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Measuring the Cost Efficiency of Urban Rail Systems An International Comparison Using DEA and Tobit Models

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  • Chi-Hong (Patrick) Tsai
  • Corinne Mulley
  • Rico Merkert

Abstract

Understanding factors driving the operational efficiency of urban rail systems and providing an evaluation of relative efficiency internationally is the purpose of this paper. Two-stage DEA models explore determinants of technical, allocative, and cost efficiency in twenty international urban rail systems (2009-11). This identifies systems with superior overall efficiency (for example, Hong Kong), with others performing better in technical efficiency than allocative and cost efficiency (for example, Sydney). Diseconomies of scale are identified for some systems (for example, Sydney). The number of stations significantly influences technical efficiency, with the key determinant of allocative and cost efficiency being population density. © 2015 LSE and the University of Bath

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  • Chi-Hong (Patrick) Tsai & Corinne Mulley & Rico Merkert, 2015. "Measuring the Cost Efficiency of Urban Rail Systems An International Comparison Using DEA and Tobit Models," Journal of Transport Economics and Policy, University of Bath, vol. 49(1), pages 17-34, January.
    • Handle: RePEc:tpe:jtecpo:v:49:y:2015:i:1:p:17-34
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    1. Rafael Marques & Rafael Teixeira & Daniel P. Lacerda & Fabio S. Piran, 2023. "Exploring outsourcing service productivity from the buyer and supplier perspective: A case analysis in the fleet maintenance industry," Operations Management Research, Springer, vol. 16(2), pages 853-867, June.
    2. Álvaro Costa & Carlos Oliveira Cruz & Joaquim Miranda Sarmento & Vitor Faria Sousa, 2021. "Empirical Analysis of the Effects of Ownership Model (Public vs. Private) on the Efficiency of Urban Rail Firms," Sustainability, MDPI, vol. 13(23), pages 1-14, December.
    3. Ha, Hun Koo & Kaneko, Shinji & Yamamoto, Masashi & Yoshida, Yuichiro & Zhang, Anming, 2017. "On the discrepancy in the social efficiency measures between parametric and non-parametric production technology identification," Journal of Air Transport Management, Elsevier, vol. 58(C), pages 9-14.
    4. Xu Zhang & Huaping Sun & Taohong Wang, 2022. "Impact of Financial Inclusion on the Efficiency of Carbon Emissions: Evidence from 30 Provinces in China," Energies, MDPI, vol. 15(19), pages 1-15, October.
    5. Zong, Yueqi & Wu, Jianhong & Yu, Kemei & Yang, Xutao, 2023. "Efficiency benchmarking and its determinants in high-speed railways: Reference for China," Research in Transportation Economics, Elsevier, vol. 102(C).
    6. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    7. Merkert, Rico & Mulley, Corinne & Hakim, Md Mahbubul, 2017. "Determinants of bus rapid transit (BRT) system revenue and effectiveness – A global benchmarking exercise," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 75-88.
    8. Hao Zhang & Xinyue Wang & Letao Chen & Yujia Luo & Sujie Peng, 2022. "Evaluation of the Operational Efficiency and Energy Efficiency of Rail Transit in China’s Megacities Using a DEA Model," Energies, MDPI, vol. 15(20), pages 1-16, October.
    9. 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.
    10. Chen, Chialin & Achtari, Guyves & Majkut, Kevin & Sheu, Jiuh-Biing, 2017. "Balancing equity and cost in rural transportation management with multi-objective utility analysis and data envelopment analysis: A case of Quinte West," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 148-165.
    11. Bhatia, Vinod & Sharma, Seema, 2021. "Expense based performance analysis and resource rationalization: Case of Indian Railways," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).

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