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Benchmark Selection: An Axiomatic Approach

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  • Jens Leth Hougaard

    (Institute of Economics, University of Copenhagen)

  • Mich Tvede

    (Institute of Economics, University of Copenhagen)

Abstract

Within a production theoretic framework, this paper considers an axiomatic approach to benchmark selection. It is shown that two simple and weak axioms: efficiency and comprehensive monotonicity characterize a natural family of benchmarks which typically becomes unique. Further axioms are added in order to obtain a unique selection.

Suggested Citation

  • Jens Leth Hougaard & Mich Tvede, 2001. "Benchmark Selection: An Axiomatic Approach," Discussion Papers 01-06, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:0106
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    References listed on IDEAS

    as
    1. Christensen, Flemming & Hougaard, Jens Leth & Keiding, Hans, 1999. "An axiomatic characterization of efficiency indices," Economics Letters, Elsevier, vol. 63(1), pages 33-37, April.
    2. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
    3. 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.
    4. R. Allen & A. Athanassopoulos & R.G. Dyson & E. Thanassoulis, 1997. "Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions," Annals of Operations Research, Springer, vol. 73(0), pages 13-34, October.
    5. Leibenstein, Harvey & Maital, Shlomo, 1994. "The organizational foundations of X-inefficiency: A game-theoretic interpretation of Argyris' model of organizational learning," Journal of Economic Behavior & Organization, Elsevier, vol. 23(3), pages 251-268, May.
    6. Post, Thierry & Spronk, Jaap, 1999. "Performance benchmarking using interactive data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 115(3), pages 472-487, June.
    7. Jens Hougaard & Hans Keiding, 1998. "On the Functional Form of an Efficiency Index," Journal of Productivity Analysis, Springer, vol. 9(2), pages 103-111, March.
    8. Bergstrom, Theodore C., 1975. "Maximal elements of acyclic relations on compact sets," Journal of Economic Theory, Elsevier, vol. 10(3), pages 403-404, June.
    9. 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.
    10. Walker, Mark, 1977. "On the existence of maximal elements," Journal of Economic Theory, Elsevier, vol. 16(2), pages 470-474, December.
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    More about this item

    Keywords

    Benchmarking; Production Economics; Selection;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D2 - Microeconomics - - Production and Organizations
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics

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