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Hierarchies and Groups in DEA

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  • Wade Cook
  • Dan Chai
  • John Doyle
  • Rodney Green

Abstract

Conventional applications of data envelopment analysis (DEA) presume the existence of a set of similar decision making units, wherein each unit is evaluated relative to other members of the set. Often, however, the DMUs fall naturally into groupings, giving rise first to the problem of how to view the groups themselves as DMUs, and second to the issue of how to deal with several different ratings for any given DMU when groupings can be formed in different ways. In the present paper we introduce the concept of hierarchical DEA, where efficiency can be viewed at various levels. We provide a means for adjusting the ratings of DMUs at one level to account for the ratings received by the groups (into which these DMUs fall) at a higher level. We also develop models for aggregating different ratings for a DMU arising from different possible groupings. An application of these models to a set of power plants is given. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Wade Cook & Dan Chai & John Doyle & Rodney Green, 1998. "Hierarchies and Groups in DEA," Journal of Productivity Analysis, Springer, vol. 10(2), pages 177-198, October.
    • Handle: RePEc:kap:jproda:v:10:y:1998:i:2:p:177-198
    DOI: 10.1023/A:1018625424184
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    References listed on IDEAS

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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. Agha Iqbal Ali & Wade D. Cook & Lawrence M. Seiford, 1991. "Strict vs. Weak Ordinal Relations for Multipliers in Data Envelopment Analysis," Management Science, INFORMS, vol. 37(6), pages 733-738, June.
    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. Boaz Golany, 1988. "Note---A Note on Including Ordinal Relations Among Multipliers in Data Envelopment Analysis," Management Science, INFORMS, vol. 34(8), pages 1029-1033, August.
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