A multi-stage methodology for the solution of orientated data envelopment analysis models

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 will identify more representative efficient points and that it is also invariant to units of measurement. The methodology is illustrated using a simple example.