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This new edition continues to emphasize the use of data envelopment analysis (DEA) to create optimization-based benchmarks within hospitals, physician group practices, health maintenance organizations, nursing homes and other health care delivery organizations. Suitable for graduate students learning DEA applications in health care as well as for practicing administrators, it is divided into two sections covering methods and applications. Section I considers efficiency evaluations using DEA; returns to scale; weight restricted (multiplier) models; non-oriented or slack-based models, including in this edition two versions of non-controllable variable models and categorical variable models; longitudinal (panel) evaluations and the effectiveness dimension of performance evaluation. A new chapter then looks at new and advanced models of DEA, including super-efficiency, congestion DEA, network DEA, and dynamic network models. Mathematical formulations of various DEA models are placed in end-of-chapter appendices. Section II then looks at health care applications within particular settings, chapter-by-chapter, including hospitals, physician practices, nursing homes and health maintenance organizations (HMOs). Other chapters then explore home health care and home health agencies; dialysis centers, community mental health centers, community-based your services, organ procurement organizations, aging agencies and dental providers; DEA models to evaluate provider performance for specific treatments, including stroke, mechanical ventilation and perioperative services. A new chapter then examines international-country-based applications of DEA in health care in 16 different countries, along with OECD and multi-country studies. Most of the existing chapters in this section were expanded with recent applications. Included with the book is online access to a learning version of DEA Solver software, written by Professor Kaoru Tone, which can solve up to 50 DMUs for various DEA models listed in the User’s Guide at the end of the book.
The author is one of the prominent researchers in the field of Data Envelopment Analysis (DEA), a powerful data analysis tool that can be used in performance evaluation and benchmarking. This book is based upon the author’s years of research and teaching experiences. It is difficult to evaluate an organization’s performance when multiple performance metrics are present. The difficulties are further enhanced when the relationships among the performance metrics are complex and involve unknown tradeoffs. This book introduces Data Envelopment Analysis (DEA) as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective. Conventional and new DEA approaches are presented and discussed using Excel spreadsheets — one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets. DEA models and approaches are presented to deal with performance evaluation problems in a variety of contexts. For example, a context-dependent DEA measures the relative attractiveness of similar operations/processes/products. Sensitivity analysis techniques can be easily applied, and used to identify critical performance measures. Two-stage network efficiency models can be utilized to study performance of supply chain. DEA benchmarking models extend DEA’s ability in performance evaluation. Various cross efficiency approaches are presented to provide peer evaluation scores. This book also provides an easy-to-use DEA software — DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches. This version of DEAFrontier is for use with Excel 97-2013 under Windows and can solve up to 50 DMUs, subject to the capacity of Excel Solver. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational performance issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, public services and many other industries.
Computer and microprocessor architectures are advancing at an astounding pace. However, increasing demands on performance coupled with a wide variety of specialized operating environments act to slow this pace by complicating the performance evaluation process. Carefully balancing efficiency and accuracy is key to avoid slowdowns, and such a balance can be achieved with an in-depth understanding of the available evaluation methodologies. Performance Evaluation and Benchmarking outlines a variety of evaluation methods and benchmark suites, considering their strengths, weaknesses, and when each is appropriate to use. Following a general overview of important performance analysis techniques, the book surveys contemporary benchmark suites for specific areas, such as Java, embedded systems, CPUs, and Web servers. Subsequent chapters explain how to choose appropriate averages for reporting metrics and provide a detailed treatment of statistical methods, including a summary of statistics, how to apply statistical sampling for simulation, how to apply SimPoint, and a comprehensive overview of statistical simulation. The discussion then turns to benchmark subsetting methodologies and the fundamentals of analytical modeling, including queuing models and Petri nets. Three chapters devoted to hardware performance counters conclude the book. Supplying abundant illustrations, examples, and case studies, Performance Evaluation and Benchmarking offers a firm foundation in evaluation methods along with up-to-date techniques that are necessary to develop next-generation architectures.
This book constitutes the refereed post-conference proceedings of the 12th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2020, held in August 2020.The 8 papers presented were carefully reviewed and cover the following topics: testing ACID compliance in the LDBC social network benchmark; experimental performance evaluation of stream processing engines made easy; revisiting issues in benchmarking metric selection; performance evaluation for digital transformation; experimental comparison of relational and NoSQL document systems; a framework for supporting repetition and evaluation in the process of cloud-based DBMS performance benchmarking; benchmarking AI inference; a domain independent benchmark evolution model for the transaction processing performance council.
First established in August 1988, the Transaction Processing Performance Council (TPC) has shaped the landscape of modern transaction processing and database benchmarks over two decades. Now, the world is in the midst of an extraordinary information explosion led by rapid growth in the use of the Internet and connected devices. Both user-generated data and enterprise data levels continue to grow ex- nentially. With substantial technological breakthroughs, Moore's law will continue for at least a decade, and the data storage capacities and data transfer speeds will continue to increase exponentially. These have challenged industry experts and researchers to develop innovative techniques to evaluate and benchmark both hardware and software technologies. As a result, the TPC held its First Conference on Performance Evaluation and Benchmarking (TPCTC 2009) on August 24 in Lyon, France in conjunction with the 35th International Conference on Very Large Data Bases (VLDB 2009). TPCTC 2009 provided industry experts and researchers with a forum to present and debate novel ideas and methodologies in performance evaluation, measurement and characteri- tion for 2010 and beyond. This book contains the proceedings of this conference, including 16 papers and keynote papers from Michael Stonebraker and Karl Huppler.
To design and develop capable, dependable, and affordable intelligent systems, their performance must be measurable. Scienti?c methodologies for standardization and benchmarking are crucial for quantitatively evaluating the performance of eme- ing robotic and intelligent systems’ technologies. There is currently no accepted standard for quantitatively measuring the performance of these systems against user-de?ned requirements; and furthermore, there is no consensus on what obj- tive evaluation procedures need to be followed to understand the performance of these systems. The lack of reproducible and repeatable test methods has precluded researchers working towards a common goal from exchanging and communic- ing results, inter-comparing system performance, and leveraging previous work that could otherwise avoid duplication and expedite technology transfer. Currently, this lack of cohesion in the community hinders progress in many domains, such as m- ufacturing, service, healthcare, and security. By providing the research community with access to standardized tools, reference data sets, and open source libraries of solutions, researchers and consumers will be able to evaluate the cost and be- ?ts associated with intelligent systems and associated technologies. In this vein, the edited book volume addresses performance evaluation and metrics for intel- gent systems, in general, while emphasizing the need and solutions for standardized methods. To the knowledge of the editors, there is not a single book on the market that is solely dedicated to the subject of performance evaluation and benchmarking of intelligent systems.
In 1997, Congress, in the conference report, H.R. 105-271, to the FY1998 Energy and Water Development Appropriation Bill, directed the National Research Council (NRC) to carry out a series of assessments of project management at the Department of Energy (DOE). The final report in that series noted that DOE lacked an objective set of measures for assessing project management quality. The department set up a committee to develop performance measures and benchmarking procedures and asked the NRC for assistance in this effort. This report presents information and guidance for use as a first step toward development of a viable methodology to suit DOE's needs. It provides a number of possible performance measures, an analysis of the benchmarking process, and a description ways to implement the measures and benchmarking process.
In order to make sound investment choices, investors must know the projected return on investment in relation to the risk of not being paid. Benchmarks are excellent evaluators, but the failure to choose the right investing performance benchmark often leads to bad decisions or inaction, which inevitably results in lost profits. The first book of its kind, Portfolio Performance Measurement and Benchmarking is a complete guide to benchmarks and performace evaluation using benchmarks. In one inclusive volume, readers get foundational coverage on benchmark construction, as well as expert insight into specific benchmarks for asset classes and investment styles. Starting with the basics—such as return calculations and methods of dealing with cash flows—this thorough book covers a wide variety of performance measurement methodologies and evaluation techniques before moving into more technical material that deconstructs both the creation of indexes and the components of a desirable benchmark. Portfolio Performance Measurement and Benchmarking provides detailed coverage of benchmarks for: U.S. equities Global and international equities Fixed income Real estate The team of renowned authors offers illuminating opinions on the philosophy and development of equity indexes, while highlighting numerous mechanical problems inherent in building benchmarks and the implications of each one. Before you make your next investment, be certain your return will be worth the risk with Portfolio Performance Measurement and Benchmarking.
The book discusses rationales for creating and updating benchmarks, the use of benchmarks in academic research, benchmarking methodologies, the relation of SPEC benchmarks to other benchmarking activities, shortcomings of current benchmarks, and the need for further benchmarking efforts. Performance evaluation and benchmarking are of concern to all computer-related disciplines. A benchmark is a standard program or set of programs that can be run on different computers to give an accurate measure of their performance. This book covers a variety of aspects of computer performance evaluation, with a focus on Standard Performance Evaluation Corporation (SPEC) benchmarks. SPEC is a nonprofit organization whose members represent industry, academia, and other organizations. The book discusses rationales for creating and updating benchmarks, the use of benchmarks in academic research, benchmarking methodologies, the relation of SPEC benchmarks to other benchmarking activities, shortcomings of current benchmarks, and the need for further benchmarking efforts. Contributors Brian Armstrong, Frederica Darema, Edward S. Davidson, Sylvia Dieckmann, Jozo J. Dujmovic, Rudolf Eigenmann, J. Kelly Flanagan, Greg Gaertner, Jonathan Geisler, John Gustafson, Urs Hölzle, Shih-Hao Hung, Kathryn S. McKinley, Reinhard Riedl, Faisal Saied, Frank Sorenson, Mark Straka, Valerie Taylor, Olivier Temam, Rajat Todi, Reinhold Weicker
Praise for Exemplary Performance "I have seen the transformative power of human performance improvement in the power industry where it has produced measurable results in areas such as safety performance. Executives, managers, and other leaders will benefit from this approach, enabling exemplary performance by replicating the results of their stars." Carl English, vice-chairman (retired), American Electric Power "A must-read for anyone accountable for producing and leading high-performing individuals or teams." Jamie Torchiana, learning implementation leader, Sales Strategy, AstraZeneca "Uniquely captures profound ideas, frames them concisely, and explains how they work in the real world in a powerful way. If you want to link your business's capability development to actual business outcome, this book might be all you need. A fantastic read." Don Shoultz, head of learning and development, BP Upstream Learning