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Efficiency analysis to incorporate interval-scale data

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

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.

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

Volume (Year): 207 (2010)
Issue (Month): 2 (December)
Pages: 1116-1121

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Handle: RePEc:eee:ejores:v:207:y:2010:i:2:p:1116-1121
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  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. Murat Köksalan & Ceren Tuncer, 2009. "A Dea-Based Approach To Ranking Multi-Criteria Alternatives," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 29-54.
  10. 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.
  11. 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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