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Measuring efficiency with a linear economic model

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Author Info
Norman Keith Womer
Homeé F. E. Shroff
Thomas R. Gulledge
Kingsley E. Haynes
Abstract

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 and Francis Journals in its journal Applied Economics.

Volume (Year): 35 (2003)
Issue (Month): 13 (September)
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. 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. [Downloadable!] (restricted)
  2. 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. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
  4. 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. [Downloadable!] (restricted)
  5. 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. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
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  1. Mika Kortelainen & Timo Kuosmanen, 2007. "Eco-efficiency analysis of consumer durables using absolute shadow prices," Journal of Productivity Analysis, Springer, vol. 28(1), pages 57-69, October. [Downloadable!] (restricted)
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  2. Timo Kuosmanen & Mika Kortelainen & Timo Sipiläinen & Laurens Cherchye, 2005. "Firm and Industry Level Profit Efficiency Analysis Under Incomplete Price Data: A Nonparametric Approach based on Absolute and Uniform Shadow Prices," Microeconomics 0509011, EconWPA. [Downloadable!]
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