Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software / Edition 2

Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software / Edition 2

by William W. Cooper, Lawrence M. Seiford, Kaoru Tone
     
 

ISBN-10: 0387452818

ISBN-13: 9780387452814

Pub. Date: 12/01/2006

Publisher: Springer US

This volume systematically details both the basic principles and new developments in Data Envelopment Analysis (DEA), offering a solid understanding of the methodology, its uses, and its potential. New material in this edition includes coverage of recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research

Overview

This volume systematically details both the basic principles and new developments in Data Envelopment Analysis (DEA), offering a solid understanding of the methodology, its uses, and its potential. New material in this edition includes coverage of recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research and DEA uses. Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. The first nine chapters cover the basic principles of DEA, while the final seven chapters provide a more advanced treatment.

Product Details

ISBN-13:
9780387452814
Publisher:
Springer US
Publication date:
12/01/2006
Edition description:
2nd ed. 2007
Pages:
492
Product dimensions:
6.10(w) x 9.25(h) x 0.24(d)

Related Subjects

Table of Contents

General Discussion.- The Basic CCR Model.- The CCR Model and Production Correspondence.- Alternative Dea Models.- Returns to Scale.- Models with Restricted Multipliers.- Non-Discretionary and Categorical Variables.- Allocation Models.- Data Variations.- Super-Efficiency Models.- Efficiency Change over Time.- Scale Elasticity and Congestion.- Undesirable Outputs Models.- Economies of Scope and Capacity Utilization.- A Dea Game.- Multi-Stage Use of Parametric and Non-Parametric Models.

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