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Some phenomena pertaining to rarefied gases are beyond the reach of traditional fluid dynamics described, e.g., by the Euler or Navier–Stokes–Fourier equations. Therefore we adopt a recently developed model—referred to as the CCR model—to investigate thermally-induced transport in rarefied gases. To this end, the method of fundamental solutions is employed on the CCR model to investigate two problems: (i) a rarefied gas flow confined between two coaxial cylinders having different temperatures with the inner cylinder being circular while the outer being elliptical, and (ii) evaporation/condensation process in a rarefied vapor confined between two coaxial cylinders, again with the inner cylinder being circular and the outer being elliptical. Through a comprehensive analysis, the efficiency of the method of fundamental solutions is assessed. The work contributes toward a better understanding of thermally-induced confined rarefied gas flows. [ABSTRACT FROM AUTHOR]

Innovation and entrepreneurship are essential for higher vocational students to escape low-end employment and are vital for vocational education to provide diverse products and services, fulfilling the people’s demand for a better life. This study builds on the theory of innovation and entrepreneurship education, integrating information technology to devise the “Four-Drive-One-Guide” model for vocational colleges. Utilizing Province A as a case study, a survey was conducted to gather data on the effectiveness of this education model, analyzed using ANOVA, Pearson’s correlation coefficient, and multiple linear regression. Furthermore, the operational efficiency of innovation and entrepreneurship education across 30 Chinese regions was assessed using the CCR model within the DEA framework. Findings reveal that the “Four-Drive-One-Guide” model significantly boosts students’ innovative and entrepreneurial capabilities, with an average rating of 4.06. The most influential factor in its effectiveness is students’ attitudes, with a coefficient of 0.238. Moreover, vocational colleges in the eastern region exhibit the highest comprehensive efficiency at 0.875. The study suggests that integrating industry teaching and optimizing the curriculum can further enhance students’ innovative and entrepreneurial thinking.

Improving the quality of preschool education management is the basic guarantee of national talent training. In this paper, the data envelopment analysis of resource allocation efficiency of preschool education is conducted by analyzing the characteristics of preschool education and the allocation process of educational resources. Based on the original input and original output, the productivity of preschool education is analyzed by combining different environmental variables in the CCR model. The asymptotic approximation method was used to improve the fit of the initial data and to speed up the convergence of the fit by weighting. Based on the study of preschool education in County M, kindergartens with resource allocation at a high level ( 0.8≤ θ

Neutrosophic data envelopment analysis (Neu-DEA) is a mathematical tool for calculating the performance of decision-making units (DMUs) in a neutrosophic environment. In this paper, a novel ranking function is developed specifically for single-valued trapezoidal neutrosophic numbers (SVTrNNs). The properties of this new ranking function have also been extensively studied. We develop the Charnes–Cooper–Rhodes models in the context of SVTrNNs to measure the efficiency of homogeneous DMUs. Additionally, we propose a unique solution process by incorporating the newly developed ranking function, which allows for the conversion of the neutrosophic DEA model into a corresponding Crisp LP model. This approach offers an efficient and effective tool of measuring the DMU efficiency in a neutrosophic environment. The reference set or peer group is defined for inefficient DMUs, which enables them to improve their efficiency score by following their peers. Two different approaches are suggested as potential ways to completely rank the DMUs, i.e., the reference set- and the super-efficiency-score-based ranking approaches. The validity and existence of the proposed models are demonstrated by providing an illustrative example, and the results are compared to an existing approach. The proposed Neu-DEA model is employed to assess the efficiency of the 12 major seaports in India, and it yields superior outcomes compared to the currently existing models. [ABSTRACT FROM AUTHOR]

The aim of this study is to solve the problem of increasing the efficiency of fuel and energy complex enterprises. Because such enterprises are complex systems, it is difficult to optimize their work, taking into account all the technical indicators of such enterprises. This study proposes to solve this problem by defining an algorithm using the data envelopment analysis (DEA) method. In particular, the algorithm was applied in heating systems using the example of a combined heat and power plant, where the DEA method had not previously been used. Experiments were carried out to improve the efficiency of the combined heat and power plant. Efficiency indicators were calculated, changing inputs and outputs of the model according to the study case to achieve the maximum efficiency of the system. The Charnes; Cooper and Rhodes; and the Banker, Charnes, and Cooper models were tested with good results. The presented methodology and experimental results enabled the DEA method to be applied for the first time to improve the efficiency of fuel and energy companies. [ABSTRACT FROM AUTHOR]

The main reason for this research is to analyze the Polish banking systems with Data Envelopment analysis and its sub-models, to measure efficiency, and then to compare the banks of both countries separately and together, according to the results of the analysis. In this study, the measurement of the efficiency of all 19 banks operating in Poland between 2016-2022 was investigated with CCR and BCC models of an input-oriented the Data Envelopment Analysis. According to the analysis result, efficient and inefficient banks were identified and compared, and potential improvement suggestions were developed for inefficient banks. It has been observed that the efficiency of the banking system has estimated to increase linearly over the years. Results of efficient banks of Poland have been compared and recommended as benchmarks and potential improvement suggestions for inefficient banks. [ABSTRACT FROM AUTHOR]

Copyright of Exacta is the property of Exacta - Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study is to solve the problem of increasing the efficiency of fuel and energy complex enterprises. Because such enterprises are complex systems, it is difficult to optimize their work, taking into account all the technical indicators of such enterprises. This study proposes to solve this problem by defining an algorithm using the data envelopment analysis (DEA) method. In particular, the algorithm was applied in heating systems using the example of a combined heat and power plant, where the DEA method had not previously been used. Experiments were carried out to improve the efficiency of the combined heat and power plant. Efficiency indicators were calculated, changing inputs and outputs of the model according to the study case to achieve the maximum efficiency of the system. The Charnes; Cooper and Rhodes; and the Banker, Charnes, and Cooper models were tested with good results. The presented methodology and experimental results enabled the DEA method to be applied for the first time to improve the efficiency of fuel and energy companies.

In this study, Data Envelopment Analysis (DEA) models are improved by employing spherical fuzzy sets (SFSs), which is an extension of generalized fuzzy sets. SFSs were recently introduced as a novel type of fuzzy set that allows decision-makers to express their level of uncertainty directly. As a result, SFSs provide a more preferred domain for decision-makers. Fundamental Charnes-Cooper-Rhodes (CCR) model is discussed on the context of spherical trapezoidal fuzzy numbers (STrFNs), which consider each data value’s truth, indeterminacy, and falsehood degrees, and a unique solution technique is implemented. This method converts a spherical fuzzy DEA (SF-DEA) model into three pair of crisp DEA model, which may then be solved using one of many existing approaches. The largest optimal interval is determined for each DMU such that the efficiency score lies inside that interval. Furthermore, an example demonstrates this novel method and clearly explains the DMUs’ ranking technique. [ABSTRACT FROM AUTHOR]

This paper surveys and critically evaluates the literature on the use of advanced methods to assess the financial effectiveness of insurance entities. The paper presents methodological assumptions for Data Envelopment Analysis (DEA) using the CCR (Charnes-Cooper-Rhodes) and BCC (Banker-Charnes-Cooper) models. The usefulness of these methods for assessing the financial efficiency of insurance companies was also shown on the example of entities conducting insurance activities in Nigeria, Malaysia, Singapore, Indonesia, Serbia, Poland and Slovakia. [ABSTRACT FROM AUTHOR]

This paper examines the applicability of DEA (Data Envelopment Analysis) to measure and evaluate the efficiency of materials management at the regional level. The research has been conducted for Polish regions as a case study. The basis for the calculation of the efficiency scores was a statistically selected set of materials used in a given region and the Gross Domestic Product (GDP). The results of the analysis reveal that 4 (Łódzkie, Śląskie, Warmińsko‐Mazurskie, and Zachodniopomorskie) out of 16 Polish regions are relatively efficient. The remaining regions consume too many material resources in the process of generating goods and services. [ABSTRACT FROM AUTHOR]

As there are many indexes for evaluating technological innovation in enterprises, it is hard to quantify all those indexes. Therefore, common evaluation methods cannot be applied to solve the absolute value of the evaluation indexes. Therefore, this study used the nonparametric CCR model based on input-output to estimate the relative value of evaluation index, and took dual programming tool to obtain the judgment basis for the most effective and optimal solution. Based on the software evaluation criteria, this paper proposed the concept of "maturity in technological innovation, " its four levels, and an evaluation standard for maturity. Based on the homogeneity, the paper selected four Beijing enterprises as evaluation samples. After comparing and analyzing the efficiency, scale return, production surface projection and maturity, we found that the evaluation results conform to the reality of sampling enterprises. CCR model was used to evaluate decision-making units with multiple inputs and outputs. The results show that this method can help accurately obtain the relative order and the enterprises' ability to make technological innovation. Thus, CCR model is able to help enterprises formulate policies on technological innovation. [ABSTRACT FROM AUTHOR]

Data envelopment analysis has been widely used for performance evaluation in sectors such as banking, health, education in recent years. In this study, data envelopment analysis, one of the non-parametric efficiency analysis methods, has applied in order to determine the efficiency values of the departments operating within Samsun Ondokuz Mayıs University Training and Research Hospital. Analyzes have performed using input and output oriented Charnes-Cooper-Rhodes and Banker-Charnes-Cooper models. In this regard, 27 departments with outpatient clinics with services for active and inpatients, which serve for 11 months, including January and November, have included in the scope of the study. The current data set has analyzed using two different models (Charnes-Cooper-Rhodes and Banker-Charnes-Cooper) and four different sub-models connected to these models (input oriented Banker-Charnes-Cooper, output oriented Banker- Charnes-Cooper, input oriented Charnes-Cooper-Rhodes and output oriented Charnes-Cooper-Rhodes), and the efficiency values of the departments were revealed. As a result, 11 departments are found to be active in all four models examined. [ABSTRACT FROM AUTHOR]

Maize cultivation performance, including the efficiency of the input and output of maize, which reflect the allocation and utilization of resources in the process of maize cultivation, is crucial for evaluating and improving maize cultivation. This paper adopts the method of quadratic regression orthogonal rotation combination experimental design to explore the effects of four main cultivation measures (planting density, nitrogen fertilizer, phosphorus fertilizer and potassium fertilizer) on maize yield at five levels (−2, −1, 0, 1; 2). The CCR (A. Charnes, W. Cooper and E. Rhodes) model, which is the basic model of data envelopment analysis (DEA), was used to evaluate the 36 groups of cultivation measures. The results show that 9 groups are CCR-effective cultivation measures, but the performance of these cultivation measures cannot be further evaluated. To improve the evaluation of cultivation performance, a novel method termed as the group decision method of DEA (GDM-DEA) is proposed to detect the improvement of evaluation performance and is tested using the measurements of maize cultivation. The results suggest that the GDM-DEA method can classify and sort the performance of all the cultivation measures, which is more sensitive and accurate than the CCR method. For the effective cultivation measures that meet the requirements of GDM-DEA, the optimal cultivation measures could be determined according to the ranking of yield. This method determined the most effective cultivation measure. Further independent validation showed that the final optimal cultivation measures fall in the range of the expected cultivation measures. The GDM-DEA model is capable of more effectively evaluating cultivation performance.

Dünya günden güne gelişerek değişmektedir. Bu değişimle beraber rekabet iyice yoğunlaşmıştır. Rekabetin yoğun olduğu bir ortamda kaynaklarını en iyi kullanan örgütler varlıklarını sürdürebilmektedirler. Kullandıkları girdiler ile en büyük çıktı seviyesini elde edip etmemesi performans değerleme açısından önem taşımaktadır. Tüm sektörlerde olduğu gibi işletmelerin etkin bir şekilde çalışmaları otomotiv sektöründe de büyük önem taşımaktadır. Bu çalışmada, Türk sanayisinin başat sektörlerinden olan otomotiv sektörünün etkinlik değerleri hesaplanarak sektöre ilişkin performans sonuçları elde edilmeye çalışılmıştır. Etkinlik analizlerinde parametrik olmayan yöntemlerden biri olan veri zarflama analizine göre CCR modeli ve Malmquist toplam faktör verimlilik endeksi kullanılmıştır. VZA, çok sayıda girdi ve çıktıya sahip karar birimlerinin etkinliklerini ölçen doğrusal programlama tabanlı bir tekniktir. VZA durağan bir analiz iken Malmquist toplam faktör verimlilik endeksi dinamik bir analizdir. Malmquist toplam faktör verimlilik endeksi zaman içerisinde karar verme birimlerinde meydana gelen değişimlerin ölçülmesinde kullanılan bir yöntemdir. Analiz DEAP 2.1. Data Envelopment Analysis Program paket program kullanılarak yapılmıştır. Çalışmada 2015-2018 yılları baz alınarak bu dönemde kesintisiz olarak 16 işletmeye ait veriler kullanılmıştır. Analizde girdi olarak toplam aktifler, öz sermaye ve çalışan sayısı kullanılmıştır. Çıktı değişkeni olarak ise ciro ve net kar verileri kullanılmıştır. Analiz sonuçlarına göre, tüm yıllarda etkin olan iki firma var iken analiz dönemi boyunca etkinlik gösteremeyen dokuz firma olmuştur. Gözlem kümesindeki otomotiv firmalarından 2015 yılında 6 firma, 2016 yılında 4 firma, 2017 yılında 3 firma etkinlik gösterirken analizin son yılı olan 2018 yılında ise 4 firma etkin olabilmiştir. Yıllar itibariyle ortalama etkinlik derecelerinde düşüş görülmüştür. Ortalama etkinlik derecesi en yüksek yıl analizin ilk yılı olan 2015 iken, etkinlik derecesi en düşük olarak gerçekleşen yıl ise analizin son yılı olan 2018 olmuştur. Malmquist Toplam Faktör Verimliliği Endeksi değerleri ise gözlem kümesindeki 16 firmanın ortalama endeks değerlerini yıllara göre kıyaslamaktadır. Buna göre 2016 yılında düşük oranda da olsa bir düşüş yaşanırken, 2017 yılında 2016 yılına göre ve 2018 yılında da 2017 yılına göre artış görülmüştür

One of the most serious principles in production theory in economic is the principle of "efficiency". Simply put, efficiency can be defined as the demand that the desired goals (outputs) are achieved with the minimum use of the available resources (inputs). In order to, distinguish the relative efficiency of organizational units with multiple inputs to produce multiple outputs, "Data Envelopment Analysis" (DEA) method was introduced by Charnes, Cooper and Rhodes. In fact, DEA is a linear mathematical programming which calculates the efficiency of an organization within a group relative to observed best practice within that group. Unlike common statistical analysis which are based on central tendencies, it is a methodology directed at the frontier. Recently, DEA has become one of the most favorite fields in operations research. The background was a motivation for us to in this paper, via running the CCR model in "DEA-Solver Software", present data envelopment analysis from simulation on the lattice QCD with temporal extent N_τ=4,6, respectively. Astonishingly, results are derived for both cases, indicating the fact that efficient data set belong to the areas of high temperature (deconfinement phase). It is very interesting to highlight that even an efficient data has not reported at low temperature (confinement phase). Note that the data obtained at the critical temperature is also efficient. As expected from practical lattice QCD, the DEA-CCR model presented in this paper also confirms the fact which the best data set arises from simulation in continuum limit a→0. Indeed, by taking the limit of vanishing lattice spacing, the efficiency of algorithms can be further.

This paper considers an algorithmic approach to sensitivity in Data Envelopment Analysis for the CCR and Additive models. Specifically, it gives sufficient conditions that preserve the efficiency of a decision-making unit (DMU) under arbitrary perturbations of the inputs and/or outputs of the DMUs. The paper illustrates the results for the Additive model. [ABSTRACT FROM AUTHOR]

The aim of this paper is to estimate the efficiency of public healthcare expenditures using Data envelopment analysis. We propose two equivalents of DEA models. The first is based on per capita type of variables (health expenditures per capita, healthy years of life and preventable deaths per million people) and second equivalent accumulates all the health expenditures for last 10 years (PPP US dollars in 2011 prices), aggregates healthy years and preventable deaths of population in given country and year. Slovakia has one of the least efficient healthcare systems among EU countries, while Cyprus and Bulgaria seem to be efficient under all specifications of the models. Results from DEA analysis suggest considerable space for improving in Slovakia. Slovakia would need to reduce health expenditure per capita and number of preventable deaths by more than half while keeping the same level of health life years per capita to become efficient. We also briefly looked at the evolution of efficiency in time, since 2011. However, we suggest, that more sophisticated analysis (e.g. Malmquist index) is needed. [ABSTRACT FROM AUTHOR]

Copyright of Selcuk University Social Sciences Institute Journal is the property of Selcuk University Social Sciences Institute Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Iran is one of the Middle East's developing countries, with a per capita GDP that ranks among the upper middle countries, according to international reports. On the other hand, according to research, the development of e-government in a country is directly tied to that country's economic status. Despite its economic strength, Iran is not well-positioned in the sphere of information and communication technology (ICT), with undesirable development of e-government and ICT infrastructure. The performance of Iranian provinces in the field of ICT development is analyzed in this study utilizing the DEA-CCR model, the Malmquist productivity index (MPI), reciprocal efficiency technique and k-means clustering. The main contribution of this study is that it aids policymakers and top managers by identifying poorly performing provinces, to make thorough preparations to strengthen them, and implement suitable policies and strategies. Indeed, by supporting and developing the weak provinces in the field of ICT, the overall ICT status of the country will improve. • In order to assess the digital divide in Iran, the state of ICT development in Iran's provinces during a nine-year period was investigated by the DEA-CCR model, the Malmquist productivity index (MPI), the reciprocal efficiency technique and k-means clustering. • The efficient and inefficient provinces in the development of IDI index were identified based on the provincial population and budget through DEA-CCR model and Malmquist Index. • For each province, the level of inefficiency in each sub-index of IDI was determined through DEA-CCR model and reciprocal efficiency technique. • The budget of each province was analyzed by k-means clustering. [ABSTRACT FROM AUTHOR]

The research on the banking efficiency all around the world has been one of the main topics for the international financial sectors over the last years. The special case is in Europe. Some of the countries are in the European Union. The European Commission creates the rules for safer and sounder financial sector in these countries. In the past, these rules brought a lot of controversy whether they help to all countries in the European Union or just some of them. The purpose of this article is to determine the development of different types of efficiencies for banking industry in the Visegrad Group. Generally, the development is measured by the Malmquist approach. Different type of index is used in this article, more precisely the Hicks-Moorsteen Total Factor Productivity index. It is one of the alternative indexes. The results have showed that the model with the variable return to scale assumption is better for the use in banking industry in the Visegrad Group, as this model is more precise about the results.

The reliability of CNC lathe was allocated based on the failure information of CNC lathe. It used Edgeworth series method to expand the fault data into standard normal variable expansion to obtained the reliability. Tested with data fitting method,the distribution curve of Edgeworth was well resembled. To obtain subsystem reliabilities,the Edgeworth series method was introduced. Concentrating three kinds of influence factors from the perspective of fault information,the allocation model based on Date Envelopment Analysis（ DEA） was proposed. Based on failure information of CNC lathe,this method was considerably practical to improve the redistribution of the machine’s reliability.

Since Charnes, Cooper, and Rhodes introduced data envelopment analysis (DEA) in 1978, later called the DEA-CCR model, many studies applied this technique to different fields. Based on the original CCR model, many modified DEA models were developed by researchers. Since 1999, Seiford and Zhu presented a two-stage DEA model. Later, these models were widely used in many studies. However, the relationship between the efficiency scores that are obtained from the original CCR model and the two-stage DEA model remains unknown. To fill this gap, this study proposed a theoretical relationship between the efficiency scores that are calculated from the two-stage DEA model and those that are obtained from the original CCR model. How the sets of nonsymmetrical weights affected the efficiency scores were also investigated. Theorems regarding the relationship were developed, and then the model was utilized to evaluate the two-stage efficiency scores of the insurance companies (non-life) and bank branches. The results show that using a two-stage DEA model can get more information about operational efficiency than the traditional CCR model does. The findings from this study about the two-stage DEA technique can provide significant reasons for using this model to evaluate performance efficiency.

In 2003, the process of public universities evaluation began. For this purpose, a set of performance indicators constructed by the Public University System (SUE by its acronym in Spanish) in alliance with the Ministry of National Education (MEN) was used. In an effort to know about the research efficiency level that public universities had in the period 2003-2012, an analysis of the results of these indicators was executed using Data Envelopment Analysis. In particular, the product-oriented CCR model was applied. Although many universities have experienced a sustained development in some of the indicators analyzed and show high relative levels of efficiency, the results show that, as a whole, the Public University System has still much to improve regarding its scientific mission, especially, those aspects related to graduate programs and scientific journals.

Copyright of Journal of International Social Research is the property of Journal of International Social Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bank ratings are integral elements of information infrastructure that ensure sound development of the banking business. One of the key issues that the clients of banking structures are worried about is the issue of identification of the degree of reliability and trust to the bank. As of now there are no common generally accepted methods of bank rating and the issue of bank reliability is rather problematic. The article considers a modern DEA method of economic and mathematical analysis which is a popular instrument of assessment of quality of services of different subjects and which became very popular in foreign econometric studies. The article demonstrates application of the data encapsulation method (data envelopment analysis, DEA) for obtaining new methods of development of bank ratings and marks out incoming and outgoing indicators for building a DEA model as applied to the Ukrainian banking system. The authors also discuss some methodical problems that might appear when applying component indicators for ranging the subjects and offer methods of their elimination.

This article examines the concept of eco-efficiency at a regional level as an approach to promote the sustainable transformation of regions, using the regions of Poland as an example. The data envelopment analysis (DEA) method-the input-oriented Charnes, Cooper, and Rhodes (CCR) model-was chosen as the eco-efficiency analysis tool because of its high capability to measure the regional eco-efficiency. The research process was divided into two stages. First, the chosen instruments of mathematical statistics (e.g., Hellwig's method and coefficient of determination) were applied to ensure an appropriate combination of environmental and economic indicators of the eco-efficiency equation. Next, the CCR model was used to calculate the eco-efficiency scores. The results of the study have revealed that the regions of Lubuskie, Mazowieckie, Śląskie, Warmińsko-Maurskie, and Wielkopolskie are relatively eco-efficient, whereas the remaining regions use too many environmental resources in relation to the produced value of goods and services. Six of the eleven eco-inefficient regions in Poland have increasing returns to scale, that is, the usage of natural resources connected with the negative impact upon the environment rises slower than the values of goods and services. Notwithstanding, it is beneficiary from the perspective of sustainability. The obtained research results are a valuable source of management information for the creation of regional environmental protection strategies and a basis for searching for the causes of eco-inefficiency. [ABSTRACT FROM AUTHOR]

Selection of industrial robots for the present day’s manufacturing organizations is one of the most difficult assignments due to the presence of a wide range of feasible alternatives. Robot manufacturers are providing advanced features in their products to sustain in the globally competitive environment. For this reason, selection the most suitable robot for a given industrial application now becomes a more complicated task. In this paper, four models of data envelopment analysis (DEA), i.e. Charnes, Cooper and Rhodes (CCR), Banker, Charnes and Cooper (BCC), additive, and cone-ratio models are applied to identify the feasible robots having the optimal performance measures, simultaneously satisfying the organizational objectives with respect to cost and process optimization. Furthermore, the weighted overall efficiency ranking method of multi-attribute decision-making theory is also employed for arriving at the best robot selection decision from the short-listed competent alternatives. In order to demonstrate the relevancy and distinctiveness of the adopted DEA-based approach, two real time industrial robot selection problems are solved.

This paper estimates the efficiency of the Czech commercial banks in the period 2001–2010 using the non-parametric Data Envelopment Analysis. We simultaneously use two alternative specifications – CCR model and BCR model – that differ in returns to scale assumption. Differences in estimated efficiency scores of individual banks are quite large up to 70 percentage points. Largest banks perform significantly worse than mid-size and small banks. This efficiency gap decreases if variable returns to scale are considered in the estimation. The average efficiency in the banking sector remained nearly unchanged during the analysed period. Although each year is estimated separately one can observe a deterioration of average efficiency during the recent crisis period.

This paper is the first attempt to analyze efficiency of building societies in the Czech Republic. We apply non-parametric method Data Envelopment Analysis on data from all building societies in the sector over the period 2002–2008. Having deposits received and administrative expenses as inputs and volume of loans disbursed as output we estimate efficiency scores of all individual building societies as well as calculate the average efficiency in the industry. For this purpose we use two alternative models that allows for constant and variable returns of scale respectively. The results suggest that there is no significant improvement in efficiency of building societies during the estimation period. Furthermore, most of the building societies have not been operating at appropriate size. We also found that Českomoravská stavební spořitelna, a. s. was the most efficient building society in the Czech Republic according to the both models applied. In order to increase efficiency, we suggest reduction in the number of external employees and agents or increase of their productivity, more sophisticated products that can outperform the standard services and effective response to changes in the legislature.

Introduction: Performance measurement, programming and goal setting for performance improvement are needed for organizations to improve their performance. Despite advancement in performance measurement systems, many organizations still emphasize on old models. Methods: This paper analyzes the efficiency of Yazd governmental hospitals by using DEA model from 2004 to 2006. The inputs in DEA model are 3 variables including number of physician, number of health personnel and number of beds. The outputs in DEA model are also 3 variables; number of in-patients, number of out-patients and number of bed days. Results: This paper results suggest that hospitals in Ardakan, Maybod, Khatam and Tabas Counties and only Afshar hospital in Yazd city are efficient. Inefficient hospitals include Savaneh Sookhtegi hospital of Yazd city and the hospital in Abarkooh County. Also, this paper determined the input and output targets of efficient and inefficient hospitals. For example, hospital in Taft County is efficient when number of inpatient increases to 54494, number of outpatients increases to 5225 and number of bed days increases to 21009 by output orientation model. Conclusion: Manager of hospitals can measure efficiency of hospital sections by using DEA models and plan for efficiency improvement, respectively.

In 2003, the process of public universities evaluation began. For this purpose, a set of performance indicators constructed by the Public University System (SUE by its acronym in Spanish) in alliance with the Ministry of National Education (MEN) was used. In an effort to know about the research efficiency level that public universities had in the period 2003-2012, an analysis of the results of these indicators was executed using Data Envelopment Analysis. In particular, the product-oriented CCR model was applied. Although many universities have experienced a sustained development in some of the indicators analyzed and show high relative levels of efficiency, the results show that, as a whole, the Public University System has still much to improve regarding its scientific mission, especially, those aspects related to graduate programs and scientific journals. [ABSTRACT FROM AUTHOR]

The slacks-based measure (SBM) model based on the constant returns to scale has achieved some good results in addressing the undesirable outputs, such as waste water and water gas, in measuring environmental efficiency. However, the traditional SBM model cannot deal with the scenario in which desirable outputs are constant. Based on the axiomatic theory of productivity, this paper carries out a systematic research on the SBM model considering undesirable outputs, and further expands the SBM model from the perspective of network analysis. The new model can not only perform efficiency evaluation considering undesirable outputs, but also calculate desirable and undesirable outputs separately. The latter advantage successfully solves the "dependence" problem of outputs, that is, we can not increase the desirable outputs without producing any undesirable outputs. The following illustration shows that the efficiency values obtained by two-stage approach are smaller than those obtained by the traditional SBM model. Our approach provides a more profound analysis on how to improve environmental efficiency of the decision making units. [ABSTRACT FROM AUTHOR]

The article summarizes the arguments and counterarguments in the scholarly discussion about the problem of choosing a model of healthcare organization. The study's primary goal was to identify the economic efficiency of the public health system and resistance to COVID-19. The relevance of addressing this research issue is that the epidemiological challenges posed by the pandemic worldwide have manifested themselves differently in various countries. Therefore, it is advisable to consider the effectiveness of public healthcare models and how they have worked out in the fight against COVID-19. Research in the work was carried out in the following logical sequence: conducting scientometric analysis of research, creation of a statistical research base for 22 countries of the world; construction of integral indices of the economic efficiency of the health care system; calculation of public health system resilience to the COVID-19 pandemic; application of frontier DEA analysis to determine system efficiency; comparison and analysis of the results of research on the economic efficiency of public health systems obtained by different methods. The article presents the results of a comparison of the economic efficiency of the public health system, which showed that the system built according to the Beveridge principle is the most resistant to the pandemic and, at the same time, has the highest indices of economic efficiency.

The task of this study is to valuate the investment efficiency of distribution companies. Although a series of publications and studies has been dedicated to this topic, it is difficult to find a general consensus in defining the investment efficiency of a company. Nevertheless if we simplify an imaginary company as a production unit in which a series of actions transforms inputs to outputs, efficiency can be understood as like an effort to achieve maximum value of the outputs together with minimum usage of inputs, where the inputs constitute investments by a company. The investment efficiency of a company can be measured by expressing the absolute values of selected inputs and outputs, a relative expression of inputs and outputs, and perhaps an expression of the difference between them. However, an examination of the efficiency of a certain company is impossible without a valuation of other companies. In view of the amount of benchmarking, it should be emphasized, that this study is dedicated to a certain category of benchmarking, which we may term investment benchmarking. This benchmarking can be defined as a comparison of companies in terms investment efficiency. The purpose of this comparison is not only to investigate levels of investment efficiency and to relate them to other companies from the same branch, but also to locate the greatest efficiency and indicate potential improvement.

Taguchi method is found efficient for optimising process performance with a single quality characteristic (QCH) of a product or process. In practice, however, customers are concerned about multiple QCHs, which are usually correlated. This research proposes and implements an approach using principal components analysis (PCA) and two data envelopment analysis (DEA) models, including CCR and super efficiency, for optimising multiple correlated QCHs in robust design. The PCA is first utilised to obtain multiple uncorrelated linear combinations of principal components, which are the same number of QCHs and hence avoid the loss of information by ignoring some principal components. Then, these components are utilised in two DEA models to decide optimal factor levels. Three real case studies are provided for illustration; in all of which the proposed approach is found more efficient than some other techniques in literature, including engineering judgement, PCA, PCA and grey analysis, and utility concept. In conclusion, the proposed approach shall provide a great assistance to process/product engineers for obtaining robust design with multiple correlated QCHs. [ABSTRACT FROM AUTHOR]

Abstract: The generic term ‘non-traditional machining’ (NTM) refers to a variety of thermal, chemical, electrical and mechanical material removal processes which have been developed due to lack of efficiency of the traditional machining processes to generate complex and intricate shapes in materials with ‘high strength-to-weight’ ratio. For effective utilization of the capabilities of different NTM processes, utmost care is needed for the selection of the most suitable process for a given machining application. Due to the lack of experienced experts in the domain of NTM processes, there is a need for a simple scientific/mathematical tool for selecting the most suitable NTM process when a particular shape feature is to be generated on a given work material. This paper focuses on the development of a two-phase decision model in this aspect. In the first phase, the most efficient NTM processes are selected for a given shape feature and work material combination having the best combination of performance parameters with the help of input-minimized-based Charnes, Cooper and Rhodes (CCR) model of data envelopment analysis (DEA). In the second phase, those efficient NTM processes are ranked in descending order of priority using the weighted-overall efficiency ranking method of multi-attribute decision-making (MADM) theory. Two real time machining applications are cited which prove the applicability, versatility and adaptability of this two-phase NTM process selection decision-making model as the results are quite consistent with those as derived by the past researches. [Copyright &y& Elsevier]

The main objective of this research is to identify and analyze the sources of technical inefficiency in turmeric crop farming system in north western region of Tamil Nadu from a sample of 180 turmeric growing farmers. A non-parametric approach, Data Envelopment Analysis (DEA) has been used to estimate Technical Efficiency Scores (TES). Results indicate the presence of technical inefficiency in turmeric farming system. The average technical efficiency score is 79 per cent with the maximum score of 95 per cent and minimum score of 59 per cent. The potential to increase the technical efficiency score of turmeric growing farms is found to be 17 per cent. [ABSTRACT FROM AUTHOR]

Enterprise managers and investors are constantly concerning about the future management efficiency of enterprises. This paper integrates GM(1,1) of grey theory into CCR model of data envelopment analysis to make CCR model become a model which can forecast the relative efficiency of decision making unit, in order to discuss the future performance development of a decision making unit. This paper takes a LED manufacturing company as an evaluation target to explain the operation process of this model. The CCR forecasting model constructed by this paper can be used as a tool for administrators to forecast the future management efficiency of a decision making unit. [ABSTRACT FROM AUTHOR]

In this paper, sensitivity analysis of the Charnes-Cooper-Rhodes model in data envelopment analysis (DEA) is studied for the case of perturbation of all outputs and of all inputs of an efficient decision-making unit (DMU). Using an approximate inverse of the perturbed optimal basis matrix, an approximate preservation of efficiency for an efficient DMU under these perturbations is considered. Sufficient conditions for an efficient DMU to preserve its efficiency are obtained in that case. An illustrative example is provided. [ABSTRACT FROM AUTHOR]