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Performance Measurement for Railway Transport: Stochastic Distance Functions with Inefficiency and Ineffectiveness Effects

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  • Lawrence W. Lan
  • Erwin T. J. Lin

Abstract

To scrutinise the plausible sources of poor performance for non-storable transport services, it is necessary to distinguish technical inefficiency from service ineffectiveness. This paper attempts to measure the performance of railways that produce passenger and freight services by two stochastic distance function approaches. A stochastic input distance function with an inefficiency effect is defined to evaluate technical efficiency; whereas a stochastic consumption distance function with an ineffectiveness effect is introduced to assess service effectiveness. The empirical analysis examines 39 worldwide railway systems over eight years (1995-2002) where inputs contain number of passenger cars, number of freight cars, and number of employees, while outputs contain passenger train-kilometres and freight train-kilometres, and consumptions contain passenger-kilometres and ton-kilometres. The findings show that railways' technical inefficiency and service ineffectiveness are negatively influenced by gross national income per capita, percentage of electrified lines, and line density. Overall, the railways in West Europe perform more efficiently and effectively than those in East Europe and Non-European regions. Strategies for ameliorating the operation of less-efficient and/or less-effective railways are proposed. © 2006 LSE and the University of Bath

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  • Lawrence W. Lan & Erwin T. J. Lin, 2006. "Performance Measurement for Railway Transport: Stochastic Distance Functions with Inefficiency and Ineffectiveness Effects," Journal of Transport Economics and Policy, University of Bath, vol. 40(3), pages 383-408, September.
  • Handle: RePEc:tpe:jtecpo:v:40:y:2006:i:3:p:383-408
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    Cited by:

    1. Pierre Pestieau, 2009. "Assessing The Performance Of The Public Sector," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 80(1), pages 133-161, March.
    2. Holvad, Torben, 2020. "Efficiency analyses for the railway sector: An overview of key issues," Research in Transportation Economics, Elsevier, vol. 82(C).
    3. Niu, Yanliang & Li, Xin & Zhang, Jiangxue & Deng, Xiaopeng & Chang, Yuan, 2023. "Efficiency of railway transport: A comparative analysis for 16 countries," Transport Policy, Elsevier, vol. 141(C), pages 42-53.
    4. Hanauerová, Eliška, 2019. "Assessing the technical efficiency of public procurements in the bus transportation sector in the Czech Republic," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 105-111.
    5. Wey, Wann-Ming & Kang, Chao-Chung & Khan, Haider A., 2020. "Evaluating the effects of environmental factors and a transfer fare discount policy on the performance of an urban metro system," Transport Policy, Elsevier, vol. 97(C), pages 172-185.
    6. Yu, Ming-Miin & Lin, Erwin T.J., 2008. "Efficiency and effectiveness in railway performance using a multi-activity network DEA model," Omega, Elsevier, vol. 36(6), pages 1005-1017, December.
    7. Fumitoshi Mizutani & Shuji Uranishi, 2013. "Does vertical separation reduce cost? An empirical analysis of the rail industry in European and East Asian OECD Countries," Journal of Regulatory Economics, Springer, vol. 43(1), pages 31-59, January.
    8. Aziz Kutlar & Ali Kabasakal & Murat Sarikaya, 2013. "Determination of the efficiency of the world railway companies by method of DEA and comparison of their efficiency by Tobit analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3575-3602, October.
    9. Mahdiloo, Mahdi & Toloo, Mehdi & Duong, Thach-Thao & Farzipoor Saen, Reza & Tatham, Peter, 2018. "Integrated data envelopment analysis: Linear vs. nonlinear model," European Journal of Operational Research, Elsevier, vol. 268(1), pages 255-267.
    10. Michał Zajfert, 2023. "A Study of the Efficiency of Regional Railway Services: The Case of Poland," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 4, pages 30-53.
    11. Ali Kabasakal & Aziz Kutlar & Murat Sarikaya, 2015. "Efficiency determinations of the worldwide railway companies via DEA and contributions of the outputs to the efficiency and TFP by panel regression," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 69-88, March.
    12. Tavassoli, Mohammad & Faramarzi, Gholam Reza & Farzipoor Saen, Reza, 2014. "Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 146-153.
    13. Hooper, Louise, 2008. "Paying for performance: Uncertainty, asymmetric information and the payment model," Research in Transportation Economics, Elsevier, vol. 22(1), pages 157-163, January.
    14. Bai, Xuejie & Jin, Zeng & Chiu, Yung-Ho, 2021. "Performance evaluation of China's railway passenger transportation sector," Research in Transportation Economics, Elsevier, vol. 90(C).
    15. Guilherme F. Frederico & Vagner Cavenaghi, 2017. "Measuring Performance in Rail Freight Transportation Companies," International Business Research, Canadian Center of Science and Education, vol. 10(11), pages 117-128, November.

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