Rank Order Data In Dea

Wade D. Cook and Joe Zhu ()
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Wade D. Cook: York University
Joe Zhu: Worcester Polytechnic Institute

Chapter Chapter 2 in Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, 2007, pp 13-34 from Springer

Abstract: Abstract In data envelopment analysis (DEA), performance evaluation is generally assumed to be based upon a set of quantitative data. In many real world settings, however, it is essential to take into account the presence of qualitative factors when evaluating the performance of decision making units (DMUs). Very often rankings are provided from best to worst relative to particular attributes. Such rank positions might better be presented in an ordinal, rather than numerical sense. The chapter develops a general framework for modeling and treating qualitative data in DEA, and provides a unified structure for embedding rank order data into the DEA framework. We show that the approach developed earlier in Cook et al (1993, 1996) is equivalent to the IDEA methodology given in Chapter 3. It is shown that, like IDEA, the approach given her for dealing with qualitative data lends itself to treatment by conventional DEA methodology.

Keywords: Data envelopment analysis (DEA); efficiency; qualitative; rank order data (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-0-387-71607-7_2

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