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Efficiency measurement using independent component analysis and data envelopment analysis

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  • Kao, Ling-Jing
  • Lu, Chi-Jie
  • Chiu, Chih-Chou
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    Abstract

    Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors' and then develop corresponding plans to improve performance. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, problems of discrimination between efficient and inefficient decision-making units also exist in the DEA context (Adler and Yazhemsky, 2010). In this paper, a two-stage approach of integrating independent component analysis (ICA) and data envelopment analysis (DEA) is proposed to overcome this issue. We suggest using ICA first to extract the input variables for generating independent components, then selecting the ICs representing the independent sources of input variables, and finally, inputting the selected ICs as new variables in the DEA model. A simulated dataset and a hospital dataset provided by the Office of Statistics in Taiwan's Department of Health are used to demonstrate the validity of the proposed two-stage approach. The results show that the proposed method can not only separate performance differences between the DMUs but also improve the discriminatory capability of the DEA's efficiency measurement.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 210 (2011)
    Issue (Month): 2 (April)
    Pages: 310-317

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    Handle: RePEc:eee:ejores:v:210:y:2011:i:2:p:310-317

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    Web page: http://www.elsevier.com/locate/eor

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    Keywords: Independent component analysis Data envelopment analysis Efficiency measurement;

    References

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    1. Sahoo, Biresh K. & Tone, Kaoru, 2009. "Decomposing capacity utilization in data envelopment analysis: An application to banks in India," European Journal of Operational Research, Elsevier, vol. 195(2), pages 575-594, June.
    2. Ray, Subhash C. & Jeon, Yongil, 2008. "Reputation and efficiency: A non-parametric assessment of America's top-rated MBA programs," European Journal of Operational Research, Elsevier, vol. 189(1), pages 245-268, August.
    3. Kao, Chiang & Liu, Shiang-Tai, 2009. "Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks," European Journal of Operational Research, Elsevier, vol. 196(1), pages 312-322, July.
    4. 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.
    5. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    6. Ancarani, A. & Di Mauro, C. & Giammanco, M.D., 2009. "The impact of managerial and organizational aspects on hospital wards' efficiency: Evidence from a case study," European Journal of Operational Research, Elsevier, vol. 194(1), pages 280-293, April.
    7. David Parkin & Bruce Hollingsworth, 1997. "Measuring production efficiency of acute hospitals in Scotland, 1991-94: validity issues in data envelopment analysis," Applied Economics, Taylor & Francis Journals, vol. 29(11), pages 1425-1433.
    8. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    9. Puig-Junoy, Jaume, 2000. "Partitioning input cost efficiency into its allocative and technical components: an empirical DEA application to hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 199-218, September.
    10. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
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    Cited by:
    1. Lin, Tzu-Yu & Chiu, Sheng-Hsiung, 2013. "Using independent component analysis and network DEA to improve bank performance evaluation," Economic Modelling, Elsevier, vol. 32(C), pages 608-616.

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