The impact of reliability on the productivity of railroad companies
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DOI: 10.1016/j.tre.2012.12.004
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Citations
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Cited by:
- Kwon, He-Boong, 2017. "Exploring the predictive potential of artificial neural networks in conjunction with DEA in railroad performance modeling," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 159-170.
- Li, Zheng & Hensher, David A. & Rose, John M., 2010. "Willingness to pay for travel time reliability in passenger transport: A review and some new empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 384-403, May.
- Xu, Ren-Hong & Lai, Yung-Cheng & Huang, Kwei-Long, 2021. "Decision support models for annual catenary maintenance task identification and assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
- Zhao, Jian & Zhao, Yunyi & Li, Ying, 2015. "The variation in the value of travel-time savings and the dilemma of high-speed rail in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 130-140.
- Smith, Andrew S.J. & Ojeda Cabral, Manuel, 2022. "Is higher quality always costly? Marginal costs of quality: Theory and application to railway punctuality," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 258-273.
- Link, Heike, 2019. "The impact of including service quality into efficiency analysis: The case of franchising regional rail passenger serves in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 284-300.
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Keywords
Reliability; Productivity; Production frontier; Railroad; Public transport;All these keywords.
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