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A multi-stage methodology for the solution of orientated DEA models. (English) Zbl 0963.91032

Summary: The majority of DEA studies use a two-stage Linear Programming (LP) process to solve orientated DEA models. There are two significant problems associated with the second stage of this process. The first is that the sum of slacks is maximized rather than minimized and hence will identify not the nearest efficient point but the furthest efficient point. The second problem is that it is not invariant to units of measurement. In this paper we propose a multi-stage DEA methodology which involves a sequence of radial LPs. We observe that this new approach identify more representative efficient points and that it is also invariant to units of measurement. The methodology is illustrated using a simple example.

MSC:

91B06 Decision theory
90B50 Management decision making, including multiple objectives
90C05 Linear programming

Software:

DEAP
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References:

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