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Handbook on Data Envelopment Analysis - (International Operations Research & Management Science) 2nd Edition (Paperback)
About this item
Highlights
- This handbook covers DEA topics that are extensively used and solidly based.
- Author(s): William W Cooper & Lawrence M Seiford & Joe Zhu
- 498 Pages
- Business + Money Management, Operations Research
- Series Name: International Operations Research & Management Science
Description
About the Book
Focusing on extensively used Data Envelopment Analysis topics, this volume aims to both describe the state of the field and extend the frontier of DEA research. New chapters include DEA models for DMUs, network DEA, models for supply chain operations and applications, and new developments.Book Synopsis
This handbook covers DEA topics that are extensively used and solidly based. The purpose of the handbook is to (1) describe and elucidate the state of the field and (2), where appropriate, extend the frontier of DEA research. It defines the state-of-the-art of DEA methodology and its uses. This handbook is intended to represent a milestone in the progression of DEA. Written by experts, who are generally major contributors to the topics to be covered, it includes a comprehensive review and discussion of basic DEA models, which, in the present issue extensions to the basic DEA methods, and a collection of DEA applications in the areas of banking, engineering, health care, and services. The handbook's chapters are organized into two categories: (i) basic DEA models, concepts, and their extensions, and (ii) DEA applications. First edition contributors have returned to update their work.
The second edition includes updated versions of selected first edition chapters. New chapters have been added on: different approaches with no need for a priori choices of weights (called "multipliers) that reflect meaningful trade-offs, construction of static and dynamic DEA technologies, slacks-based model and its extensions, DEA models for DMUs that have internal structures network DEA that can be used for measuring supply chain operations, Selection of DEA applications in the service sector with a focus on building a conceptual framework, research design and interpreting results.
From the Back Cover
This handbook covers DEA topics that are extensively used and solidly based. The purpose of the handbook is to (1) describe and elucidate the state of the field and (2), where appropriate, extend the frontier of DEA research. It defines the state-of-the-art of DEA methodology and its uses. This handbook is intended to represent a milestone in the progression of DEA. Written by experts, who are generally major contributors to the topics to be covered, it includes a comprehensive review and discussion of basic DEA models, which, in the present issue extensions to the basic DEA methods, and a collection of DEA applications in the areas of banking, engineering, health care, and services. The handbook's chapters are organized into two categories: (i) basic DEA models, concepts, and their extensions, and (ii) DEA applications. First edition contributors have returned to update their work.
The second edition includes updated versions of selected first edition chapters. New chapters have been added on:
- Different approaches with no need for a priori choices of weights (called "multipliers) that reflect meaningful trade-offs.
- Construction of static and dynamic DEA technologies.
- Slacks-based model and its extensions
- DEA models for DMUs that have internal structures network DEA that can be used for measuring supply chain operations.
- Selection of DEA applications in the service sector with a focus on building a conceptual framework, research design and interpreting results.Review Quotes
From the reviews:
"This handbook provides a valuable overview of DEA models on the one hand and many DEA applications supplemented by software information on the other hand. ... can be recommended to researchers, students and practitioners with basic knowledge of DEA who are interested in current DEA methodology and applications." (Andreas Kleine, OR-News Gesellschaft für Operations Research (GOR) e.V., Iss. 24, Juli, 2005)