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Performance evaluation based on multiple attributes with nonparametric frontiers

Author

Listed:
  • Caporaletti, L. E.
  • Dulá, J. H.
  • Womer, N. K.

Abstract

Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framework based on nonparametric frontiers to rate and classify entities described by multiple performance attributes into 'performers' and 'underperformers'. The method is equivalent to Data Envelopment Analysis (DEA) with entities defined only by outputs. In the spirit of DEA, the weights for each attribute are selected to maximize each entity's performance score. This approach, however, results in a new linear program that is more direct and intuitive than traditional DEA formulations. The model can be easily understood and interpreted by practitioners since it conforms better to the practice of evaluating and comparing performance using standard specifications. We illustrate the model's use with two examples. The first evaluates the performance of employees. The second is an application in manufacturing where multiple quality attributes are used to assess and compare performance of different manufacturing processes.

Suggested Citation

  • Caporaletti, L. E. & Dulá, J. H. & Womer, N. K., 1999. "Performance evaluation based on multiple attributes with nonparametric frontiers," Omega, Elsevier, vol. 27(6), pages 637-645, December.
  • Handle: RePEc:eee:jomega:v:27:y:1999:i:6:p:637-645
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    References listed on IDEAS

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    1. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
    2. 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.
    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.
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    Cited by:

    1. repec:pal:jorsoc:v:68:y:2017:i:7:d:10.1057_jors.2015.81 is not listed on IDEAS
    2. Färe, Rolf & Karagiannis, Giannis, 2014. "Benefit-of-the-doubt aggregation and the diet problem," Omega, Elsevier, vol. 47(C), pages 33-35.
    3. repec:pal:jorsoc:v:56:y:2005:i:3:d:10.1057_palgrave.jors.2601816 is not listed on IDEAS
    4. Greta Falavigna, 2006. "Models for Default Risk Analysis: Focus on Artificial Neural Networks, Model Comparisons, Hybrid Frameworks," CERIS Working Paper 200610, Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY -NOW- Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY.
    5. repec:pal:jorsoc:v:54:y:2003:i:5:d:10.1057_palgrave.jors.2601531 is not listed on IDEAS
    6. repec:eee:soceps:v:61:y:2018:i:c:p:44-51 is not listed on IDEAS
    7. repec:pal:jorsoc:v:68:y:2017:i:4:d:10.1057_s41274-016-0168-1 is not listed on IDEAS
    8. repec:eee:jomega:v:71:y:2017:i:c:p:93-105 is not listed on IDEAS
    9. Garcia-Cestona, Miguel & Surroca, Jordi, 2008. "Multiple goals and ownership structure: Effects on the performance of Spanish savings banks," European Journal of Operational Research, Elsevier, vol. 187(2), pages 582-599, June.
    10. Bougnol, M.-L. & Dulá, J.H. & Estellita Lins, M.P. & Moreira da Silva, A.C., 2010. "Enhancing standard performance practices with DEA," Omega, Elsevier, vol. 38(1-2), pages 33-45, February.
    11. repec:spr:grdene:v:22:y:2013:i:3:d:10.1007_s10726-011-9279-x is not listed on IDEAS

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