Data Envelopment Analysis A Handbook of Empirical Studies and Applic
This handbook compiles state-of-the-art empirical studies and applications using Data Envelopment Analysis (DEA). It includes a collection of 18 chapters written by DEA experts. Chapter 1 examines the performance of CEOs of U.S. banks and thrifts. Chapter
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Joe Zhu Editor
Data Envelopment Analysis A Handbook of Empirical Studies and Applications
International Series in Operations Research & Management Science Volume 238
Series Editor Camille C. Price Stephen F. Austin State University, TX, USA Associate Series Editor Joe Zhu Worcester Polytechnic Institute, MA, USA Founding Series Editor Frederick S. Hillier Stanford University, CA, USA
More information about this series at http://www.springer.com/series/6161
Joe Zhu Editor
Data Envelopment Analysis A Handbook of Empirical Studies and Applications
Editor Joe Zhu International Center for Auditing and Evaluation Nanjing Audit University Nanjing, P.R., China School of Business Worcester Polytechnic Institute Worcester, MA, USA
ISSN 0884-8289 ISSN 2214-7934 (electronic) International Series in Operations Research & Management Science ISBN 978-1-4899-7682-6 ISBN 978-1-4899-7684-0 (eBook) DOI 10.1007/978-1-4899-7684-0 Library of Congress Control Number: 2015959708 © Springer Science+Business Media New York 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
Preface
This handbook complements Handbook on Data Envelopment Analysis (eds, W.W. Cooper, L.M. Seiford, and J. Zhu, 2011, Springer), Data Envelopment Analysis: A Handbook of Modeling Internal Structures and Networks (eds, W.D. Cook and J. Zhu, 2014, Springer), and Data Envelopment Analysis: A Handbook of Models and Methods (ed. J. Zhu, 2015, Springer). Data envelopment analysis (DEA) is a “data-oriented” approach for evaluating the performance of a set of entities called decision-making units (DMUs) whose performance is categorized by multiple metrics. These performance metrics are classified or termed as inputs and outputs under DEA. Although DEA has a strong link to production theory in economics, the tool is also used for benchmarking in operations management
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