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Improving envelopment in Data Envelopment Analysis under variable returns to scale

  • Thanassoulis, Emmanuel
  • Kortelainen, Mika
  • Allen, Rachel

In a Data Envelopment Analysis model, some of the weights used to compute the efficiency of a unit can have zero or negligible value despite of the importance of the corresponding input or output. This paper offers an approach to preventing inputs and outputs from being ignored in the DEA assessment under the multiple input and output VRS environment, building on an approach introduced in Allen and Thanassoulis (2004) for single input multiple output CRS cases. The proposed method is based on the idea of introducing unobserved DMUs created by adjusting input and output levels of certain observed relatively efficient DMUs, in a manner which reflects a combination of technical information and the decision maker’s value judgements. In contrast to many alternative techniques used to constrain weights and/or improve envelopment in DEA, this approach allows one to impose local information on production trade-offs, which are in line with the general VRS technology. The suggested procedure is illustrated using real data.

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

Volume (Year): 218 (2012)
Issue (Month): 1 ()
Pages: 175-185

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Handle: RePEc:eee:ejores:v:218:y:2012:i:1:p:175-185
Contact details of provider: Web page: http://www.elsevier.com/locate/eor

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  1. 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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  5. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
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  7. 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.
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  9. Sowlati, Taraneh & Paradi, Joseph C., 2004. "Establishing the "practical frontier" in data envelopment analysis," Omega, Elsevier, vol. 32(4), pages 261-272, August.
  10. 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.
  11. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
  12. E. Thanassoulis & R. Allen, 1998. "Simulating Weights Restrictions in Data Envelopment Analysis by Means of Unobserved DMUs," Management Science, INFORMS, vol. 44(4), pages 586-594, April.
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  14. Estellita Lins, M.P. & Moreira da Silva, A.C. & Lovell, C.A.K., 2007. "Avoiding infeasibility in DEA models with weight restrictions," European Journal of Operational Research, Elsevier, vol. 181(2), pages 956-966, September.
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