ON CHARACTERIZING THE PRODUCTION POSSIBILITY SET FOR THE CCR RATIO MODEL IN DEA

This work makes two contributions. The first is to establish the relat ion between the production possibility set in the CCR ratio model and a polyhedral cone. The relation is based on a one-to-one correspondenc e between elements from a well-defined subset of the generators which are extreme rays of the cone and the extreme-efficient DMUs of the pro duction possibility set. The second contribution is to demonstrate tha t the reduced set of extreme-efficient DMUs is sufficient to perform D EA analysis on a complete data set. Therefore, the polyhedral cone pro posed here may be used to obtain the extreme-efficient DMUs a priori i n a CCR ratio problem and using this set all other DMUs can be subsequ ently scored. This two-stage approach to DEA offers several potential advantages. One is that a body of work on finding extreme rays of fini tely generated cones becomes directly relevant to DEA analysis. Other advantages include working with smaller linear programs, not having to check for 'weak' efficiency from among the extreme-efficient DMUs, an d occurrence of induced degeneracy.