Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References

Author:   William W. Cooper ,  Lawrence M. Seiford ,  Kaoru Tone
Publisher:   Springer-Verlag New York Inc.
Edition:   2006
ISBN:  

9780387285801


Pages:   354
Publication Date:   16 November 2005
Format:   Paperback
Availability:   Awaiting stock   Availability explained
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Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References


Overview

Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References has been carefully designed by the authors to provide a systematic introduction to DEA and its uses as a multifaceted tool for evaluating problems in a variety of contexts. The authors have been involved in DEA's development from the beginning. William Cooper (with Abraham Charnes and Edwardo Rhodes) is a founder of DEA. Lawrence Seiford and Kaoru Tone have been actively involved as researchers and practitioners from its earliest beginnings. All have been deeply involved in uses of DEA in practical applications as well as in the development of its basic theory and methodologies. The result is a textbook grounded in authority, experience and substance.

Full Product Details

Author:   William W. Cooper ,  Lawrence M. Seiford ,  Kaoru Tone
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2006
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   0.593kg
ISBN:  

9780387285801


ISBN 10:   0387285806
Pages:   354
Publication Date:   16 November 2005
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Awaiting stock   Availability explained
The supplier is currently out of stock of this item. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out for you.

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.- Discretionary, non-Discretionary and Categorical Variables.- Allocation Models.- Data Variations.- Super-Efficiency Models.

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