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Generalizing cross redundancy in data envelopment analysis

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  • López, Francisco J.

Abstract

Lee and Choi (2010) proved that a cross redundant output in a CCR or BCC DEA study is unnecessary and can be eliminated from the model without affecting the results of the study. A cross redundant output, as characterized by Lee and Choi, can be expressed as a specially constrained linear combination of both some outputs and some inputs. This article extends the contributions of Lee and Choi (2010) in at least three ways: (i) by adding precision and clarity to some of their definitions; (ii) by introducing specific definitions that complement the ones in their paper; and (iii) by conducting some additional analysis on the impact of the presence of other types of linear dependencies among the inputs and outputs of a DEA model. One reason that it is important to identify and remove cross redundant inputs or outputs from DEA models is that the computational burden of the DEA study is decreased, especially in large applications.

Suggested Citation

  • López, Francisco J., 2011. "Generalizing cross redundancy in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 214(3), pages 716-721, November.
  • Handle: RePEc:eee:ejores:v:214:y:2011:i:3:p:716-721
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    1. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    2. N/A, 1996. "Note:," Foreign Trade Review, , vol. 31(1-2), pages 1-1, January.
    3. J. H. Dulá & R. V. Helgason & N. Venugopal, 1998. "An Algorithm for Identifying the Frame of a Pointed Finite Conical Hull," INFORMS Journal on Computing, INFORMS, vol. 10(3), pages 323-330, August.
    4. Kyuseok Lee & Kyuwan Choi, 2010. "Cross redundancy and sensitivity in DEA models," Journal of Productivity Analysis, Springer, vol. 34(2), pages 151-165, October.
    5. Banker, R. D. & Bardhan, I. & Cooper, W. W., 1996. "A note on returns to scale in DEA," European Journal of Operational Research, Elsevier, vol. 88(3), pages 583-585, February.
    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. Ali, Agha Iqbal, 1993. "Streamlined computation for data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 64(1), pages 61-67, January.
    8. Cooper, W. W. & Gu, Bisheng & Li, Shanling, 2001. "Comparisons and evaluations of alternative approaches to the treatment of congestion in DEA," European Journal of Operational Research, Elsevier, vol. 132(1), pages 62-74, July.
    9. Richard Barr & Matthew Durchholz, 1997. "Parallel and hierarchical decomposition approaches for solving large-scale Data Envelopment Analysis models," Annals of Operations Research, Springer, vol. 73(0), pages 339-372, October.
    10. Dula, J. H. & Helgason, R. V., 1996. "A new procedure for identifying the frame of the convex hull of a finite collection of points in multidimensional space," European Journal of Operational Research, Elsevier, vol. 92(2), pages 352-367, July.
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