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Multi-output efficiency and operational safety: An analysis of railway traffic control centre performance

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  • Roets, Bart
  • Verschelde, Marijn
  • Christiaens, Johan

Abstract

Transportation service providers are under increasing pressure to raise cost efficiency without sacrificing safety. We show the usefulness of a nonparametric multi-output framework to both monitor staff efficiency and detect operational safety concerns. To realistically model input–output relations at an hourly rate of Belgian computerized railway traffic control centres, we apply a Data Envelopment Analysis (DEA)-based framework with proportional cost allocation restrictions and introduce output-specific metafrontiers. Our analysis (covering each single hour of the complete year 2015) shows that production tasks with a highly variable work load, when characterized by binding cost allocation restrictions and high within-traffic-control-centre efficiency, are more prone to human error. Further, we show how DEA combined with disaggregated data can be used to a priori assess staff schedule changes.

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  • Roets, Bart & Verschelde, Marijn & Christiaens, Johan, 2018. "Multi-output efficiency and operational safety: An analysis of railway traffic control centre performance," European Journal of Operational Research, Elsevier, vol. 271(1), pages 224-237.
    • Handle: RePEc:eee:ejores:v:271:y:2018:i:1:p:224-237
    DOI: 10.1016/j.ejor.2018.04.045
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    Cited by:

    1. Laurens Cherchye & Bram De Rock & Dieter Saelens & Marijn Verschelde & Bart Roets, 2022. "Performance Analysis with Unobserved Inputs: An Application to Endogenous Automation in Railway Traffic Management," Working Papers ECARES 2022-06, ULB -- Universite Libre de Bruxelles.
    2. Sobrie, Léon & Verschelde, Marijn & Hennebel, Veerle & Roets, Bart, 2023. "Capturing complexity over space and time via deep learning: An application to real-time delay prediction in railways," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1201-1217.
    3. Cherchye, Laurens & Rock, Bram De & Saelens, Dieter & Verschelde, Marijn & Roets, Bart, 2024. "Productive efficiency analysis with unobserved inputs: An application to endogenous automation in railway traffic management," European Journal of Operational Research, Elsevier, vol. 313(2), pages 678-690.
    4. Sobrie, Léon & Verschelde, Marijn & Roets, Bart, 2024. "Explainable real-time predictive analytics on employee workload in digital railway control rooms," European Journal of Operational Research, Elsevier, vol. 317(2), pages 437-448.
    5. Joohwan Kim & Hwayoung Kim, 2021. "Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    6. Majid Azadi & Balal Karimi & William Ho & Reza Farzipoor Saen, 2022. "Assessing green performance of power plants by multiple hybrid returns to scale technologies," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1177-1211, December.
    7. Thiago Victorino & Carlos Rosano Peña, 2023. "The Development of Efficiency Analysis in Transportation Systems: A Bibliometric and Systematic Review," Sustainability, MDPI, vol. 15(13), pages 1-32, June.
    8. Topcu, Taylan G. & Triantis, Konstantinos & Roets, Bart, 2019. "Estimation of the workload boundary in socio-technical infrastructure management systems: The case of Belgian railroads," European Journal of Operational Research, Elsevier, vol. 278(1), pages 314-329.
    9. Jorge Antunes & Goodness C. Aye & Rangan Gupta & Peter Wanke & Yong Tan, 2020. "Endogenous Long-Term Productivity Performance in Advanced Countries: A Novel Two-Dimensional Fuzzy-Monte Carlo Approach," Working Papers 2020111, University of Pretoria, Department of Economics.

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