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Network DEA: A slacks-based measure approach

Author

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  • Miki Tsutsui

    (Central Research Institute of Electric Power Industry)

  • Kaoru Tone

    (National Graduate Institute for Policy Studies)

Abstract

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them in DEA models, we propose a slacks-based network DEA model that can deal with intermediate products. Using this model we can evaluate divisional efficiencies along with the overall efficiency of decision making units (DMUs).

Suggested Citation

  • Miki Tsutsui & Kaoru Tone, 2007. "Network DEA: A slacks-based measure approach," GRIPS Discussion Papers 07-08, National Graduate Institute for Policy Studies.
    • Handle: RePEc:ngi:dpaper:07-08
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    References listed on IDEAS

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    1. Rolf Färe & Shawna Grosskopf & Gerald Whittaker, 2014. "Network DEA II," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 307-327, Springer.
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    5. Tone, Kaoru & Tsutsui, Miki, 2007. "Decomposition of cost efficiency and its application to Japanese-US electric utility comparisons," Socio-Economic Planning Sciences, Elsevier, vol. 41(2), pages 91-106, June.
    6. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    7. Prieto, Angel M. & Zofio, Jose L., 2007. "Network DEA efficiency in input-output models: With an application to OECD countries," European Journal of Operational Research, Elsevier, vol. 178(1), pages 292-304, April.
    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. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, October.
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    Cited by:

    1. Qingyou Yan & Youwei Wan & Jingye Yuan & Jieting Yin & Tomas Baležentis & Dalia Streimikiene, 2017. "Economic and Technical Efficiency of the Biomass Industry in China: A Network Data Envelopment Analysis Model Involving Externalities," Energies, MDPI, vol. 10(9), pages 1-19, September.

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