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Growth in rail traffic has not been matched by increases in railway infrastructure. Given this capacity challenge and the current restrictions on public spending, the allocation and the utilization of existing railway capacity are more important than ever. Great Britain has had the greatest growth in rail passenger kilometers of European countries since 1996. However, costs are higher and efficiency is lower than European best practice. This paper provides an innovative methodology for assessing the efficiency of passenger operators in capacity utilization. Data envelopment analysis (DEA) is used to analyze the efficiency of operators in transforming inputs of allocated capacity of infrastructure and franchise payments into valuable passenger service outputs while avoiding delays. By addressing operational and economic aspects of capacity utilization simultaneously, the paper deviates from existing DEA work on the economic efficiency of railways by considering a new combination of input–output that also incorporates quality of service. The constant and variable returns to scale models are applied to the case study of franchised passenger operators in Great Britain. The follow-up Tobit regression model shows positive correlation between serving London and the efficiency scores. There is negative correlation between offering regional services (average length of journeys less than 40 mi) and the efficiency scores. The overall study and the results can provide helpful insights for railway authorities into the tactical and strategic planning of railways needed to increase efficiency.

In the European Union, the total length of railway lines has decreased since 1970, mainly by abandoning very old routes such as those to coal mines. However, there has been huge growth in the transport of goods and passengers due to economic growth and globalization. Accommodating more passengers and goods on less infrastructure has resulted in the railway capacity challenge. The highest rate of growth in passenger kilometres in Europe belongs to Britain, where a rise of 42.2 percent has been achieved in the period 1995–2006 while the total length of railway lines has decreased from 19,330 route km in 1970 to 16,321 km in 2008. Railways originated from Great Britain therefore old tracks along with huge growth in railway transportation in recent years and inadequate infrastructure have resulted in a serious railway capacity challenge. This paper reviews different definitions of railway capacity, discusses issues for it (including having one degree of freedom for movement, constant need for maintenance due to wear caused by wheel-rail interaction and domino effect) and examines underlying infrastructure, traffic and operating parameters that affect capacity utilisation. Current methods for analyzing capacity utilisation are investigated: theoretical formulae, parametric and mathematical models and various simulation software. For tackling the capacity challenge, a hierarchy of soft and hard measures that can be deployed to increase capacity is proposed. Some of the latest initiatives in Britain to tackle railway capacity challenge and using the current infrastructure efficiently are analyzed including Network Modeling Framework (NMF), Delivering a Sustainable Railway, High Level Output Statement (HLOS) and Route Utilisation Strategies (RUSs). In the end, five policies that can contribute to better utilising capacity in Britain are suggested.

Stations are bottlenecks for railway transportation as they are where traffics merge and diverge. Numerous activities such as passengers boarding, alighting and interchanging, train formation and technical checks are also done at these points. The number of platforms is limited and it is vital to do all the work efficiently. For the first time in the literature, we implement a methodology based on data envelopment analysis which is benchmarked from ports and airport efficiency studies. It can help policy makers and practitioners to rank stations in terms of efficiency and take more informative decisions. The proposed methodology can analyse the relative 'technical efficiency' of stations to handle train stops with existing station capacity. The second stage model analyses 'service effectiveness' to identify how well train stops at a station are transformed into the number of passenger entries, exits and interchanges, taking into account catchment area population and job opportunities. The models are applied to a case study of the 96 busiest train stations in Great Britain and are followed up by two Tobit regressions to assess the effect of traffic type and location on the results.