Network Data Envelopment Analysis Foundations and Extensions
This book presents the underlying theory, model development, and applications of network Data Envelopment Analysis (DEA) in a systematic way. The field of network DEA extends and complements conventional DEA by considering not only inputs and outputs when
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Chiang Kao
Network Data Envelopment Analysis Foundations and Extensions
International Series in Operations Research & Management Science Volume 240
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
Chiang Kao
Network Data Envelopment Analysis Foundations and Extensions
Chiang Kao Department of Industrial and Information Management National Cheng Kung University Tainan, Taiwan
ISSN 0884-8289 ISSN 2214-7934 (electronic) International Series in Operations Research & Management Science ISBN 978-3-319-31716-8 ISBN 978-3-319-31718-2 (eBook) DOI 10.1007/978-3-319-31718-2 Library of Congress Control Number: 2016940506 © Springer International Publishing Switzerland 2017 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
How to use fewer resources to generate more outputs and services is a concern of all organizations, including profit-pursuing, government, nonprofit, and all other types of decision-making units (DMUs). This is a problem of efficiency, which has three phases: efficiency measurement, target setting, and goal achievement. Such issues have been studied by economists and management scientists for many years. Since the seminal work of Charnes, Cooper, and Rhodes in 1978, Data Envelopment Analysis (DEA) has become the preeminent nonparametric method for measuring the efficiency of DMUs that apply multiple inputs to produce multiple outputs. In addition to efficiency measurement, the DEA technique is also able to show how much output a DMU can be expected to increase with the current amount of input or how much input can be saved while producing the current leve
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