This project involves the extension of Data Envelopment Analysis (DEA) to situations involving stochastic inputs. DEA is a techniques for combining variables which differ in their scale properties in order to produce decision functions. DEA has been applied to a wide range of processes including manufacturing productivity, audit of managerial performance, choice and location of unique facilities, hospital efficiency, branch bank management, financial management, and marketing/sales efficiency. The stochastic extensions of DEA are computationally intensive and computer software will be developed and tested to enable practical application of the procedures.
