1. Benchmarking -- 2. An Introduction to Data Envelopment Analysis -- 3. Probability Theory -- 4. Stochastic Data Envelopment Analysis -- 5. Stochastic Network Data Envelopment Analysis -- 6. Stochastic Scale Elasticity.

In this paper, we address several issues related to the use of data envelopment analysis (DEA). These issues include model orientation, input and output selection/definition, the use of mixed and raw data, and the number of inputs and outputs to use versus the number of decision making units...

The purpose of this study was to perform an interim evaluation of the policy effect of the current reform of Japan’s municipal hospitals. We focused on efficiency improvements both within hospitals and within two separate internal hospital organizations. Hospitals have two heterogeneous...

This papersurveys recently developed analytical methods for studying thesensitivity of DEA results to variations in the data. The focusis on the stability of classification of DMUs (Decision MakingUnits) into efficient and inefficient performers. Early workon this topic concentrated on...

The measure proposed in this paper is a new nonparametric data envelopment analysis (DEA) scheme, the hybrid measure, for determining efficiency in the presence of radial and nonradial inputs or outputs. Further extension of the scheme occurred to address nonseparable desirable and undesirable...