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Efficiency analysis to incorporate interval-scale data

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  • Dehnokhalaji, Akram
  • Korhonen, Pekka J.
  • Köksalan, Murat
  • Nasrabadi, Nasim
  • Wallenius, Jyrki

Abstract

We develop an approach to efficiency analysis to enable us to incorporate interval-scale data in addition to ratio-scale data. Our approach introduces a measure of inefficiency and identifies efficient units as is done in Data Envelopment Analysis. The basic idea in our approach is to find the "best" hyperplane separating the units that are better and worse than each unit. "Best" is defined in such a way that the number of not-better units is maximal. The efficiency measure is defined as a proportion of not-better units to all units. The results are invariant under a strictly increasing linear re-scaling of any input- or output-variables. Thus zeroes or negative values do not cause problems for the analysis. The approach is used to analyze the data of the research evaluation exercise recently carried out at the University of Joensuu, Finland.

Suggested Citation

  • Dehnokhalaji, Akram & Korhonen, Pekka J. & Köksalan, Murat & Nasrabadi, Nasim & Wallenius, Jyrki, 2010. "Efficiency analysis to incorporate interval-scale data," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1116-1121, December.
  • Handle: RePEc:eee:ejores:v:207:y:2010:i:2:p:1116-1121
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    References listed on IDEAS

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    1. Köksalan, Murat & Büyükbasaran, Tayyar & Özpeynirci, Özgür & Wallenius, Jyrki, 2010. "A flexible approach to ranking with an application to MBA Programs," European Journal of Operational Research, Elsevier, vol. 201(2), pages 470-476, March.
    2. Pekka Korhonen & Sari Stenfors & Mikko Syrjänen, 2003. "Multiple Objective Approach as an Alternative to Radial Projection in DEA," Journal of Productivity Analysis, Springer, vol. 20(3), pages 305-321, November.
    3. Tarja Joro & Pekka Korhonen & Jyrki Wallenius, 1998. "Structural Comparison of Data Envelopment Analysis and Multiple Objective Linear Programming," Management Science, INFORMS, vol. 44(7), pages 962-970, July.
    4. Laurens Cherchye & Timo Kuosmanen & Thierry Post, 2000. "New Tools for Dealing with Errors-in-Variables in DEA," Public Economics Working Paper Series ces0006, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
    5. Halme, Merja & Joro, Tarja & Koivu, Matti, 2002. "Dealing with interval scale data in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 137(1), pages 22-27, February.
    6. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    7. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    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. 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.
    10. 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.
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    Cited by:

    1. Kristof de Witte & Laura López-Torres, 2015. "Efficiency in Education. A Review of Literature and a Way Forward," Working Papers 1501, Departament Empresa, Universitat Autònoma de Barcelona, revised Apr 2015.
    2. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.

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