The study shows that technical efficiency scores in Data Envelopment Analysis are biased by linear aggregation of the quantities of the same type of input that are used by all outputs (intra-input aggregation). Fare et al. 's (2004) models are expanded to account for this additional bias, and...

Building on Data Envelopment Analysis technical efficiency models developed by Fare et al. (2004) and Barnum and Gleason (2005), a procedure is illustrated for estimating a firm's efficiency in allocating inputs among the production technologies producing its outputs.

This article addresses Data Envelopment Analysis (DEA) efficiency analysis in organizations with multiple production processes. It shows how to measure the impact on an organization's overall efficiency of (a) inefficient and superefficient subunits and (b) the efficiency with which input...

In Data Envelopment Analysis (DEA), the two-stage method is a popular procedure for accounting for exogenous influences on efficiency. With the conventional two-stage method, a DEA is first conducted using only traditional (endogenous) inputs and outputs. Then, the first-stage DEA scores are...