Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis

by Joe Zhu (Editor), Wade D. Cook (Editor)

In a relatively short period of time, data envelopment analysis (DEA) has grown into a powerful analytical tool for measuring and evaluating performance. DEA is computational at its core and this book is one of several Springer aim to publish on the subject. This work deals with the micro aspects of handling and modeling data issues in DEA problems. It is a handbook treatment dealing with specific data problems, including imprecise data and undesirable outputs.

342 pages, Paperback

First published January 1, 2007