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Slack based measure (SBM) model of Data Envelopment Analysis (DEA) is very effective to evaluate the relative efficiency of decision making units (DMUs). It deals with the directly input excess and output shortfall to assess the effect of slacks on efficiency with common crisp inputs and outputs. In some cases, input and output data of DMUs can't be precisely measured, so, the uncertain theory has played an important role in DEA. In these cases, the data can be represented as linguistic variable characterized by fuzzy numbers. This paper attempts to extend the traditional DEA model to a fuzzy framework, thus proposing a fuzzy SBM DEA model based on possibility approach to deal with the efficiency measuring problem with the given fuzzy input and output data. Finally, numerical examples are presented to illustrate the proposed fuzzy SBM model. By extending to fuzzy environment, the DEA approach is made more powerful for application. [ABSTRACT FROM AUTHOR]

The present study is an attempt to provide an overview of the general status of the public sector hospitals of Uttarakhand, in terms of their productive efficiencies. The paper applies slack base model (SBM) for the measurement of efficiencies and slacks. On the basis of the status of the overall technical efficiency, it concludes that the performance of hospitals is not satisfactory and is far away from the optimal level. The average overall technical efficiency 54.10 % indicates that an average hospital has the scope of producing the outputs with the inputs 45.90 % lesser than their existing levels. The slack analysis results show that on average 12.57 % of beds, 13.16 % of doctors, 14.04 % of paramedical staff can be reduced and 17.53 % of out-door patients, 66.55 % of in-door patients, 208.23 % of major surgeries, 110.73 % of minor surgeries can be expanded if all the inefficient hospitals operate at the level of efficient hospitals. [ABSTRACT FROM AUTHOR]

The assessment of software evolution in terms of quality poses significant challenges as different metrics have to be combined and normalized over the size of each examined version. Data Envelopment Analysis (DEA), a non-parametric technique from production economics, can offer a unified view of several design properties providing insight into global evolutionary trends. In this paper a set of practical guidelines for the application of DEA and the interpretation of the extracted results is proposed, with a focus on open source software, where limited information and documentation might be available. [ABSTRACT FROM AUTHOR]

In recent years, evaluating the region innovation activity has gained a renewed interest in both growth economists and trade economists. In this work, a two-stage architecture constructed by combining kernel principal component analysis (KPCA) and the data envelopment analysis (DEA) is proposed for evolution region innovation. In the first stage, KPCA is used as feature extraction. In the second stage, DEA is used to evolution region innovation efficiency. By examining the region innovation data, it is shown that the proposed method achieves is effective and feasible. And it provides a better estimate tool for the region innovation activity. It also provides a novel way for the evolution design of the other engineering. [ABSTRACT FROM AUTHOR]

This paper presents a new class of fuzzy expectation data envelopment analysis (FEDEA) models with credibility constraints. Since the proposed model contains the credibility of fuzzy events in the constraints and the expected value of a fuzzy variable in the objective, the solution process is very complex. Thus, in the case when the inputs and outputs are mutually independent trapezoidal fuzzy variables, we discuss the equivalent nonlinear forms of the programming model, which can be solved by standard optimization software. At the end of this paper, one numerical example is also provided to illustrate the efficiency of decision-making unites (DMUs) in the proposed model. [ABSTRACT FROM AUTHOR]

Chip resistor is widely applied in various kinds of electronic products nowadays. Almost as long as there are electronic products, chip resistor will be the existence with them. But extensive use of the market created a chip resistor industry expansive development. Because of competitors competing into the ranks of chip resistor manufacturing, leading to oversupply the market and caused strict competition. In order to survive, the same industries sacrifice getting profit and start a price war. And finally show operating losses of the state. To make products reduce costs in a competitive market is to hold competition advantage. This research as a individual example, based on the data envelopment analysis (Data Envelopment Analysis, referred to DEA), provide a set of systematic model to assess the each process between the input of manpower, working hours, fees and other manufacturing costs. And then to provide the best permutation combination of improvement, the purpose can be reducing manufacturing costs and also upgrade operational efficiency, and improve industry competitiveness. The results demonstrated that the proposed model can be applied to inter-industry analysis of the manufacturing cost and provide effective assessment, improvement and recommendations. [ABSTRACT FROM AUTHOR]

It becomes more and more difficult for a telecommunication company to retain a successful operational model in the highly competitive environment. In fact, a good performance evaluation method becomes a good management technique for bench marking among industry. This has become an important topic nowadays. The objective of this research is to provide an effective study to evaluate the telecommunication industry between China and Taiwan, as well as the analysis of efficiency and improvement suggestions for those companies which want to improve the efficiency based on Data Envelopment Analysis (DEA). Realistic data are collected from both China and Taiwan published stock market. Total major 5 companies, which are included around 90% market share, are collected. The results show that 3 companies have very good performances. Moreover, this study provides improvement suggestions for those companies, which performances are not good enough. This method and results are useful for telecommunication industry for management and bench marking between China and Taiwan. [ABSTRACT FROM AUTHOR]

This paper introduces clustering method to traditional Data Envelopment Analysis (DEA) in order to examine the performance of 982 branches of one big Canadian bank nation wide. This improved method can address the effects exerted by different operating environment. K-means, one of the most popular clustering techniques is used to cluster the branches into 8 clusters in order to make a fair comparison. The system differentiated DEA model used in the paper considers the systematic difference among different clusters. The potential management uses of the DEA results were also presented. All the findings are discussed in the context of the Canadian banking market. [ABSTRACT FROM AUTHOR]

In today's economy and society, performance analyses in the services industries attract more and more attention. This paper presents an evaluation of 240 branches of one big Canadian bank in Greater Toronto Area using Data Envelopment Analysis (DEA). Special emphasis was placed on how to present the DEA results to management so as to provide more guidance to them on what to manage and how to accomplish the changes. Finally the potential management uses of the DEA results were presented. [ABSTRACT FROM AUTHOR]

Crop production is a process of multiple inputs (water and nutrients, etc.), and the relationships between the inputs and crop yield are very complex. This study used a model for data envelopment analysis (DEA) to evaluate the efficiency of irrigation-fertilization schemes for winter wheat in North China. The field experiments were conducted at the Xiaohe Irrigation Experiment Station in Central Shanxi Province, China. Sixteen irrigation-fertilization schemes, the combinations of four levels of irrigation (irrigation volume from 0 to 300 mm) and four levels of fertilizer (0, low, moderate and high), were considered in the experiments. Experimental results revealed that irrigation and fertilization have significant impact on wheat yield and water use efficiency (WUE). For schemes without fertilization, wheat yield and WUE tend to be the lowest for all the irrigation levels and vary little with irrigation volume. With a specified irrigation volume, wheat yield and WUE tend to increase with fertilizer level. At a specified fertilizer level, wheat yield tends to increase with irrigation volume, while WUE is less influenced by irrigation volume. Among the sixteen schemes, ten were evaluated to be DEA efficient or nearly DEA efficient. The results indicated that proper combination of irrigation and fertilization is necessary for efficient use of water and fertilizer. Low fertilizer level with no irrigation and low, moderate or high fertilizer levels with more irrigation volume are generally effective for winter wheat production. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) is an effective method for measuring the relative efficiency of a set of homogeneous decision-making units (DMUs). However, the data in traditional DEA model are limited to crisp inputs and outputs, which cannot be precisely obtained in many production processes or social activities. This paper attempts to extend the traditional DEA model and establishes a DEA model with type-2 (T2) fuzzy inputs and outputs. To establish this model, we first propose a reduction method for T2 fuzzy variables based on the expected value of fuzzy variable. After that, we establish a DEA model with the obtained fuzzy variables. In some special cases such as the inputs and outputs are independent T2 triangular fuzzy variables, we provide a method to turn the original DEA model to its equivalent one. At last, we provide a numerical example to illustrate the efficiency of the proposed DEA model. [ABSTRACT FROM AUTHOR]

Chapter 22 of the book "Global Cases on Hospitality Industry" is presented. It focuses on the use of data envelopment analysis (DEA) to evaluate the performance of the worldwide hotel industry. The research has shown a possible improvement in terms of efficiency, with a 30 to 40 percent reduction in the inputs without decreasing the outputs. It is observed that companies that concentrate on their core businesses have better performance than those who are diversified.

Control charts are widely implemented in firms to establish and maintain statistical control of a process which leads to the improved quality and productivity. Design of control charts requires that the engineer selects a sample size, a sampling frequency and the control limits for the chart. In this paper, a possible combination of design parameters is considered as a decision making unit which is identified by three attributes: hourly expected cost, detection power of the chart and in-control average run length. Optimal design of control charts can be formulated as multiple objective decision making (MODM). We have extended cost function from single to multiple assignable causes to near the model to the real situations. An algorithm using DEA is applied to solve the MODM model. A numerical example is used to illustrate the algorithm procedure. [ABSTRACT FROM AUTHOR]

The 10-year National Plan for Energy Technology Development established in 1997 has now expired. To this end, the Korean government must now establish a new strategic ten-year plan that will cover the period from 2006 through 2015. In this paper, we prioritize the relative weights of energy technologies in terms of the national greenhouse gas plan using the AHP/DEA hybrid model. This model, which is composed of the analytic hierarchy process and data envelopment analysis, represents one of the multi-criteria decision making (MCDM) methods. In order to facilitate decision-makers and energy policy makers tasks in conjunction with the formulation of national decisions and energy policies, this study introduces a scientific procedure which can be used to measure the relative efficiency and priorities of various greenhouse gas technologies. [ABSTRACT FROM AUTHOR]

In this paper, we present a slacks-based and additive-based measure (SBM-ADD) of efficiency in context-dependent data envelopment analysis, called the SBM-ADD context-dependent DEA. In this proposed measure, we use the concept of the additive model developed by Charnes et al. (2000), which combines input-oriented and output-oriented models and the SBM proposed by Tone (2001), which evaluates the efficiency based on the slack values. The SBM-ADD context-dependent DEA takes into account of input slacks and output slacks in the objective function, and provides sharper attractiveness and progress scores for measuring the DMUs performance. A comparison among the CCR context-dependent DEA by Seiford and Zhu (2003), the SBM context-dependent DEA by Morita et al. (2005), and the SBM-ADD context-dependent DEA is made using a 32-printer benchmark data. The results show that SBM-ADD is able to provide a more appropriate stratification of the DMU performance levels than other two models. [ABSTRACT FROM AUTHOR]

Job Scheduling in high performance computing (HPC) clusters and grids has traditionally been performed by job entry and management sys tems, such as the Portable Batch System that place their emphasis on job management and only to a lesser extent on job scheduling. In grid infrastruc tures and emerging, virtual machine-based HPC environments, the previous assumption on relative homogeneity of nodes does not hold any more. In con trast, loosely coupled nodes in these settings are more heterogenous than ev er. This places new demands on job scheduling, where a large number of dif ferent nodes create the problem of optimally laying out compute jobs across the network for efficient resource allocation. The proposed approach present ed utilizes non-parametric Data Envelopment Analysis (DEA) to derive a workload-type proximity factor for a given node type. An experimental fac tor determination is performed using 5 physical and one virtual nodes. [ABSTRACT FROM AUTHOR]

Nothing I wish for more than to be Liberated from all Concerns in the Indies. Absentee plantation ownership has been much criticised for its deleterious social effects and productive inefficiency. The economic case against absenteeism was founded on arguments first advanced by Adam Smith. Slavery was one of the examples used by Smith to illustrate his theories of monitoring and incentives. A slave, he wrote, was a ‘person who can acquire no property, can have no other interest but to eat as much and labour as little as possible’. While systems of coercion and control might succeed in preserving the profitability of enslavement, such an institution could never be efficient. Agency problems are created whenever a conflict of interest arises between an owner and the overseer of a business, and when the costs of monitoring the overseer's behaviour are high. West Indian estates were located thousands of miles away from Britain and communications were very slow by modern standards (a letter sent out to the colonies might take up to two months to be delivered). White managers of absentee estates possessed powers of coercion over enslaved labourers; observing the daily conduct of such overseers was well-nigh impossible. Smith's criticism of slavery argued that managerial failures compounded a slave's inherent lack of incentives. In consequence, agents were well placed to defraud distant grandee employers, more concerned with status-enhancing projects of conspicuous consumption than with scrutinising the cost schedules of their estates. [ABSTRACT FROM AUTHOR]

This chapter discusses the use of nonparametric productivity analysis in measuring and comparing the relative performance of production units. The basic concepts of productivity analysis and two popular methods, Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH) model are reviewed. An example from the empirical study of Scheel (1999) is considered in order to illustrate the practical application of DEA. This concrete data analysis is about the efficiency of 63 agencies of a German insurance company. In order to illustrate how FDH works, the Manufacturing Industry Productivity Database from the U.S. National Bureau of Economic Research is discussed.

The purpose of this study is to propose Data Envelopment Analysis (DEA) as an effective tool to measure labor productivity of hotels. Using the data collected from the hotels in the State of California, the study applies DEA to calculate the labor productivity score of each sampled hotel. The internal and external determinants of labor productivity are examined. Implications of the study's results are also discussed. [ABSTRACT FROM AUTHOR]

Conventional approaches to assessing unit-level productivity, such as labor-cost percentages or basic ratio analysis including sales per labor hour, are limited in utility because they integrate too few operational characteristics to portend true operational efficiency. Moreover, current parametric approaches impose a functional form relating independent variables uniformly to dependent variable(s) and provide only an average by which other operations are compared. Data envelopment analysis (DEA), a linear-programming-based benchmarking technique that explicitly considers weighted outputs and inputs, is introduced as an alternative. DEA does not require any assumptions about functional form and calculates a maximal performance measure for all units in the population. As an exploratory investigation, data from 38 same-brand midscale restaurants were analyzed. Results, which include relative-to-best efficiency valuations, suggest that data envelopment analysis offers considerable potential for managers looking to accurately assess productivity. The viability of key variables as part of the DEA application is also discussed. [ABSTRACT FROM AUTHOR]

This paper introduces Data Envelopment Analysis (DEA) for the evaluation of inefficiencies in tourism advertising programs and the identification of optimal comparison partners for benchmarking. The implementation of DEA for benchmarking tourism destinations is demonstrated by assessing state tourism advertising programs in the United States. This evaluation includes information on the advertising budgets of state tourism offices, the allocation of market effort in international and domestic segments, and the number of visitors and expenditures generated in the various destinations. A proximity measure was used as an exogenously fixed input variable in order to reflect differences in domestic market size. Findings include efficiency scores for state tourism offices offering several possibilities for managerial implications. Furthermore, the concept of a virtual reference destination assisting managers to analyze their individual strength and weaknesses is introduced. Finally, a discussion of the potential and limitations of DEA for benchmarking of tourism destinations is provided. [ABSTRACT FROM AUTHOR]

This chapter uses windows and cone ratio analysis -- a longitudinal and weight- restriction application of Data Envelopment Analysis (DEA) -- to develop a methodology for analyzing organizational performance of community mental health centers (CMHCs); the chapter also develops measures of efficiency as a basis for improving productivity in behavioral health care. Specifically, non-hospital services provided by CMHCs were studied. Data limitations are noted in relation to use of the method and to the results. The model is shown to capture the impact of managed care on CMHC efficiency. The cone ratio version of the model, using weight restrictions, identified six super-efficient CMHCs, which had been consistently efficient since the implementation of managed behavioral care. The potential usefulness of this method for public and private mental health systems and for managed care companies is discussed. [ABSTRACT FROM AUTHOR]

Elective surgery typically generates 40 percent or more of a hospital's total revenue, and individual surgeons almost always have a net positive contribution margin. Perioperative services include surgical operations, preoperative care of patients, and post-operative care. This chapter presents a method to identify best practices among hospitals' perioperative services using Data Envelopment Analysis (DEA). This analysis included 44,033 procedures performed by 3,502 surgeons at 53 non-metropolitan Pennsylvania hospitals. Eight procedures, each performed by one surgical specialty, were selected. For each hospital, DEA 1) identifies untapped markets for surgery; 2) identifies relatively high and low procedure volumes among specialties; and 3) suggests a strategy for increasing surgical volume for inefficient hospitals. Findings may be used by managers of perioperative services to aid in resource allocation decisions, such as hiring and recruitment among different surgical specialties. [ABSTRACT FROM AUTHOR]

The article presents an encyclopedia entry for fractional programming. Fractional programs are constrained ratio optimization problems, which may involve more than one ratio in the objective function. These programs may also arise in the process of solving other optimization problems involving no ratios. The term is cross-referenced to data envelopment analysis, linear programming and quadratic programming.

An encyclopedia entry that discusses data envelopment analysis is presented. It refers to data oriented approach for evaluating the performance of a collection of entities called decision making units which are regarded as responsible for converting inputs into outputs. The history of the topic, description of relevant applications, overview of present and future trends, and a list of references are provided. The term is used in operations research and management science.

The article presents an encyclopedia entry for banking. Operations research and management science techniques find applications, such as the use of data-driven models to measure the operating efficiency of bank branches through data envelopment analysis, in numerous and diverse areas of operation in a banking institution.