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Including substitution of inputs in DEA models

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  • Bogusla Guzik

    ()
    (Katedra Ekonometrii, Akademia Ekonomiczna, Poland)

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    Abstract

    Classic DEA models (e.g., CCR or super-efficiency DEA) assume that inputs are complementary and there is no substitution of inputs. The lack of substitution is a result of using the same input multiplier for all inputs. The author indicates that there is a possibility of including the substitution of inputs by using individual multiplier for each input. This is a characteristic of so-called non-radial DEA, which was proposed by Dyson and Thanassoulis (1992). The author presents some simple measures of substitution which are based on individual multipliers of inputs: substitution range, substitution index, substitution intensity. The substitution index describes what change of initial structure of inputs is needed to reach the optimal technology. The substitution intensity describes the velocity of necessary decrease of one input induced by an increase or not as fast as expected a decrease of the second input. Another characteristic of substitution is a substitution line the estimation of which is also proposed by the author.

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    Bibliographic Info

    Article provided by Wroclaw University of Technology, Institute of Organization and Management in its journal Operations Research and Decisions.

    Volume (Year): 3-4 (2007)
    Issue (Month): ()
    Pages: 71-92

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    Handle: RePEc:wut:journl:v:3-4:y:2007:p:71-92

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    Keywords: Data Envelopment Analysis (DEA); substitution of inputs; non-radial efficiency;

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    1. 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.
    2. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    3. 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.
    4. 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.
    5. Thanassoulis, E. & Dyson, R. G., 1992. "Estimating preferred target input-output levels using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 80-97, January.
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