Modeling Performance Measurement

Advances in Experimental Medicine and Biology

Book 566
Springer Science & Business Media
Free sample

Modeling Performance Measurement: Applications and Implementation Issues in DEA presents unified results from several authors’ recent DEA research. These new DEA methodology and techniques are developed in application-driven scenarios that go beyond the identification of the best-practice frontier and seek solutions to aid managerial decisions. These new DEA developments are well-grounded in real world applications. Both DEA researchers and practitioners will find this book helpful. Theory is provided for DEA researchers for further development and possible extensions. However, it should also be mentioned that each theory is presented in practical terms with numerical examples, simple real management cases and verbal descriptions. These concrete examples will be of value to researchers, students, and practitioners.
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About the author

GREG N. GREGORIOU is Assistant Professor of Finance and coordinator of faculty research in the School of Business and Economics at the State University of New York (Plattsburgh). He received his BA in economics from Concordia University and his MBA and PhD in finance from the University of Quebec at Montreal. He is an associate with the Peritus Group in Montreal and the hedge fund editor and an editorial board member for Derivatives Use, Trading and Regulation (London). Gregoriou has published over forty articles on hedge funds and CTAs for peer-reviewed publications such as the Journal of Futures Markets, European Journal of Operational Research, Annals of Operations Research, European Journal of Finance, and Journal of Asset Management. He is coauthor or coeditor of three books on hedge funds and CTAs: Performance Evaluation of Hedge Funds; Hedge Funds: Strategies, Risk Assessment, and Returns; and Commodity Trading Advisors: Risk, Performance Analysis, and Selection (Wiley).

JOE ZHU is Associate Professor of Operations in the Department of Management at Worcester Polytechnic Institute. Zhu received his PhD in industrial engineering and operations research from the University of Massachusetts Amherst. Zhu has published two books focusing on performance evaluation using Data Envelopment Analysis and has developed the DEAFrontier software. An associate editor of the Omega journal, he is an expert in methods of performance measurement. Dr. Zhu has published over forty refereed papers in journals such as Management Science, Operations Research, IIE Transactions, and the Journal of Operational Research Society.

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Additional Information

Publisher
Springer Science & Business Media
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Published on
Jun 3, 2006
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Pages
408
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ISBN
9780387241388
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Best For
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Language
English
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Genres
Business & Economics / Econometrics
Business & Economics / General
Business & Economics / Management
Business & Economics / Management Science
Business & Economics / Operations Research
Business & Economics / Production & Operations Management
Technology & Engineering / Engineering (General)
Technology & Engineering / General
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Content Protection
This content is DRM protected.
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The International Society of Oxygen Transport to Tissue (ISOTT) was founded in 1973 to provide a forum for bioengineers, basic scientists, physiologists, and physicians to discuss new data, original theories, new interpretations of old data, and new technologies for the measurement of oxygen. At each annual meeting all posters are presented orally along with plenary lectures, and all presentations are given in a general session attended by everyone. Each meeting has had a specific focus, ranging from neonatology to physical chemistry to cancer biology. The Society has helped to build many careers, through opportunities to meet leaders in the field, and through awards made to young physicians and scientists. The Society also, through cross fertilization of ideas and scientific comradery, has inspired many breakthroughs in clinical medicine that now benefit mankind. I find myself president of the society after having been a winner of the Melvin Knisely Award for young scientists, in 1991. The 2003 meeting emphasized the role of oxygen and oxygen measurement in tumor growth, metastasis, physiology, and treatment resistance. Additionally, however, completely novel approaches to measurement of tissue oxygen were presented (notably work by Dr. Takahashi) and molecular methods for estimating tissue oxygen were evaluated. Papers discussing other aspects of oxygen measurement and pathophysiology were presented including in vivo ESR spectroscopy (notably including Dr. Swartz and colleagues), exercise physiology, organ transplant outcome (discussed by Dr. Cicco, our 2004 president), circulatory physiology, and cerebral oxygenation (notably including Dr. Chance).
Frontiers in Biochip Technology
Dr. Wan-Li Xing and Dr. Jing Cheng

Frontiers in Biochip Technology serves as an essential collection of new research in the field of biochip technology. This comprehensive collection covers emerging technologies and cutting –edge research in the field of biochip technology, with all chapters written by the international stars of this evolving field.

Key topics and current trends in biochip technology covered include:

-microarray technology and its applications

- microfluidics

- drug discovery

- detection technology

- lab-on-chip technology and bioinformatics.

Frontiers in Biochip Technology is an important volume for all biotechnologists, bioengineers, genetic engineers, pharmacological researchers, and general bench researchers who want to be up-to-date on the latest advances in the rapidly growing field of biochip technology.

The Editors:

Dr. Wan-Li Xing, Tsinghua University School of Medicine, National Engineering Research Center for Beijing Biochip Technology (NERCBBT), and CapitalBio Corporation, Beijing, China
Dr. Xing is a Professor at Medical Systems Biology Research Center, Tsinghua University School of Medicine, and also serves as the Executive Deputy Director at NERCBBT, CapitalBio Corporation, a world-leader in biochip research. Dr. Xing has published widely and obtained many patents and applications.

Dr. Jing Cheng, Tsinghua University School of Medicine, National Engineering Research Center for Beijing Biochip Technology (NERCBBT), and CapitalBio Corporation, Beijing, China
Dr. Jing Cheng is the Cheung Kong Professor at Medical Systems Biology Research Center, Tsinghua University School of Medicine, the Director of NERCBBT and CEO & CTO of CapitalBio. Dr. Cheng developed the world’s first system of laboratory-on-a-chip in 1998; this work was featured in the front-cover story of the June 1998 issue of Nature Biotechnology and cited as the breakthrough of the year by Science in the same year. He has been awarded Nanogen’s most prestigious award Nano Grant, Distinguished Achievement Award for Overseas Chinese Scholars Returned, China’s Science & Technology Award for Outstanding Youth, and Qiushi Technology Transfer Award for Outstanding Youth. Dr. Cheng has published over 90 peer-reviewed papers. In addition, he has obtained over 60 European and U.S. patents and applications.


The possibility that nutrition in early life could influence propensity to adult disease is of great concern to public health. Extensive research carried out in pregnant women, in breastfeeding women and in infants strongly suggests that nutrition in early life has major effects on long-term health and well-being. Health problems such as hypertension, tendency to diabetes, obesity, blood lipids, vascular disease, bone health, behaviour and learning and longevity may be ‘imprinted’ during early life. This process is defined as ‘programming’ whereby a nutritional stimulus operating at a critical, sensitive period of pre and postnatal life imprints permanent effects on the structure, physiology and metabolism.

For this reason, academics and industry set-up the EC supported Scientific Workshop -Early Nutrition and its Later Consequences: New Opportunities. The prime objective of the Workshop was to generate a sound exchange of the latest scientific developments within the field of early nutrition to look for opportunities for new preventive health concepts. Further, a closer look was taken at the development of food applications which could provide (future) mothers and infants with improved nutrition that will ultimately lead to better future health. The Workshop was organised by the Dept. of Pediatrics, University of Munich, Germany in collaboration with the Danone Institutes and the Infant Nutrition Cluster, a collaboration of three large research projects funded by the EU.

Many of the contributors have important roles to play in a new EC supported integrated project: Early nutrition programming of adult health (EARNEST) which will take place between 2005 and 2010 and will involve more than 40 research centres. Further Workshops on the same theme are planned as part of this project.

In recent years, supply chain planning has emerged as one of the most challenging problems in the industry. As a consequence, the planning focus is shifting from the management of plant-speci?c operations to a holistic view of the various logistics and productionstages, that is an approach in which suppliers, productionplants and customers are considered as constituents of an integrated network. A major dr- ing force behind this development lies in the globalization of the world economy, which has facilitated the co-operation between different partners working together in world-wide logistics networks. Hence, considerable cost savings can be gained from optimizing the structure and the operations of complex supply networks li- ing plants, suppliers, distribution centres and customers. Consequently, to improve the performance of the entire logistic chain, more sophisticated planning systems and more effective decision support are needed. Clearly, successful applications of supply chain management have driven the development of advanced planning systems (APS), which are concerned with s- porting decision-making activities at the strategic, tactical and operational decision level. These software packages basically rely on the application of quantitative methods, which are used to model the underlying complex decision problems c- sidering the limited availability of resources and the need to react on time to customer orders. The core module at the mid-term level of APS comprises op- ational supply chain planning. In many industries, productionstages are assigned to differentplantsand distribution centreshave been established at geographicallyd- persed locations.
In scheduling theory, the models that have attracted considerable attention during the last two decades allow the processing times to be variable, i.e., to be subjected to various effects that make the actual processing time of a job dependent on its location in a schedule. The impact of these effects includes, but is not limited to, deterioration and learning. Under the first type of effect, the later a job is scheduled, the longer its actual processing time becomes. In the case of learning, delaying a job will result in shorter processing times. Scheduling with Time-Changing Effects and Rate-Modifying Activities covers and advances the state-of-the-art research in this area.

The book focuses on single machine and parallel machine scheduling problems to minimize either the maximum completion time or the sum of completion times of all jobs, provided that the processing times are subject to various effects. Models that describe deterioration, learning and general non-monotone effects to be considered include positional, start-time dependent, cumulative and their combinations, which cover most of the traditionally used models. The authors also consider more enhanced models in which the decision-maker may insert certain Rate-Modifying Activities (RMA) on processing machines, such as for example, maintenance or rest periods. In any case, the processing times of jobs are not only dependent on effects mentioned above but also on the place of a job in a schedule relative to an RMA. For most of the enhanced models described in the book, polynomial-time algorithms are presented which are based on similar algorithmic ideas such as reduction to linear assignment problems (in a full form or in a reduced form), discrete convexity, and controlled generation of options.

“Supply Chain Risk Management is an issue that many companies face and yet few companies know how to deal with it in a systematic and pragmatic manner. While avoiding and reducing supply chain risks are certainly preferable, developing ways to restore and stabilize supply chain operations rapidly after a major disruption is critical for managing global supply chains. Sodhi and Tang present important concepts, frameworks, strategies, and analyses that are essential for managing supply chain risks. Not only does this book suggest some practical ways to work with different partners to manage the risks that are present in a global supply chain, it creates a framework that would enable practitioners to engage researchers to work on this important area.”
—Thomas A. Debrowski, Executive Vice President, Worldwide Operations, Mattel, Inc.

“When a firm outsources its operations to external suppliers, the firm is vulnerable to major and rare disruptions that can occur at any link in the global supply chain. Because these disruptions rarely occur, few firms take commensurable actions to identify, assess, mitigate and respond to various types of supply chain risks. By introducing frameworks and concepts along with several case studies and a review of academic literature, Sodhi and Tang treat this important subject with practical relevance and academic rigor. This book will bring practitioners and researchers to develop effective and efficient ways to manage supply chain risks.”
—Marshall L. Fisher, UPS Professor, Professor of Operations and Information Management and Co-Director of Fishman-Davidson Center for Service and Operations Management, The Wharton School, University of Pennsylvania

“This book ties observations in practice to methodologies and research. The rich case examples motivated the approaches and methodologies used to mitigate risks, and in the course of doing so, Sodhi and Tang provided insights on existing and new research opportunities. As a result, this book is highly relevant to both practitioners and academics. Also, the book is also written with management lessons on how risks can be mitigated, and how risks can be contained once disruptions have occurred. As such, it is also a book for management to gain insights and to develop management skills.”
—Hau L. Lee, Thoma Professor of Operations, Information and Technology and Director of the Stanford Global Supply Chain Management Forum, Graduate School of Business, Stanford University

“As companies have extended their supply chains globally and as the face increasing resource issues, they face a number of new risk challenges. While there are various case studies written about supply chain risks, this book gives a comprehensive treatment of the subject with clarity. The concepts and frameworks developed by Sodhi and Tang in this book would create awareness of this important and yet not well understood subject, and strategies described in this book would stimulate practitioners to develop a holistic approach for identifying, assessing, mitigating, and responding to different types of supply chain risks.”
—Nick Wildgoose, Global Supply Chain Proposition Manager, Zurich Insurance
This handbook serves as a complement to the Handbook on Data Envelopment Analysis (eds, W.W. Cooper, L.M. Seiford and J, Zhu, 2011, Springer) in an effort to extend the frontier of DEA research. It provides a comprehensive source for the state-of-the art DEA modeling on internal structures and network DEA. Chapter 1 provides a survey on two-stage network performance decomposition and modeling techniques. Chapter 2 discusses the pitfalls in network DEA modeling. Chapter 3 discusses efficiency decompositions in network DEA under three types of structures, namely series, parallel and dynamic. Chapter 4 studies the determination of the network DEA frontier. In chapter 5 additive efficiency decomposition in network DEA is discussed. An approach in scale efficiency measurement in two-stage networks is presented in chapter 6. Chapter 7 further discusses the scale efficiency decomposition in two stage networks. Chapter 8 offers a bargaining game approach to modeling two-stage networks. Chapter 9 studies shared resources and efficiency decomposition in two-stage networks. Chapter 10 introduces an approach to computing the technical efficiency scores for a dynamic production network and its sub-processes. Chapter 11 presents a slacks-based network DEA. Chapter 12 discusses a DEA modeling technique for a two-stage network process where the inputs of the second stage include both the outputs from the first stage and additional inputs to the second stage. Chapter 13 presents an efficiency measurement methodology for multi-stage production systems. Chapter 14 discusses network DEA models, both static and dynamic. The discussion also explores various useful objective functions that can be applied to the models to find the optimal allocation of resources for processes within the black box, that are normally invisible to DEA. Chapter 15 provides a comprehensive review of various type network DEA modeling techniques. Chapter 16 presents shared resources models for deriving aggregate measures of bank-branch performance, with accompanying component measures that make up that aggregate value. Chapter 17 examines a set of manufacturing plants operating under a single umbrella, with the objective being to use the component or function measures to decide what might be considered as each plant’s core business. Chapter 18 considers problem settings where there may be clusters or groups of DMUs that form a hierarchy. The specific case of a set off electric power plants is examined in this context. Chapter 19 models bad outputs in two-stage network DEA. Chapter 20 presents an application of network DEA to performance measurement of Major League Baseball (MLB) teams. Chapter 21 presents an application of a two-stage network DEA model for examining the performance of 30 U.S. airline companies. Chapter 22 then presents two distinct network efficiency models that are applied to engineering systems.
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