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Measuring the efficiency and return to scale status of multi-mode bus transit - evidence from Taiwan's bus system

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  • Ming-Miin Yu

Abstract

In this article not only the multi-activity DEA model is applied to determine the efficiency of individual services within different but highly homogeneous multi-mode transit firms, but the relationship between size and local returns to scale status of each transit service is also investigated. The empirical findings indicate that it does not necessarily imply that the transit firm will be as efficient as a single-activity model when the multi-activity model is estimated, and there are different optimal scale sizes for highway bus and urban bus service in the Taipei metropolitan area.

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  • Ming-Miin Yu, 2008. "Measuring the efficiency and return to scale status of multi-mode bus transit - evidence from Taiwan's bus system," Applied Economics Letters, Taylor & Francis Journals, vol. 15(8), pages 647-653.
    • Handle: RePEc:taf:apeclt:v:15:y:2008:i:8:p:647-653
    DOI: 10.1080/13504850600721858
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    Cited by:

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    2. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    3. 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".
    4. Xiyang Lei & Yongjun Li & Alec Morton, 2022. "Dominance and ranking interval in DEA parallel production systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 649-675, June.
    5. 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.
    6. Xiyang Lei & Yongjun Li & Qiwei Xie & Liang Liang, 2015. "Measuring Olympics achievements based on a parallel DEA approach," Annals of Operations Research, Springer, vol. 226(1), pages 379-396, March.
    7. Y. c{C}inar, 2016. "Research and Teaching Efficiencies of Turkish Universities with Heterogeneity Considerations: Application of Multi-Activity DEA and DEA by Sequential Exclusion of Alternatives Methods," Papers 1701.07318, arXiv.org.
    8. 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.
    9. Daraio, Cinzia & Diana, Marco & Di Costa, Flavia & Leporelli, Claudio & Matteucci, Giorgio & Nastasi, Alberto, 2016. "Efficiency and effectiveness in the urban public transport sector: A critical review with directions for future research," European Journal of Operational Research, Elsevier, vol. 248(1), pages 1-20.
    10. Saeedi, Hamid & Behdani, Behzad & Wiegmans, Bart & Zuidwijk, Rob, 2019. "Assessing the technical efficiency of intermodal freight transport chains using a modified network DEA approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 66-86.
    11. Anand Venkatesh & Shivam Kushwaha, 2017. "Measuring technical efficiency of passenger bus companies in India: a non-radial data envelopment analysis approach," OPSEARCH, Springer;Operational Research Society of India, vol. 54(4), pages 706-723, December.

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