Some models and measures for evaluating performances with DEA: past accomplishments and future prospects |
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Authors: | W W Cooper L M Seiford K Tone J Zhu |
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Institution: | (1) The Red McCombs School of Business, The University of Texas at Austin, University Station One, Austin, B6500, TX, USA;(2) College of Engineering, Industrial and Operations Engineering, The University of Michigan, 1677 A IOE Building, Ann Arbor, 48109-2117, MI, USA;(3) National Graduate Institute for Policy Studies, 7-22-1 Roppongi, Minato-ku, Tokyo 106-8677, Japan;(4) Department of Management, Worcester Polytechnic Institute, Worcester, 01609, MA, USA |
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Abstract: | This paper covers some of the past accomplishments of DEA (Data Envelopment Analysis) and some of its future prospects. It
starts with the “engineering-science” definitions of efficiency and uses the duality theory of linear programming to show
how, in DEA, they can be related to the Pareto–Koopmans definitions used in “welfare economics” as well as in the economic
theory of production. Some of the models that have now been developed for implementing these concepts are then described and
properties of these models and the associated measures of efficiency are examined for weaknesses and strengths along with
measures of distance that may be used to determine their optimal values. Relations between the models are also demonstrated
en route to delineating paths for future developments. These include extensions to different objectives such as “satisfactory”
versus “full” (or “strong”) efficiency. They also include extensions from “efficiency” to “effectiveness” evaluations of performances
as well as extensions to evaluate social-economic performances of countries and other entities where “inputs” and “outputs”
give way to other categories in which increases and decreases are located in the numerator or denominator of the ratio (=engineering-science)
definition of efficiency in a manner analogous to the way output (in the numerator) and input (in the denominator) are usually
positioned in the fractional programming form of DEA. Beginnings in each of these extensions are noted and the role of applications
in bringing further possibilities to the fore is highlighted.
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Keywords: | Efficiency Effectiveness Social Indicators Engineering-science Welfare economics Distance measures |
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