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

Data Envelopment Analysis (eBook, PDF)

A Comprehensive Text with Models, Applications, References and DEA-Solver Software

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 492
• Erscheinungstermin: 10. Januar 2007
• Englisch
• ISBN-13: 9780387452838
• Artikelnr.: 37286053

Autorenporträt

Data Envelopment Analysis (DEA) has grown into a powerful, quantitative analytical tool for measuring and evaluating performance. This volume offers a systematic introduction to DEA and its uses as a multifaceted tool for evaluating problems in a variety of contexts. Each chapter illustrates its concepts 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. For this new second edition, the final seven chapters have been completely revised, reflecting recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research and DEA uses. This new edition systematically details both basic principles and new developments in DEA, offering a solid understanding of the methodology, its uses, and its potential.

Inhaltsangabe

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.