Measuring efficiency under fixed proportion technologies |
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Authors: | Darold T Barnum John M Gleason |
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Institution: | (1) Departments of Managerial Studies, Information & Decision Sciences, and Pharmacy Administration, University of Illinois at Chicago, (MC 243), 601 South Morgan Street, Chicago, IL 60607-7123, USA;(2) Department of Information Systems and Technology, College of Business Administration, Creighton University, Omaha, NE 68178, USA |
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Abstract: | Data Envelopment Analysis (DEA) applications frequently involve nonsubstitutable inputs and nonsubstitutable outputs (that
is, fixed proportion technologies). However, DEA theory requires substitutability. In this paper, we illustrate the consequences
of nonsubstitutability on DEA efficiency estimates, and we develop new efficiency indicators that are similar to those of
conventional DEA models except that they require nonsubstitutability. Then, using simulated and real-world datasets that encompass
fixed proportion technologies, we compare DEA efficiency estimates with those of the new indicators. The examples demonstrate
that DEA efficiency estimates are biased when inputs and outputs are nonsubstitutable. The degree of bias varies considerably
among Decision Making Units, resulting in substantial differences in efficiency rankings between DEA and the new measures.
And, over 90% of the units that DEA identifies as efficient are, in truth, not efficient. We conclude that when inputs and
outputs are not substituted for either technological or other reasons, conventional DEA models should be replaced with models
that account for nonsubstitutability. |
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