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Measuring efficiency with a linear economic model

  • Norman Keith Womer
  • Homee Shroff
  • Thomas Gulledge
  • Kingsley Haynes

This paper modifies and interprets Data Envelopment Analysis (DEA) using a linear economic model. This approach is similar to the cone input/output and assurance region approaches to DEA, but it is implemented so that the multipliers are measured in the same units across all linear optimization problems. This approach allows one to interpret alternatives as profit maximizing organizations and the DEA multipliers as prices that are comparable across the alternatives. This is a useful extension of the assurance region concept, but more important, is that our approach enhances communication with decision-makers. The improved communication is illustrated by applying the model to the siting of a long-term health care facility. This application is interesting because the multiplier bounds make practical sense, and because the problem has dimensions that sometimes lead to interpretation problems with the traditional DEA model. For example, the site characteristics do not result from coordinated decisions, some sites exhibit zero values for some variables, and the problem has many variables compared with the number of potential sites. Problems with these dimensions have, at times, been deemed unsuitable for DEA, but they are handled without problem by the linear economic model.

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Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 35 (2003)
Issue (Month): 13 ()
Pages: 1459-1467

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Handle: RePEc:taf:applec:v:35:y:2003:i:13:p:1459-1467
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  1. Kao, Chiang & Chi Yang, Yong, 1992. "Reorganization of forest districts via efficiency measurement," European Journal of Operational Research, Elsevier, vol. 58(3), pages 356-362, May.
  2. 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.
  3. Schaffnit, Claire & Rosen, Dan & Paradi, Joseph C., 1997. "Best practice analysis of bank branches: An application of DEA in a large Canadian bank," European Journal of Operational Research, Elsevier, vol. 98(2), pages 269-289, April.
  4. 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.
  5. 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.
  6. 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.
  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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