Download or read book Benchmarking with a Dynamic DEA Model written by Ram Pratap Sinha and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: There was a paradigm shift in the competition scenario of the Indian commercial banking sector as a consequence of the initiation of banking sector reforms and opening up of the banking sector to the foreign participants in a gradual fashion. The present paper benchmarks the performance of public sector, private sector and foreign banks operating in India for the period 2006-07 to 2010-11 through a 'Dynamic Slacks-Based DEA Model'. The study also computes factor efficiency indicator for the output and link variables.
Download or read book Health Care Benchmarking and Performance Evaluation written by Yasar A. Ozcan and published by Springer. This book was released on 2014-07-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Quantitative Models for Performance Evaluation and Benchmarking written by Joe Zhu and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managers are often under great pressure to improve the performance of their organizations. To improve performance, one needs to constantly evaluate operations or processes related to producing products, providing services, and marketing and selling products. Performance evaluation and benchmarking are a widely used method to identify and adopt best practices as a means to improve performance and increase productivity, and are particularly valuable when no objective or engineered standard is available to define efficient and effective performance. For this reason, benchmarking is often used in managing service operations, because service standards (benchmarks) are more difficult to define than manufacturing standards. Benchmarks can be established but they are somewhat limited as they work with single measurements one at a time. It is difficult to evaluate an organization's performance when there are multiple inputs and outputs to the system. The difficulties are further enhanced when the relationships between the inputs and the outputs are complex and involve unknown tradeoffs. It is critical to show benchmarks where multiple measurements exist. The current book introduces the methodology of data envelopment analysis (DEA) and its uses in performance evaluation and benchmarking under the context of mUltiple performance measures.
Download or read book A Tutorial on Using Dynamic Network DEA to Benchmark Organizational Performance written by Necmi K. Avkiran and published by . This book was released on 2015 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: In investigating organizational performance or efficiency, two perennial problems confront us, namely, loss of information in aggregated data, and determining the influence of lower level variables when they are not explicitly identified in a performance model. It can be quite complicated to quantify various interactions using parametric methods that make distributional assumptions. An additional complication is how to capture the effect of undesirable outputs on organizational performance across time. The primary purpose of this tutorial is to illustrate step-by-step how non-parametric, dynamic network data envelopment analysis (DN-DEA) can be used to overcome the above problems and provide a refined estimate of relative efficiency. The tutorial begins with a discussion of the rationale for studying relative efficiency and a non-technical introduction to standard DEA. It then continues to illustrate how interactions across time among various inputs used in providing different levels of outputs can be captured and main potential improvements identified. DN-DEA enables an analysis where lower level variables in an organization are accounted for by disaggregating data, while simultaneously maintaining the focus on performance of the organization as well as its main divisions. Efficiency analysis of divisions across time can be an integral part of organizational learning and a source of competitive advantage.
Download or read book Data Envelopment Analysis Balanced Benchmarking written by Wade D. Cook and published by . This book was released on 2013-10-20 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current book introduces the methodology of data envelopment analysis (DEA). DEA uses mathematical programming techniques and models to evaluate the performance of peer units (e.g., bank branches, hospitals and schools) in terms of multiple performance measures or metrics. These multiple performance measures are classified or coined as DEA inputs and DEA outputs. Although DEA has a strong link to production theory in economics, the tool is also used for benchmarking in operations management, where a set of measures is selected to benchmark the performance of manufacturing and service operations. In the circumstance of benchmarking, the efficient DMUs, as defined by DEA, may not necessarily form a "production frontier", but rather lead to a "best-practice frontier". DEA's empirical orientation and absence of a priori assumptions have resulted in its use in a number of studies involving efficient or best-practice frontier estimation in the nonprofit, regulated, and private sectors. DEA applications involve a wide range of contexts, such as education, health care, banking, armed forces, auditing, market research, retail outlets, organization effectiveness, transportation, public housing, and manufacturing. DEA is a balanced benchmarking tool that will help organizations to examine their assumptions about their productivity and performance. The book provides students, researchers, and practitioners with a solid understanding of the methodology, its uses and potentials in business analytics.
Download or read book Research Methodology on Data Envelopment Analysis DEA written by Jibendu Kumar Mantri and published by Universal-Publishers. This book was released on 2008 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Envelopment Analysis (DEA) represents a milestone in the progression of a continuously advancing methodology for data analysis, which finds extensive use in industry, society and even in education. This book is a handy encyclopedia for researchers, students and practitioners looking for the latest and most comprehensive references in DEA. J.K. Mantri has specifically selected 22 research papers where DEA is applied in different fields so that the techniques discussed in this book can be used for various applications. In A Bibliography of Data Envelopment Analysis (1978-2001), Gabriel Tavares states that DEA is a mathematical programme for measuring performance efficiency of organizations popularly named as decision-making units (DMU). The DMU can be of any kind such as manufacturing units, a number of schools, banks, hospitals, police stations, firms, etc. DEA measures the performance efficiency of these kinds of DMUs, which share a common characteristic: they have a non-profit organization where measurement is difficult. DEA assumes the performance of the DMU using the concepts of efficiency and productivity, which are measured as the ratio of total outputs to total inputs. The efficiencies estimated are relative to the best performing DMU, which is given a score of 100%. The performance of other DMUs varies between 0% and 100%.
Download or read book Quantitative Models for Performance Evaluation and Benchmarking written by Joe Zhu and published by . This book was released on 2003 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in DEA Theory and Applications written by Kaoru Tone and published by John Wiley & Sons. This book was released on 2017-04-12 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: A key resource and framework for assessing the performance of competing entities, including forecasting models Advances in DEA Theory and Applications provides a much-needed framework for assessing the performance of competing entities with special emphasis on forecasting models. It helps readers to determine the most appropriate methodology in order to make the most accurate decisions for implementation. Written by a noted expert in the field, this text provides a review of the latest advances in DEA theory and applications to the field of forecasting. Designed for use by anyone involved in research in the field of forecasting or in another application area where forecasting drives decision making, this text can be applied to a wide range of contexts, including education, health care, banking, armed forces, auditing, market research, retail outlets, organizational effectiveness, transportation, public housing, and manufacturing. This vital resource: Explores the latest developments in DEA frameworks for the performance evaluation of entities such as public or private organizational branches or departments, economic sectors, technologies, and stocks Presents a novel area of application for DEA; namely, the performance evaluation of forecasting models Promotes the use of DEA to assess the performance of forecasting models in a wide area of applications Provides rich, detailed examples and case studies Advances in DEA Theory and Applications includes information on a balanced benchmarking tool that is designed to help organizations examine their assumptions about their productivity and performance.
Download or read book Data Enabled Analytics written by Joe Zhu and published by Springer Nature. This book was released on 2021-12-16 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.
Download or read book DEA Based Benchmarking Models in Supply Chain Management written by Gurdal Ertek and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Envelopment Analysis (DEA) is a mathematical methodology for benchmarking a group of entities in a group. The inputs of a DEA model are the resources that the entity consumes, and the outputs of the outputs are the desired outcomes generated by the entity, by using the inputs. DEA returns important benchmarking metrics, including efficiency score, reference set, and projections. While DEA has been extensively applied in supply chain management (SCM) as well as a diverse range of other fields, it is not clear what has been done in the literature in the past, especially given the domain, the model details, and the country of application. Also, it is not clear what would be an acceptable number of DMUs in comparison to existing research. This paper follows a recipe-based approach, listing the main characteristics of the DEA models for supply chain management. This way, practitioners in the field can build their own models without having to perform detailed literature search. Further guidelines are also provided in the paper for practitioners, regarding the application of DEA in SCM benchmarking.
Download or read book Benchmarking with DEA SFA and R written by Peter Bogetoft and published by Springer Science & Business Media. This book was released on 2010-11-19 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent advances in efficiency evaluations, most notably Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) methods. It introduces the underlying theories, shows how to make the relevant calculations and discusses applications. The aim is to make the reader aware of the pros and cons of the different methods and to show how to use these methods in both standard and non-standard cases. Several software packages have been developed to solve some of the most common DEA and SFA models. This book relies on R, a free, open source software environment for statistical computing and graphics. This enables the reader to solve not only standard problems, but also many other problem variants. Using R, one can focus on understanding the context and developing a good model. One is not restricted to predefined model variants and to a one-size-fits-all approach. To facilitate the use of R, the authors have developed an R package called Benchmarking, which implements the main methods within both DEA and SFA. The book uses mathematical formulations of models and assumptions, but it de-emphasizes the formal proofs - in part by placing them in appendices -- or by referring to the original sources. Moreover, the book emphasizes the usage of the theories and the interpretations of the mathematical formulations. It includes a series of small examples, graphical illustrations, simple extensions and questions to think about. Also, it combines the formal models with less formal economic and organizational thinking. Last but not least it discusses some larger applications with significant practical impacts, including the design of benchmarking-based regulations of energy companies in different European countries, and the development of merger control programs for competition authorities.
Download or read book Benchmarking for Performance Evaluation written by Subhash C. Ray and published by Springer. This book was released on 2015-03-25 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed introduction to the theoretical and methodological foundations of production efficiency analysis using benchmarking. Two of the more popular methods of efficiency evaluation are Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA), both of which are based on the concept of a production possibility set and its frontier. Depending on the assumed objectives of the decision-making unit, a Production, Cost, or Profit Frontier is constructed from observed data on input and output quantities and prices. While SFA uses different maximum likelihood estimation techniques to estimate a parametric frontier, DEA relies on mathematical programming to create a nonparametric frontier. Yet another alternative is the Convex Nonparametric Frontier, which is based on the assumed convexity of the production possibility set and creates a piecewise linear frontier consisting of a number of tangent hyper planes. Three of the papers in this volume provide a detailed and relatively easy to follow exposition of the underlying theory from neoclassical production economics and offer step-by-step instructions on the appropriate model to apply in different contexts and how to implement them. Of particular appeal are the instructions on (i) how to write the codes for different SFA models on STATA, (ii) how to write a VBA Macro for repetitive solution of the DEA problem for each production unit on Excel Solver, and (iii) how to write the codes for the Nonparametric Convex Frontier estimation. The three other papers in the volume are primarily theoretical and will be of interest to PhD students and researchers hoping to make methodological and conceptual contributions to the field of nonparametric efficiency analysis.
Download or read book Advances in DEA Theory and Applications written by Kaoru Tone and published by John Wiley & Sons. This book was released on 2017-04-12 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: A key resource and framework for assessing the performance of competing entities, including forecasting models Advances in DEA Theory and Applications provides a much-needed framework for assessing the performance of competing entities with special emphasis on forecasting models. It helps readers to determine the most appropriate methodology in order to make the most accurate decisions for implementation. Written by a noted expert in the field, this text provides a review of the latest advances in DEA theory and applications to the field of forecasting. Designed for use by anyone involved in research in the field of forecasting or in another application area where forecasting drives decision making, this text can be applied to a wide range of contexts, including education, health care, banking, armed forces, auditing, market research, retail outlets, organizational effectiveness, transportation, public housing, and manufacturing. This vital resource: Explores the latest developments in DEA frameworks for the performance evaluation of entities such as public or private organizational branches or departments, economic sectors, technologies, and stocks Presents a novel area of application for DEA; namely, the performance evaluation of forecasting models Promotes the use of DEA to assess the performance of forecasting models in a wide area of applications Provides rich, detailed examples and case studies Advances in DEA Theory and Applications includes information on a balanced benchmarking tool that is designed to help organizations examine their assumptions about their productivity and performance.
Download or read book Performance Benchmarking in Public Transport Sector The Data Envelopment Analysis DEA method written by Andreas Davidek and published by GRIN Verlag. This book was released on 2017-11-28 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2015 in the subject Business economics - Controlling, grade: 1,3, , course: Performance Benchmarking and Operations Research, language: English, abstract: The non-parametric approach is a common method for measuring the relative efficiency in the area of performance benchmarking and operations research. This approach does not require the a priori specification of a function. The estimation of the frontier of the production set only requires that the production set satisfies some properties, such as input and output factors. The Data Envelopment Analysis (DEA) method is a non-parametric approach that uses mathematical programming to esti-mate production frontiers and calculus efficiency scores. The above technical explanation is necessary, as the present seminar paper deals with the application of the DEA approach in the field of the public transport. The objective of this paper is to review the state of the art in performance benchmarking in terms of different DEA-based framework and criteria to measure efficiency in the environments of public transport. To contribute to this goal, the ambition is to provide a systematic analysis of the performance criteria of the DEA models. Consequently, the main focus of this paper is to examine and classify the performance criteria.
Download or read book Modeling Performance Measurement written by Wade D. Cook and published by Springer Science & Business Media. This book was released on 2006-06-03 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume addresses advanced DEA methodology and techniques developed for modeling unique new performance evaluation issues. Many numerical examples, real management cases and verbal descriptions make it very valuable for researchers and practitioners.
Download or read book Benchmarking Economic Efficiency written by Jesús T. Pastor and published by Springer Nature. This book was released on 2022-07-12 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book unifies and extends the definition and measurement of economic efficiency and its use as a real-life benchmarking technique for actual organizations. Analytically, the book relies on the economic theory of duality as guiding framework. Empirically, it shows how the alternative models can be implemented by way of Data Envelopment Analysis. An accompanying software programmed in the open-source Julia language is used to solve the models. The package is a self-contained set of functions that can be used for individual learning and instruction. The source code, associated documentation, and replication notebooks are available online. The book discusses the concept of economic efficiency at the firm level, comparing observed to optimal economic performance, and its decomposition according to technical and allocative criteria. Depending on the underlying technical efficiency measure, economic efficiency can be decomposed multiplicatively or additively. Part I of the book deals with the classic multiplicative approach that decomposes cost and revenue efficiency based on radial distance functions. Subsequently, the book examines how these partial approaches can be expanded to the notion of profitability efficiency, considering both the input and output dimensions of the firm, and relying on the generalized distance function for the measurement of technical efficiency. Part II is devoted to the recent additive framework related to the decomposition of economic inefficiency defined in terms of cost, revenue, and profit. The book presents economic models for the Russell and enhanced graph Russell measures, the weighted additive distance function, the directional distance function, the modified directional distance function, and the Hölder distance function. Each model is presented in a separate chapter. New approaches that qualify and generalize previous results are also introduced in the last chapters, including the reverse directional distance function and the general direct approach. The book concludes by highlighting the importance of benchmarking economic efficiency for all business stakeholders and recalling the main conclusions obtained from many years of research on this topic. The book offers different alternatives to measure economic efficiency based on a set of desirable properties and advises on the choice of specific economic efficiency models.
Download or read book Data Envelopment Analysis written by Wade D. Cook and published by Springer. This book was released on 2014-07-08 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
