved growth of over 25% in net tonne-kilometres. These quantitative findings show that counting active operators alone is an inadequate measure of liberalization success, as market performance and overall activity levels are strongly associated with network scale and capacity rather than market fragmentation.
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Solina et al. (2026) studied this question.
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