Externalities, side effects, and adverse impacts produced or resulting from the course of operations.
Published in Chapter:
Measuring Relative Efficiency and Effectiveness
David Lengacher (Concurrent Technologies Corporation, USA), Craig Cammarata (Concurrent Technologies Corporation, USA), and Shannon Lloyd (Concurrent Technologies Corporation, USA)
Copyright: © 2014
|Pages: 10
DOI: 10.4018/978-1-4666-5202-6.ch138
Abstract
Data Envelopment Analysis (DEA) has been used to supply decision makers and analysts with new insights into the efficiency of peer entities called decision making units (DMUs). The advantage of DEA is that it provides an objective data-driven assessment of performance, free of user bias. However, because factor weights are determined by an algorithm and not a priori, many researchers and practitioners have difficulty understanding DEA models and the scores they produce. This may explain why DEA is seldom covered in university courses in the decision sciences. The result of this lack of awareness and understanding is that DEA is underutilized as a performance measurement tool in commercial, government, and military operations. This chapter aims to address this issue by providing a lucid overview of DEA, replete with examples and suggestions to make DEA more accessible for researchers and practitioners alike. Additionally, our didactic approach includes step-by-step instructions for preparing data, choosing DEA models, and avoiding pitfalls.