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Benchmark optimization and attribute identification for improvement of container terminals

Listed author(s):
  • Sharma, Mithun J.
  • Yu, Song Jin
Registered author(s):

    The aim of this paper is to optimize the benchmarks and prioritize the variables of decision-making units (DMUs) in data envelopment analysis (DEA) model. In DEA, there is no scope to differentiate and identify threats for efficient DMUs from the inefficient set. Although benchmarks in DEA allow for identification of targets for improvement, it does not prioritize targets or prescribe level-wise improvement path for inefficient units. This paper presents a decision tree based DEA model to enhance the capability and flexibility of classical DEA. The approach is illustrated through its application to container port industry. The method proceeds by construction of multiple efficient frontiers to identify threats for efficient/inefficient DMUs, provide level-wise reference set for inefficient terminals and diagnose the factors that differentiate the performance of inefficient DMUs. It is followed by identification of significant attributes crucial for improvement in different performance levels. The application of this approach will enable decision makers to identify threats and opportunities facing their business and to improve inefficient units relative to their maximum capacity. In addition, it will help them to make intelligent investment on target factors that can improve their firms' productivity.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00188-X
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    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 201 (2010)
    Issue (Month): 2 (March)
    Pages: 568-580

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    Handle: RePEc:eee:ejores:v:201:y:2010:i:2:p:568-580
    Contact details of provider: Web page: http://www.elsevier.com/locate/eor

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    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Kevin Cullinane & Dong-Wook Song, 2003. "A stochastic frontier model of the productive efficiency of Korean container terminals," Applied Economics, Taylor & Francis Journals, vol. 35(3), pages 251-267.
    3. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    4. Drake, Leigh & Simper, R., 2003. "The measurement of English and Welsh police force efficiency: A comparison of distance function models," European Journal of Operational Research, Elsevier, vol. 147(1), pages 165-186, May.
    5. Ro-Kyung Park & Prabir De, 2004. "An Alternative Approach to Efficiency Measurement of Seaports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 6(1), pages 53-69, March.
    6. Tongzon, Jose, 2001. "Efficiency measurement of selected Australian and other international ports using data envelopment analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(2), pages 107-122, February.
    7. Dyckhoff, H. & Allen, K., 2001. "Measuring ecological efficiency with data envelopment analysis (DEA)," European Journal of Operational Research, Elsevier, vol. 132(2), pages 312-325, July.
    8. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    9. Carlos Pestana Barros & Manolis Athanassiou, 2004. "Efficiency in European Seaports with DEA: Evidence from Greece and Portugal," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 6(2), pages 122-140, June.
    10. Amos Tversky & Itamar Simonson, 1993. "Context-Dependent Preferences," Management Science, INFORMS, vol. 39(10), pages 1179-1189, October.
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