Value for rail capacity. Assessing efficiency of operators in Great Britain.
Value for rail capacity. Assessing efficiency of operators in Great Britain.
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.
134-144
Khadem Sameni, M.
4f181299-5839-48c0-9f91-2f734c03b3ea
Preston, John M.
ef81c42e-c896-4768-92d1-052662037f0b
15 November 2012
Khadem Sameni, M.
4f181299-5839-48c0-9f91-2f734c03b3ea
Preston, John M.
ef81c42e-c896-4768-92d1-052662037f0b
Khadem Sameni, M. and Preston, John M.
(2012)
Value for rail capacity. Assessing efficiency of operators in Great Britain.
Transportation Research Record: Journal of the Transportation Research Board, 2289, .
(doi:10.3141/2289-18).
Abstract
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.
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Published date: 15 November 2012
Organisations:
Transportation Group
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Local EPrints ID: 350334
URI: http://eprints.soton.ac.uk/id/eprint/350334
ISSN: 0361-1981
PURE UUID: b8f42537-f76c-441a-8915-e687a3e54208
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Date deposited: 25 Mar 2013 13:45
Last modified: 15 Mar 2024 03:24
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M. Khadem Sameni
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