"This is the colorful and dramatic biography of two of America's most controversial entrepreneurs: Moses Louis Annenberg, 'the racing wire king, ' who built his fortune in racketeering, invested it in publishing, and lost much of it in the biggest tax evasion case in United States history; and his son, Walter, launcher of TV Guide and Seventeen magazines and former ambassador to Great Britain."--Jacket.
This paper measures energy efficiency improvements of US single-family homes between 1997 and 2001 using a two-stage procedure. In the first stage, an indicator of energy efficiency is derived by means of Data Envelopment Analysis (DEA), and the analogy between the DEA estimator and traditional measures of energy efficiency is demonstrated. The second stage employs a bootstrapped truncated regression technique to decompose the variation in the obtained efficiency estimates into a climatic component and factors attributed to efficiency improvements. Results indicate a small but significant improvement of energy efficiency over the studied time interval, mainly accounted for by fuel oil and natural gas users.
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 measuring system efficiency, but also the internal structure of the system being analyzed. By analyzing the efficiency of individual internal components, and more particularly by studying the effects of relationships among components which are modeled and implemented by means of various network structures, the “network DEA” approach is able to help identify and manage the specific components that contribute inefficiencies into the overall systems. This relatively new approach comprises an important analytical tool based on mathematical programming techniques, with valuable implications to production and operations management. The existing models for measuring the efficiency of systems of specific network structures are also discussed, and the relationships between the system and component efficiencies are explored. This book should be able to inspire new research and new applications based on the current state of the art. Performance evaluation is an important task in management, and is needed to (i) better understand the past accomplishments of an organization and (ii) plan for its future development. However, this task becomes rather challenging when multiple performance metrics are involved. DEA is a powerful tool to cope with such issues. For systems or operations composed of interrelated processes, managers need to know how the performances of the various processes evaluated and how they are aggregated to form the overall performance of the system. This book provides an advanced exposition on performance evaluation of systems with network structures. It explores the network nature of most production and operation systems, and explains why network analyses are necessary.
This book provides an introduction to incorporating preference information in Data Envelopment Analysis (DEA) with a special emphasis in Value Efficiency Analysis. In addition to theoretical considerations, numerous illustrative examples are included. Hence, the book can be used as a teaching text as well. Only a modest mathematical background is needed to understand the main principles. The only prerequisites are a) familiarity with linear algebra, especially matrix calculus; b) knowledge of the simplex method; and c) familiarity with the use of computer software. The book is organized as follows. Chapter 1 provides motivation and introduces the basic concepts. Chapter 2 provides the basic ideas and models of Data Envelopment Analysis. The efficient frontier and production possibility set concepts play an important role in all considerations. That's why these concepts are considered more closely in Chapter 3. Since the approaches introduced in this study are inspired by Multiple Objective Linear Programming, the basic concepts of this field are reviewed in Chapter 4. Chapter 5 also compares and contrasts Data Envelopment Analysis and Multiple Objective Linear Programming, providing some cornerstones for approaches presented later in the book. Chapter 6 discusses the traditional approaches to take into account preference information in DEA. In Chapter 7, Value Efficiency is introduced, and Chapter 8 discusses practical aspects. Some extensions are presented in Chapter 9, and in Chapter 10 Value Efficiency is extended to cover the case when a production possibility set is not convex. Three implemented applications are reviewed in Chapter 11.
Introducing Data Envelopment Analysis (DEA) -- a quantitative approach to assess the performance of hedge funds, funds of hedge funds, and commmodity trading advisors. Steep yourself in this approach with this important new book by Greg Gregoriou and Joe Zhu. "This book steps beyond the traditional trade-off between single variables for risk and return in the determination of investment portfolios. For the first time, a comprehensive procedure is presented to compose portfolios using multiple measures of risk and return simultaneously. This approach represents a watershed in portfolio construction techniques and is especially useful for hedge fund and CTA offerings." -- Richard E. Oberuc, CEO, Burlington Hall Asset Management, Inc. Chairman, Foundation for Managed Derivatives Research Order your copy today!
This is the eBook version of the printed book. This digtial Short Cut provides a concise and supremely useful guide to the emerging trend of User Acceptance Testing (UAT). The ultimate goal of UAT is to validate that a system of products is of sufficient quality to be accepted by the users and, ultimately, the sponsors. This Short Cut is unique in that it views UAT through the concept that the user should be represented in every step of the software delivery lifecycle--including requirements, designs, testing, and maintenance--so that the user community is prepared, and even eager, to accept the software once it is completed. Rob Cimperman offers an informal explanation of testing, software development, and project management to equip business testers with both theory and practical examples, without the overwhelming details often associated with books written for "professional" testers. Rather than simply explaining what to do, this resource is the only one that explains why and how to do it by addressing this market segment in simple, actionable language. Throughout the author’s considerable experience coordinating UAT and guiding business testers, he has learned precisely what testers do and do not intuitively understand about the software development process. UAT Defined informs the reader about the unfamiliar political landscape they will encounter. Giving the UAT team the tools they need to comprehend the process on their own saves the IT staff from having to explain test management from the beginning. The result is a practice that increases productivity and eliminates the costs associated with unnecessary mistakes, tedious rework, and avoidable delays. Chapter 1 Introduction Chapter 2 Defining UAT–What It Is...and What It Is Not Chapter 3 Test Planning–Setting the Stage for UAT Success Chapter 4 Building the Team–Transforming Users into Testers Chapter 5 Executing UAT–Tracking and Reporting Chapter 6 Mitigating Risk–Your Primary Responsibility
This proceedings volume examines the state-of-the art of productivity and efficiency analysis and adds to the existing research by bringing together a selection of the best papers from the 8th North American Productivity Workshop (NAPW). It also aims to analyze world-wide perspectives on challenges that local economies and institutions may face when changes in productivity are observed. The volume comprises of seventeen papers that deal with productivity measurement, productivity growth, dynamics of productivity change, measures of labor productivity, measures of technical efficiency in different sectors, frontier analysis, measures of performance, industry instability and spillover effects. These papers are relevant to academia, but also to public and private sectors in terms of the challenges firms, financial institutions, governments and individuals may face when dealing with economic and education related activities that lead to increase or decrease of productivity. The North American Productivity Workshop brings together academic scholars and practitioners in the field of productivity and efficiency analysis from all over the world. It is a four day conference exploring topics related to productivity, production theory and efficiency measurement in economics, management science, operations research, public administration, and related fields. The papers in this volume also address general topics as health, energy, finance, agriculture, utilities, and economic dev elopment, among others. The editors are comprised of the 2014 local organizers, program committee members, and celebrated guest conference speakers.
A guide to computer security discusses how the "blackhat community" uses the Internet for destructive purposes and provides information on how to learn from a "blackhat" attack to protect computer networks.
Efficiency Analysis details the important econometric area of efficiency estimation, both past approaches as well as new methodology. There are two main camps in efficiency analysis: that which estimates maximal output and attributes all departures from this as inefficiency, known as Data Envelopment Analysis (DEA), and that which allows for both unobserved variation in output due to shocks and measurement error as well as inefficiency, known as Stochastic Frontier Analysis (SFA). This volume focuses exclusively on SFA. The econometric study of efficiency analysis typically begins by constructing a convoluted error term that is composed on noise, shocks, measurement error, and a one-sided shock called inefficiency. Early in the development of these methods, attention focused on the proposal of distributional assumptions which yielded a likelihood function whereby the parameters of the distributional components of the convoluted error could be recovered. The field evolved to the study of individual specific efficiency scores and the extension of these methods to panel data. Recently, attention has focused on relaxing the stringent distributional assumptions that are commonly imposed, relaxing the functional form assumptions commonly placed on the underlying technology, or some combination of both. All told exciting and seminal breakthroughs have occurred in this literature, and reviews of these methods are needed to effectively detail the state of the art. The generality of SFA is such that the study of efficiency has gone beyond simple application of frontier methods to study firms and appears across a diverse set of applied milieus. This review should appeal to those outside of the efficiency literature seeking to learn about new methods which might assist them in uncovering phenomena in their applied area of interest.
