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Measuring the performance of multimode bus transit: A mixed structure network DEA model

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  • Yu, Ming-Miin
  • Fan, Chih-Ku

Abstract

The aim of this paper is to propose a mixed structure network data envelopment analysis (MSNDEA) model which allows a representation of a parallel production serial connection of consumption processes in a unified framework and hence can be used to simultaneously estimate the production efficiency, service effectiveness and operational effectiveness of multimode transit firms. To do this, Taiwan's bus transit system is selected for the empirical applications. The main advantages of the MSNDEA model are in contexts where internal linkage and shared inputs between activities can be considered in this model, and the model structure is more realistic than the conventional one.

Suggested Citation

  • Yu, Ming-Miin & Fan, Chih-Ku, 2009. "Measuring the performance of multimode bus transit: A mixed structure network DEA model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(3), pages 501-515, May.
  • Handle: RePEc:eee:transe:v:45:y:2009:i:3:p:501-515
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    Citations

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    Cited by:

    1. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    2. Cinzia Daraio & Marco Diana & Flavia Di Costa & Claudio Leporelli & Giorgio Matteucci & Alberto Nastasi, 2014. "Efficiency and effectiveness in the urban public transport sector: a critical review with directions for future research," DIAG Technical Reports 2014-14, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    3. Barnum, Darold T. & Karlaftis, Matthew G. & Tandon, Sonali, 2011. "Improving the efficiency of metropolitan area transit by joint analysis of its multiple providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1160-1176.
    4. Hassan, Mohammad Nurul & Hawas, Yaser E. & Ahmed, Kamran, 2013. "A multi-dimensional framework for evaluating the transit service performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 47-61.
    5. AGRELL, Per & HATAMI-MARBINI, Adel, 2011. "Frontier-based performance analysis models for supply chain management; state of the art and research directions," CORE Discussion Papers 2011069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. repec:eee:jomega:v:73:y:2017:i:c:p:93-103 is not listed on IDEAS
    7. Chen, Chih Cheng, 2017. "Measuring departmental and overall regional performance: applying the multi-activity DEA model to Taiwan׳s cities/counties," Omega, Elsevier, vol. 67(C), pages 60-80.
    8. Wu, Wei-Ming & Lin, Jenn-Rong, 2015. "Productivity growth, scale economies, ship size economies and technical progress for the container shipping industry in Taiwan," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 1-16.
    9. Pal, Debdatta & Mitra, Subrata K., 2016. "An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 1-12.
    10. Yu, Ming-Miin & Chen, Li-Hsueh & Hsiao, Bo, 2016. "Dynamic performance assessment of bus transit with the multi-activity network structure," Omega, Elsevier, vol. 60(C), pages 15-25.
    11. Zhang, Chunqin & Juan, Zhicai & Xiao, Guangnian, 2015. "Do contractual practices affect technical efficiency? Evidence from public transport operators in China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 39-55.

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