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1
Thi Vu, Loan, Nga Thu Nguyen, and Linh Hong Dinh. "Measuring banking efficiency in Vietnam: parametric and non-parametric methods." Banks and Bank Systems 14, no. 1 (2019): 55–64. http://dx.doi.org/10.21511/bbs.14(1).2019.06.
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The article aims to evaluate the business efficiency of commercial banks in Vietnam using both parametric and non-parametric approaches. In this study, the Stochastic Frontier Analysis (SFA), which belongs to a parametric method, and Data Envelopment Analysis (DEA), a non-parametric approach, are applied to a sample of 30 joint stock commercial banks in Vietnam in the period of 2011–2015. Applying Tobit regression model, the impact of bank size, bank age, and the ownership feature on the efficiency of bank service industry in Vietnam is also investigated. The analysis results show that in general, the Vietnamese banking efficiency is improving during the selected period regardless of techniques used. However, there is small level of similarity in efficiency rankings identified from the SFA and DEA models. In terms of efficiency determinants, the results show that all three variables of size, age, and state ownership have a positive impact on bank efficiency.
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Wojciech, Młynarski, and Kaliszewski Adam. "Efficiency evaluation in forest management – a literature review." Lesne Prace Badawcze / Forest Research Papers 79, no. 3 (2018): 289–98. https://doi.org/10.2478/frp-2018-0029.
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The aim of our work was to give an overview on efficiency evaluation in forest management as described in the literature. Here we present definitions for efficiency and productivity of economic entities as well as categories of efficiency evaluation methods and discuss ratio analysis, parametric and non-parametric approaches to measure efficiency in forestry. With regards to ratio analysis, we focused on reports employing this approach in Poland due to the abundant literature on this subject. On the other hand, studies based on parametric and non-parametric approaches for efficiency evaluation in the forest sector have only been used occasionally in Poland and thus this part of our analysis is based on research done abroad. The most important parametric method is the Stochastic Frontier Approach (SFA), while the most important non-parametric approach involves Data Envelopment Analysis (DEA), which was developed at the end of the 1970s and utilizes a mathematical programming algorithm. Our review shows that efficiency evaluation in forest management in Poland so far is mostly based on ratio analysis. However, although those methods are of considerable practical importance, in terms of scientific development they are now being replaced by more mathematically and statistically advanced parametric and non-parametric methods, which also open up more opportunities to analyze the efficiency of forest management. The first research employing non-parametric DEA recently published in Poland is a good step towards improving research quality and provides comprehensive results for the efficiency evaluation of forest management.
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Marković, Branka, Milica Lakić, and Ružica Đervida. "APPLICATION OF PARAMETER STATISTICAL TESTS AND DATA ENVELOPMENT ANALYSIS METHODS IN MODERN BUSINESS." SCIENCE International Journal 3, no. 4 (2024): 29–34. https://doi.org/10.35120/sciencej0304029m.
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In the absence of a sufficient amount of information for quality business decision-making, i.e. successful performance of activities without unnecessary losses in the consumption of inputs, recently the non-parametric DEA method (Data Envelopment Analysis) is most often used through the linear programming technique. In the event that company managers have enough information to make business decisions, parametric statistical tests are used that compare the company's current performance with optimal performance, i.e. those that are on the edge of efficiency. However, this situation is very rare, so before making business decisions, non-parametric and then parametric statistical tests are carried out in detail. The subject of research of this paper is primarily focused on the simultaneous application of parametric and non-parametric statistical tests in the assessment of the economic efficiency of an economic entity. After the conducted research and analysis of the obtained results, it was determined that the null hypothesis, which claims that the relative efficiency of the warehouse obtained by parametric statistical tests and the DEA method is identical and that the trends have the same direction, could not be fully accepted. Namely, it was found out that the results of one and the same economic situation using the mentioned two types of analysis differ to the extent that they are not adequate for economic decision-making, however identical results were obtained in the assessment of the trend. It can be concluded that the simultaneous application of both methods, as well as its implementation in several iterations, can provide enough quality information for effective decision-making. Stochastic processes that occur during the implementation of business decisions using the DEA technique can be minimized through the simultaneous application of statistical parametric methods and tests for evaluating the expected efficiency of DEA. The effectiveness of this method in any case depends on the size of the sample implemented in the aforementioned statistical analysis. The aforementioned statistical tests enable the measurement and detection of those input parameters that will most effectively contribute to the efficiency of business systems.
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Matulova, Marketa, and Jana Rejentova. "Efficiency of European Airports: Parametric Versus Non-parametric Approach." Croatian Operational Research Review 12, no. 1 (2021): 1–14. http://dx.doi.org/10.17535/crorr.2021.0001.
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This paper presents a performance evaluation of European airports, based on the application of both parametric and non-parametric approaches. We have evaluated the 115 busiest airports in Europe according to the number of passengers checked-in in 2018. The four inputs we used were the number of Terminals, Runways, Boarding gates, and Aircraft stands. Three variables were used to describe the outputs, namely, Passengers, Movements, and Cargo. The parametric method we chose to apply was the Stochastic Frontier Analysis (SFA) with the Cobb-Douglas production function, the Half-Normal distribution of inefficiency component, and the Normal distribution of an error term. As a basic SFA model only allows for a single output, we employed different methods to get a single efficiency score for each and every airport. Next, we evaluated the airport performance non-parametrically using several Data Envelope Analysis (DEA) models including the super-efficiency model. We compared the results obtained by individual approaches and discussed their pros and cons. Finally, we applied the program evaluation procedure to explore the effect of the different forms of airports ownership on their performance.
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Arsad, Roslah, Zaidi Isa, and Siti Nabilah Mohd Shaari. "Estimating Efficiency Performance of Decision-Making Unit by using SFA and DEA Method: A Cross-Sectional Data Approach." International Journal of Engineering & Technology 7, no. 4.33 (2018): 25. http://dx.doi.org/10.14419/ijet.v7i4.33.23478.
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In this paper, a cross-sectional samples data of 115 Malaysian stocks have been employed to compare both Data Envelopment Analysis (DEA) method and Stochastic Frontier Analysis (SFA) method. These approaches are used to provide a review of frontier conceptual measurement, strength and limitation of the parametric and non-parametric models. Stochastic frontier production function of Cobb-Douglas type was utilized for the estimation. The function was estimated using the maximum likelihood estimation technique. Two models in DEA, DEA-CCR and DEA-BCC are applied in this study and the ranking correlation between SFA method and both models DEA are determined by using the Spearman rank method. The result revealed using SFA, the mean technical efficiency of sample consumer product companies is 37.5% and implies that companies operating at means level of technical efficiency could produce 80.1% more output for given level of inputs if they become technically more efficient. From empirical results of the SFA method, we determined that the deviations from the efficient frontiers of production functions are largely attributed to inefficiency effects (technical inefficiency). Finally, the findings also showed that the difference in ranking stocks performance using DEA-CCR, DEA-BCC and SFA methods. The main contribution of the paper is showing the comparative performance based on both model, DEA and SFA method using financial ratio.
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Młynarski, Wojciech, and Adam Kaliszewski. "Efficiency evaluation in forest management – a literature review." Forest Research Papers 79, no. 3 (2018): 289–98. http://dx.doi.org/10.2478/frp-2018-0029.
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Abstract The aim of our work was to give an overview on efficiency evaluation in forest management as described in the literature. Here we present definitions for efficiency and productivity of economic entities as well as categories of efficiency evaluation methods and discuss ratio analysis, parametric and non-parametric approaches to measure efficiency in forestry. With regards to ratio analysis, we focused on reports employing this approach in Poland due to the abundant literature on this subject. On the other hand, studies based on parametric and non-parametric approaches for efficiency evaluation in the forest sector have only been used occasionally in Poland and thus this part of our analysis is based on research done abroad. The most important parametric method is the Stochastic Frontier Approach (SFA), while the most important non-parametric approach involves Data Envelopment Analysis (DEA), which was developed at the end of the 1970s and utilizes a mathematical programming algorithm. Our review shows that efficiency evaluation in forest management in Poland so far is mostly based on ratio analysis. However, although those methods are of considerable practical importance, in terms of scientific development they are now being replaced by more mathematically and statistically advanced parametric and non-parametric methods, which also open up more opportunities to analyze the efficiency of forest management. The first research employing non-parametric DEA recently published in Poland is a good step towards improving research quality and provides comprehensive results for the efficiency evaluation of forest management.
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Supriyono, Supriyono, Ahmad Rodoni, Yacop Suparno, Hermadi Hermadi, and Hilyatun Nafisah. "EFFICIENCY PERFORMANCE ANALYSIS OF PANIN DUBAI SYARIAH BANK IN COLLECTING AND DISTRIBUTING THIRD PARTY FUNDS BEFORE AND AFTER MERGER." I-Finance: a Research Journal on Islamic Finance 5, no. 1 (2019): 46–56. http://dx.doi.org/10.19109/ifinace.v5i1.3716.
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In this study, the researcher would make Panin Dubai Syariah Bank was the object of research on Islamic banks that carry out mergers and acquisitions. This research by using quarterly financial reports to determine the level of efficiency of the Panin Dubai Syariah Bank to be analyzed using the Data Envelopment Analysis (DEA) method. The researcher was used the annual report to find out the extent the Panin Dubai Syariah Bank carries out its Shariah values and objectives to be analyzed based on the Maqashid Index Sharia. The frontier approach can be divided into parametric approaches and non-parametric approaches. The parametric approach takes measurements using stochastic econometrics and seeks to eliminate interference from the effects of inefficiency. While the non-parametric approach with linear programs ( non-parametric linear programming approach ) performs non-parametric measurements using an approach is not stochastic and tends to combine the interference into inefficiency. This is based on the discovery and observation of the population and evaluates efficiency relative to the units observed. In the non- parametric method, the approaches that can be used are Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). The results of the measurement of Bank Panin Dubai Syariah using DEA indicate that the decision to merge carried out by Panin Syariah Bank with Dubai Islamic Bank was the right decision because, with the merger, Panin Dubai Syariah Bank could produce almost perfect efficiency value of 99% in the year 2015. With doing the merger, Bank Panin Dubai Syariah can minimize the inefficiencies that occur in the input variable so that it can maximize the efficiency that occurs in the output variable
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Aifeng, Song, Zhang XiaoYang, Huang Weilai, Yang xue, and Yang Juan. "Two-stage DEA for Bank Efficiency Evaluation Considering Shared Input and Unexpected Output Factors." E3S Web of Conferences 214 (2020): 01036. http://dx.doi.org/10.1051/e3sconf/202021401036.
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With the increasingly fierce market competition, only by relying on high-quality products and high customer satisfaction can enterprises survive in the fierce competition. Among many evaluation methods, Data Envelopment Analysis (DEA), as a non-parametric statistical method to effectively deal with multi-input and multi-output problems, has received more and more attention in evaluating the relative efficiency of decision-making units. In the process of bank efficiency evaluation based on DEA method, there will be a situation that banks have both dual role factors and unexpected output factors. The Two-stage DEA model provides an effective analysis method to solve the problem of bank efficiency evaluation of complex organizational structure. In order to evaluate the efficiency of unexpected output with uncertain information, a stochastic DEA model of unexpected output is established.
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Novaes, Antonio G. N. "RAPID-TRANSIT EFFICIENCY ANALYSIS WITH THE ASSURANCE-REGION DEA METHOD." Pesquisa Operacional 21, no. 2 (2001): 179–97. http://dx.doi.org/10.1590/s0101-74382001000200004.
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Rapid-transit services are a relevant part of the transportation network in most cities of the world. An important aspect of transport policy is the supply of public urban transportation. In particular, it is of interest to determine whether rapid-transit operators are working in a technically and scale-efficient way. Production analysis of transit services has been characterized by the econometric study of average practice technologies. A more recent method to study such production frontiers is Data Envelopment Analysis (DEA). It is a non-parametric method, but its application to rapid-transit, where the relations among technological variables are more strict, requires a previous structural analysis of the intervening inputs and outputs. DEA is employed in this paper to investigate the efficiency and returns to scale of 21 rapid-transit properties of the world. DEA was also used for the benchmarking of non-efficient rapid-transit properties, with special emphasis to the São Paulo’s subway system
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Mirmozaffari, Mirpouya, Reza Yazdani, Elham Shadkam, Seyed Mohammad Khalili, Leyla Sadat Tavassoli, and Azam Boskabadi. "A Novel Hybrid Parametric and Non-Parametric Optimisation Model for Average Technical Efficiency Assessment in Public Hospitals during and Post-COVID-19 Pandemic." Bioengineering 9, no. 1 (2021): 7. http://dx.doi.org/10.3390/bioengineering9010007.
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The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly return to financial stability, hospitals should implement efficiency measure. An average technical efficiency (ATE) model made up of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) for assessing efficiency in public hospitals during and after the COVID-19 pandemic is offered. The DEA method is a non-parametric method that requires no information other than the input and output quantities. SFA is a parametric method that considers stochastic noise in data and allows statistical testing of hypotheses about production structure and degree of inefficiency. The rationale for using these two competing approaches is to balance each method’s strengths, weaknesses and introduce a novel integrated approach. To show the applicability and efficacy of the proposed hybrid VRS-CRS-SFA (VCS) model, a case study is presented.
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De Vicente Oliva, María Auxiliadora, and Alberto Romero-Ania. "How to Incorporate Preference Information in a Weight-Restricted DEA Model: A Straightforward Solution Applied in the Field of Economics, Based on Simos’ Revised Method." Axioms 11, no. 8 (2022): 367. http://dx.doi.org/10.3390/axioms11080367.
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Data envelopment analysis (DEA) is one the most successful techniques in the field of Operations Research. DEA is a non-parametric and objective approach for evaluating the relative efficiency of a set of decision-making units. The original DEA proposal contemplated the total freedom of variation of weights. This free variation may lead to situations with non-realistic weights and to the impossibility of incorporating the judgments of decision-makers. This work studies the links between multicriteria decision analysis (MCDA) and DEA by introducing weight restrictions in a DEA model using a methodology developed to obtain criteria weights in a MCDA context: the so-called Revised Simos’ Procedure. The presented approach is suitable to be applied in the field of economics and management, being an intuitive and simple enough method for decision-makers who are not familiar with working with DEA models or multicriteria decision analysis. A classic example is presented, where the results found with this approach are compared with the results of other approaches which also use multicriteria decision analysis as a tool to obtain weight restrictions for a DEA model.
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Pevcin, Primož. "Efficiency levels of sub-national governments: a comparison of SFA and DEA estimations." TQM Journal 26, no. 3 (2014): 275–83. http://dx.doi.org/10.1108/tqm-12-2013-0127.
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Purpose – By utilizing the two most commonly used approaches to generate “best practice frontier” to estimate efficiency of observed units, the purpose of this research paper is to estimate technical efficiency for total population of 200 Slovenian municipalities for the 2011 fiscal year. Design/methodology/approach – Stochastic frontier analysis (SFA) and data envelopment analysis (DEA) methods are used to estimate technical efficiency levels. Namely, the majority of studies have utilized these two “traditional” approaches. Since the advantages of one method often represent the disadvantages of the other method, the two methods have been selected to compare the results obtained on the technical efficiency levels. Findings – The results suggest that mean technical inefficiency should be approximately 22-25 percent (SFA method), whereas DEA method suggests the inefficiency in the range 12-18 percent. The DEA approach also suggests that the paper has many more technically efficient units compared to the SFA estimates. Nevertheless, the SFA assessment has revealed that, although on average the inefficiency should be larger compared to the DEA assessment, more than one-third of municipalities should exhibit relatively low levels of inefficiency (less than 5 percent). Originality/value – This study utilizes both parametric as well as non-parametric approaches to assess the technical efficiency, which is not very common in the empirical literature. Besides, it focusses on the local government efficiency in a post-socialist country.
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Lita, Iulian, and Tănase Stamule. "Using non-parametric technical data envelopment analysis - DEA, for measuring productive technical efficiency." Proceedings of the International Conference on Business Excellence 12, no. 1 (2018): 533–43. http://dx.doi.org/10.2478/picbe-2018-0048.
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Abstract The following study is, in addition to a reassessment of literature and an analysis based on non-parametrical techniques based on linear programming. The analysis based on the Data Envelopment Analisys (DEA) technique will be used to see whether the model that we have used has a significant importance, if there are any substantial differences between the efficiency scores obtained or estimated through various methods. The theoretical part, based on the DEA technique will be analysed under the influence of both the works of Farell(1957), and also Charnes, Cooper, Rhodes(1978), Banker, Charnes, Cooper(1984) and other newer models. The dissolution of efficiency scores obtained through the CRS-DEA model has been studied for a long time into two different components: One is linked with the scale inefficiency and the other one represents the pure technical inefficiency. This dissolution can be done by using the CRS model with technology when not all the companies are operating at the optimum level, i.e. through the simultaneous application on the same set of data of the CRS and VRS models. In this study, the main non-parametrical Data Envelopment Analysis method is presented (Wu, Fan, Zhou, Zhou, 2012; Halkos, Tzeremes, 2009) and its application on a group of 42 companies (The headquarters of a top commercial bank in Romania - S.C. BRD GROUPE SOCIÉTÉ GÉNÉRALE ), based on the information gained in the years 2016-2017. This paper is original because it combines the already developed method with new techniques, in order to link together economic factors and operational research and leaves more room for future researches with the purpose of further assessing and changing the performance of every decisional unit under the influence of the environmental factors.
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Shameena.H.Khan*1, Mary Louis.L2. "EFFCIENCY ANALYSIS: AN INSIGHT INTO DEA COST MODEL AND ITS APPLICATION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 2 (2018): 553–59. https://doi.org/10.5281/zenodo.1183985.
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This paper presents a mathematical programming approach, known as Data Envelopment Analysis(DEA) to provide a relative cost efficiency estimate of 180 maize farmers. DEA with multiple number of inputs and outputs is a non-parametric efficiency evaluation method and it is widely applied by researchers in efficiency evaluations of various sectors. Farming is not only about the production hence emphasis is given on input oriented cost minimization technique. Six inputs and one output were considered for this study. Cost efficiency of decision making units(DMU) by DEA is carried out through linear programming methods and it compares the efficiencies among different units. DMUs that lie on the frontier curve are efficient in selecting the optimum input and producing the desired amount of output at minimum cost. The result shows that only 40% of the samples were on the frontier line.
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Prevolšek, Boris, Maja Borlinič Gačnik, and Črtomir Rozman. "Applying Integrated Data Envelopment Analysis and Analytic Hierarchy Process to Measuring the Efficiency of Tourist Farms: The Case of Slovenia." Sustainability 15, no. 5 (2023): 4314. http://dx.doi.org/10.3390/su15054314.
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This paper examines the efficiency of tourist farms in Slovenia by adopting an approach using a framework of non-parametric programming—Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP), combining the two because the DEA analysis by itself does not take into account all attributes, especially qualitative ones. The beforementioned two methods rank the farm tourism units with respect to their efficiency. By using the DEA method, an input- and output-oriented BCC and CCR model were introduced to upgrade the criteria by including the additional non-numerical criteria of the AHP. The results of the models showed that there are possible improvements on all levels of efficiency, as well as on the criteria of the additional offer of tourist farms, which were analyzed in the AHP model with additional criteria. According to the estimated efficiency, the ranking of tourist farms differed according to the two methods. Within the group of farms assessed as efficient by DEA, the AHP model allowed a more accurate ranking.
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Nourani, Ahmed, and Abdelaali Bencheikh. "Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria." Acta Technologica Agriculturae 23, no. 2 (2020): 60–66. http://dx.doi.org/10.2478/ata-2020-0010.
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AbstractAlgeria has recently experienced an important agricultural development in terms of gardening in plastic greenhouses thanks to the favourable factors (climatic conditions, etc.). In order to optimize the energy requirements, data from 29 farmers were collected, who qualitatively represent the greenhouse vegetable producers from the most productive sub-provinces of Biskra region (south of Algeria). Considering the various parametric and non-parametric methods for energy consumption optimization, data envelopment analysis is the most common non-parametric method applied. Results showed that the mean radial technical efficiency assumptions of the samples under constant returns to scale and variable returns to scale models were 0.88 and 0.98, respectively. The 51.72% of decision-making units were efficient on the basis of the constant returns to scale model; 79.31% decision-making units were observed efficient on the basis of variable returns to scale model. Calculation of optimal energy requirements for vegetable greenhouse indicated that 108.50 GJ·ha−1 can be saved on machinery (1.38 GJ·ha-1); diesel fuel (4.68 GJ·ha−1); infrastructure (9.35 GJ·ha−1); fertilizers (17.08 GJ·ha−1); farmyard manure (12.05 GJ·ha−1); pesticides (3.93 GJ·ha−1); and electricity (60.03 GJ·ha−1).
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Chen, Limei, Xiaohan Xie, Yao Yao, Weidong Huang, and Gongzhi Luo. "A Hybrid Data Envelopment Analysis–Random Forest Methodology for Evaluating Green Innovation Efficiency in an Asymmetric Environment." Symmetry 16, no. 8 (2024): 960. http://dx.doi.org/10.3390/sym16080960.
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The accurate evaluation of green innovation efficiency is a critical prerequisite for enterprises to achieve sustainable development goals and improve environmental performance and economic efficiency. This paper evaluates the green innovation efficiency of 72 new-energy enterprises by using a hybrid method of Data Envelopment Analysis (DEA) and a random forest model. The non-parametric DEA model is combined with the parametric SFA model to analyze the real green innovation efficiency on the basis of removing environmental factors and random factors. Then, the random forest model based on a nonlinear relationship is used to evaluate factors impacting green innovation efficiency. This paper proposes a comprehensive evaluation method designed to assess the green innovation efficiency of new-energy enterprises. By applying this method, companies can gain a comprehensive understanding of the current performance in green innovation, facilitating informed decision-making and accelerating sustainable development.
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SAATI, SABER, ADEL HATAMI-MARBINI, MADJID TAVANA, and PER J. AGRELL. "A FUZZY DATA ENVELOPMENT ANALYSIS FOR CLUSTERING OPERATING UNITS WITH IMPRECISE DATA." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, no. 01 (2013): 29–54. http://dx.doi.org/10.1142/s0218488513500037.
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Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiency of peer operating units that employ multiple inputs to produce multiple outputs. Several DEA methods have been proposed for clustering operating units. However, to the best of our knowledge, the existing methods in the literature do not simultaneously consider the priority between the clusters (classes) and the priority between the operating units in each cluster. Moreover, while crisp input and output data are indispensable in traditional DEA, real-world production processes may involve imprecise or ambiguous input and output data. Fuzzy set theory has been widely used to formalize and represent the impreciseness and ambiguity inherent in human decision-making. In this paper, we propose a new fuzzy DEA method for clustering operating units in a fuzzy environment by considering the priority between the clusters and the priority between the operating units in each cluster simultaneously. A numerical example and a case study for the Jet Ski purchasing decision by the Florida Border Patrol are presented to illustrate the efficacy and the applicability of the proposed method.
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Al-Assa'd, Tamer, and Johannes Sauer. "The performance of water utilities in Jordan." Water Science and Technology 62, no. 4 (2010): 803–8. http://dx.doi.org/10.2166/wst.2010.907.
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This paper aims to measure the relative performance of Jordan's water utilities for water sector (WS) and wastewater sector (WWS), and to investigate the major factors behind their inefficiencies. DEA (non-parametric method) and Tobit model (parametric method) were used at two stages. At the first stage DEA was used to evaluate the utilities' efficiency and to investigate the utilities' scale effect on efficiency. At the second stage Tobit model (regression) is applied to determine the impact of the non-controllable factors on utilities' inefficiencies where the efficiency score is the dependent variable in the regression. The results of DEA showed that there is a potential to reduce inputs level: water supply and operational expense (OPEX) for WS, and treated wastewater and OPEX for WWS, by around 15–20 and 23–27%, respectively. Aqaba and Jarash utilities are the most efficient utilities in the WS, while it is Amman utility in the WWS. The utility size has relatively moderate effect on the relative performance. It is concluded that the medium utility size for WS and large utility size for WWS is the most appropriate. Tobit model results indicate that commercialization activities have a clear positive impact on efficiency improvement for both sectors.
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Tóth, Orsolya, and István Takács. "Farm Structure And Efficiency In The Hungarian Agriculture." Visegrad Journal on Bioeconomy and Sustainable Development 4, no. 2 (2015): 51–56. http://dx.doi.org/10.1515/vjbsd-2015-0012.
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Abstract It has long been the subject of empirical researches to examine the technical efficiency on farm (micro) level. Two main methods are most often used in the empirical literature: the non-parametric Data Envelopment Analysis (DEA) based on linear programming, and the Stochastic Frontier Analysis (SFA) introduced by Aigner, Lovell and Schmidt (1977). The present study aimed to investigate the technical efficiency of farms involved in agricultural activities in Hungary using the DEA-method and the data from the Hungarian FADN database. The technical efficiency was examined based on legal forms, farm size categories and the type of farming between 2001 and 2013.
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Wang, Zhao Yang. "An Empirical Analysis on Efficiency of Foreign-Invested Manufacturing Enterprises in Hubei." Advanced Materials Research 479-481 (February 2012): 1091–96. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.1091.
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Using non-parametric Data Envelopment Analysis (DEA) method, the paper evaluates the efficiency of foreign-invested manufacturing enterprises in Hubei. The results indicate that the efficiency of foreign-invested manufacturing enterprises in Hubei is not high, and the trend is increasing returns to scale.Finally,through the projection analysis, the paper puts forward the countermeasure.
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Kubik, Renata. "Regionalne zróżnicowanie efektywności ekonomicznej gospodarstw towarowych specjalizujących się w uprawach ogrodniczych." Zeszyty Naukowe SGGW - Ekonomika i Organizacja Gospodarki Żywnościowej, no. 109 (April 3, 2015): 133–42. http://dx.doi.org/10.22630/eiogz.2015.109.11.
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To analyze the effectiveness of farms a non-parametric method DEA and financial analysis was used. DEA allows to determine the effectiveness of objects based on multiple inputs and outputs. It does not require functional form of the frontier. The analysis covers commercial farms grouped into the type horticulture (FADN classification) and presented by region. To build the DEA input-orientated model, the following variables were used: output – total output crops and crop production (SE135), inputs – labour input (SE011), total specific costs (SE281), total farming overheads (SE336). To complete the analysis the financial indicators were calculated. The results indicate that the farms from region Mazowsze and Podlasie (795) were the most effective.
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Novaes, Antonio G. N., Samantha F. Silveira, and Helena C. Medeiros. "Efficiency and productivity analysis of the interstate bus transportation industry in Brazil." Pesquisa Operacional 30, no. 2 (2010): 465–85. http://dx.doi.org/10.1590/s0101-74382010000200012.
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Productivity analysis is an important policy making and managerial control tool for assessing the degree to which inputs are utilized in the process of obtaining desired outputs. Data Envelopment Analysis (DEA) is a non-parametric method based on piecewise linear frontiers estimated with the aid of mathematical programming techniques and used, in this paper, to investigate technical, scale and managerial efficiencies associated with interstate bus companies in Brazil (ISBT). Data has been obtained from the web-site of the Brazilian National Agency of Land Transportation (ANTT). Since production factors in the application are constrained by technical and operational reasons, weight restrictions were introduced into the DEA models. The analysis has shown three groups of non-efficient bus firms, with clear differences in productivity. The relative managerial efficiencies of the firms in the non-efficient groups were also computed and analyzed. Finally, an example of benchmarking a non-efficient firm with DEA is presented.
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Endri, Endri, Naning Fatmawatie, Sugianto Sugianto, Humairoh Humairoh, Mohammad Annas, and Arjuna Wiwaha. "Determinants of efficiency of Indonesian Islamic rural banks." Decision Science Letters 11, no. 4 (2022): 391–98. http://dx.doi.org/10.5267/j.dsl.2022.8.002.
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The purpose of the study is to evaluate the efficiency of Islamic Rural Banks (BPRS) and analyze the factors that determine them using a two-stage approach to Data Envelopment Analysis (DEA). DEA in this study focuses on the production, intermediation, and inefficiency causes. This research was done on BPRS across Indonesia. The data were taken from a financial report for the 2013-2021 period. The source of the data was a publication from the Financial Services Authority of Indonesia. The data were analyzed using the non-parametric approach with a two-stage DEA method. The input variables were personnel costs, fixed assets, and third-party funds. The result shows that Revenue Sharing, ROA, and Growth have a significant positive effect on DEA. BOPO and inflation have a positive but insignificant effect on DEA. While NPF and FDR have negative but insignificant effects on DEA. Then CAR has a negative and not significant effect on DEA. It also shows that the variables of Revenue Sharing, NPF, ROA, CAR, FDR, BOPO growth, and inflation have a simultaneous effect on DEA.
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Jablonský, Josef. "Data Envelopment Analysis Models in Non-Homogeneous Environment." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 67, no. 6 (2019): 1535–40. http://dx.doi.org/10.11118/actaun201967061535.
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Data envelopment analysis (DEA) is a non-parametric method that is widely used for relative efficiency and performance evaluation of the set of decision-making units (DMUs). It is based on maximization of a weighted sum of outputs produced by the unit under evaluation divided by the weighted sum of inputs of the same unit, and the assumption that this ratio for all other units has to be lower or equal to 1. An important assumption for applications of DEA models is the homogeneity of the units. Unfortunately, the homogeneity assumption is not fulfilled in many real applications. The paper deals with the analysis of efficiency using DEA models in the non-homogeneous environment. One of the problems lies in non-homogeneous outputs. In this case, the units under evaluation spend the same inputs but produce completely or at least partly different set of outputs. The paper formulates several models how to deal with this problem and compares the results on a numerical example. Other main sources of non-homogeneity are discussed as an excellent possible starting point for future research.
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Markovits-Somogyi, Rita. "Review and Systematization of Efficiency Measurement Methods Used in the Transport Sector." PROMET - Traffic&Transportation 23, no. 1 (2012): 39–47. http://dx.doi.org/10.7307/ptt.v23i1.147.
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Efficiency analysis of transport systems can be carried out using numerous different techniques. Experts generally distinguish them as parametric and non-parametric methods, or else as methods using a production function, an index or not using anything of this kind. Based on the literature and on own research the present paper sets up a clear systematization of these techniques giving a brief summary of their essence while also providing examples of their application in the transport sector. Having elucidated each method, the author also outlines the correlation and the reliability of the techniques and presents a novel view which stresses the importance of links between the different techniques. KEY WORDS: efficiency measurement, transport, TFP, MPI, SFA, DEA, OCRA
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Chan, Defri Muhammad, Herman Mawengkang, and Sawaluddin Nasution. "Measurement of DEA-Based ICT Development Efficiency Level with Modified CCR Method." Jurnal Varian 6, no. 1 (2022): 97–104. http://dx.doi.org/10.30812/varian.v6i1.2197.
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Data Envelopment Analysis (DEA) is the use of non-parametric mathematical programming that is useful for measuring the efficiency of the Decision Making Unit (DMU) of an organization. This study uses the Cooper and Rhodes (CCR) method known as the DEA-CCR multiplier which aims to determine the weight value of each input and output variable of the DMU being evaluated, but it is not sufficient to measure efficiency optimization. To get an efficient value of the weight value of each DMU as a reference to get updated DMU input and output values. So that the DMU efficiency value is obtained which is evaluated. The results of this study show how to modify the Multiplier Model-CCR into the Envelopment Model-CCR. Then displays the efficient level DMU which is evaluated as a result of the weight each DMU gets from the results of processing the LINDO application. Illustrations of changes in input variables and output variables are displayed in the form of tables and figures before and after the changes. The modified DEA-CCR model can also complete DMU super efficiency, effectiveness and productivity.
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Muhammad Nagiyev, Muhammad Nagiyev. "DEA METHOD FOR MEASURING THE ACTIVITY EFFICIENCY OF THE ENTERPRISE." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 148, no. 02 (2024): 82–89. http://dx.doi.org/10.36962/pahtei148022024-82.
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Performance evaluation is no less important for the management experience of any organ-ization. Efficiency, which is a characteristic feature of the quality of activity and, consequently, its viability in a competitive market environment, is not only the most important field of theoretical and empirical research in the field of economics and management, but also the object of the closest attention of both the management of organizations and other interested parties. At the same time, its measurement is carried out on the basis of the relevant conceptual models according to the nature of the analyzed activity, which determines the description of the considered aspect of the division's activity (mainly financial, strategic or operational). In the article, the measurement of activity efficiency was considered as a research area and the main steps in DEA research are shown. The efficiency scores and scope of the DEA method, a non-parametric method that measures efficiency within a group of homogeneous decision-making units (DMUs) with multiple inputs and multiple outputs, are investigated. Thus, the article identifies institutions with efficient and inefficient operations, promoting possible improvements for efficient DEA operational performance. Keywords: size parameter, number of inputs and outputs density parameter, efficient and inefficient operation, evaluation of operation efficiency, data envelope analysis
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Al-Ansari, Muna A., Hamad Nabeel, Galal M. Abdella, Tarek El Mekkawy, and Adeeb A. Kutty. "A Non-Parametric Approach-Based Trade-Off between Food System Efficiency and Robustness." Sustainability 16, no. 15 (2024): 6480. http://dx.doi.org/10.3390/su16156480.
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Balancing the efficiency and robustness of food systems is a well-known trade-off process. Over-optimization of efficiency may lead to excessive use of resources. On the other hand, the under-optimization of efficiency may lead to excessive waste of resources. This paper presents a novelly structured approach that integrates two well-suited non-parametric methods for analyzing and balancing the interconnection between the efficiency and robustness of food systems. This approach, which consists of three main steps, provides a theoretical framework and offers practical solutions. First, slacks-based data envelopment analysis (SBM-DEA) is utilized to analyze the efficiency of five food robustness dimensions. Second, the weighted efficiency of these dimensions is computed and analyzed to provide insight into their influence on food system efficiency. Finally, two search methods were developed to identify improving efficiency and robustness opportunities. The outcomes of these methods were analyzed and validated using data from 37 countries, with robustness dimension weights determined via the Analytic Hierarchy Process (AHP). While the first improvement method provided valuable insights, the second method proved more effective in identifying the sources of inefficiency of robustness dimensions.
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Cao, Li, Zhan Xin Ma, and Xu Hong Qi. "Analysis on Economic Efficiency and Industrial Structure Adjustment of Some Counties Based on DEA Method." Advanced Materials Research 1073-1076 (December 2014): 2831–35. http://dx.doi.org/10.4028/www.scientific.net/amr.1073-1076.2831.
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The county economy is not only an important component of the national economy, but also be the basic operation unit of the national economy.It plays an irreplaceable role in the great economic and social development of our country. In this paper, we provide a non-parametric method for analyzing the economic efficiency based on DEA theory. Then we analyze the development efficiency of eight counties in Tongliao City from 2003 to 2012 , we also put forward suggestions on how to adjust the industrial structure according to the data analysis of the results of the model.
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Lamovšek, Nejc, and Maja Klun. "Evaluation of Biomedical Laboratory Performance Optimisation Using the DEA Method." Slovenian Journal of Public Health 59, no. 3 (2020): 172–79. http://dx.doi.org/10.2478/sjph-2020-0022.
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AbstractIntroductionThe Slovenian Resolution on the National Healthcare Plan notes that the country’s medical laboratory activities are fragmented, which may result in cost-inefficiency and a reduction in the quality of the services provided. Defining the efficiency of laboratory service providers can therefore help us to pursue the objectives of the Resolution, i.e. to consolidate and integrate laboratory activities.MethodsUsing the DEA method, we conducted an analysis of the efficiency of 20 biomedical laboratories in Slovenia, and made a comparison with a “virtual” laboratory, i.e. a merger of laboratories within a selected organisational unit. By testing different DEA models, we sought to determine whether the use of different input variables caused significant differences in the laboratories’ efficiency scores.ResultsThe research results show that inefficiency resulting from the size of the units is 1.5 times greater than process inefficiency. Using a non-parametric Wilcoxon Signed Rank test, we determined, at a risk level of 0.05, that there was no difference between the efficiency results when using two different technical efficiency DEA models. When evaluating the virtually merged laboratory, we determined that, under all three models, the virtual laboratory achieved 100% VRS efficiency. However, when the CRS methodology was used, the laboratory showed a certain degree of scale inefficiency.ConclusionsWhen evaluating merger of medical laboratories we note that the DEA method is methodologically suitable for evaluating the effects of health policy implementation, and is an appropriate tool for identifying where the field of laboratory medicine might be further developed and improved.
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AZADEH, A., S. F. GHADERI, and M. FAZLI AHMADABAD. "MULTI CRITERIA QUALITY ASSESSMENT OF PRODUCTS BY INTEGRATED DEA-PCA APPROACH." International Journal of Reliability, Quality and Safety Engineering 14, no. 03 (2007): 201–18. http://dx.doi.org/10.1142/s0218539307002593.
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The objective of this study is to analyze and assess multi criteria quality of products by an integrated multivariate approach. The integrated multivariate method is based on data envelopment analysis (DEA), principle component analysis (PCA) and numerical taxonomy (NT). To achieve the objective of this study 51-product quality indicators were identified. These indicators (inputs and outputs) were classified as direct and indirect product quality indices and they were classified according to balanced score card (BSC) arrangements. To show the applicability of the proposed approach, five random indicators were considered for seventeen workshops within a large machinery manufacturer. Moreover, PCA, DEA and NT were applied to the set of data. Furthermore, PCA and NT are used to verify and validate the findings of DEA. The results (ranking) of the three approaches were then compared by non-parametric Spearman and Kendall Tau correlation techniques. The results of the non-parametric analysis show should high level of correlation between the three approaches. Previous studies evaluate quality characteristics based on a set of selected criteria that does not reflect total quality characteristics, whereas this study proposes a total multi criteria quality approach to overcome these shortcomings. Moreover, this is the first study to utilize and apply an integrated multivariate approach based on DEA, PCA and Numerical Taxonomy for assessment, ranking and verification and validation of industrial units based on multi criteria quality characteristics. This means that DEA is used for ranking, PCA is used for evaluation of the importance of each indicator and NT is used for validation and verification purpose. The approach of this study may be applied to other manufacturers for total quality assessment of quality characteristics.
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Mitsopoulos, Ioannis, Maria Tsiouni, Aleksandra Pavloudi, Dimitrios Gourdouvelis, and Stamatios Aggelopoulos. "Improving the technical efficiency and productivity of dairy farms in Greece." Studies in Agricultural Economics 123, no. 2 (2021): 95–100. http://dx.doi.org/10.7896/j.2154.
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This paper aims to examine the current state of dairy cattle farming in Greece, to identify factors that aff ect its profitability, and to analyse the efficiency of farms, using the non-parametric Data Envelopment Analysis (DEA) method. It also assesses the economic viability of dairy cattle farms by quantifying the technical efficiency of their processes, with a view to suggesting measures that may serve to improve competitiveness. Results have shown that the mean technical efficiencies estimated for the CRS and VRS DEA approaches are 0.693 and 0.754 respectively, indicating that 30.7% and 21.6% equiproportional decreases in inputs are feasible, given the level of outputs and the production technology.
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Markovits-Somogyi, Rita, and Zoltán Bokor. "ASSESSING THE LOGISTICS EFFICIENCY OF EUROPEAN COUNTRIES BY USING THE DEA-PC METHODOLOGY." TRANSPORT 29, no. 2 (2014): 137–45. http://dx.doi.org/10.3846/16484142.2014.928787.
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Data envelopment analysis is a non-parametric linear programming method widely used for the efficiency evaluation of decision making units active in the transport sector. However, it is seldom applied for the efficiency assessment of logistics efficiency at a macro level. The article presents such an example which is at the same time the very first application of a lately developed methodology where data envelopment analysis is combined with analytic hierarchy process to yield an appropriate tool for efficiency evaluation with full ranking. The logistics efficiency of 29 European countries is tested with the new DEA-PC (pairwise comparison) methodology while it is also compared with the results gained with the original DEA method. Furthermore, the outcomes are also evaluated in light of the ‘Logistics quality and competence’ index of the Logistics Performance Indicator (LPI), a major international survey into the logistics competence of countries. Thus, the results of traditional DEA and DEA-PC are both weighted against survey data which is also a novelty in the logistics sector
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Razavi Hajiagha, Seyed Hossein, Shide Sadat Hashemi, and Hannan Amoozad Mahdiraji. "Fuzzy C-means based data envelopment analysis for mitigating the impact of units’ heterogeneity." Kybernetes 45, no. 3 (2016): 536–51. http://dx.doi.org/10.1108/k-07-2015-0176.
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Purpose – Data envelopment analysis (DEA) is a non-parametric model that is developed for evaluating the relative efficiency of a set of homogeneous decision-making units that each unit transforms multiple inputs into multiple outputs. However, usually the decision-making units are not completely similar. The purpose of this paper is to propose an algorithm for DEA applications when considered DMUs are non-homogeneous. Design/methodology/approach – To reach this aim, an algorithm is designed to mitigate the impact of heterogeneity on efficiency evaluation. Using fuzzy C-means algorithm, a fuzzy clustering is obtained for DMUs based on their inputs and outputs. Then, the fuzzy C-means based DEA approach is used for finding the efficiency of DMUs in different clusters. Finally, the different efficiencies of each DMU are aggregated based on the membership values of DMUs in clusters. Findings – Heterogeneity causes some positive impact on some DMUs while it has negative impact on other ones. The proposed method mitigates this undesirable impact and a different distribution of efficiency score is obtained that neglects this unintended impacts. Research limitations/implications – The proposed method can be applied in DEA applications with a large number of DMUs in different situations, where some of them enjoyed the good environmental conditions, while others suffered from bad conditions. Therefore, a better assessment of real performance can be obtained. Originality/value – The paper proposed a hybrid algorithm combination of fuzzy C-means clustering method with classic DEA models for the first time.
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Ma, Zhan Xin, Li Cao, and Ri Su Na. "Research on the Energy Consumption Efficiency of some Counties Based on DEA Method." Advanced Materials Research 962-965 (June 2014): 1792–96. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.1792.
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With the increasing process of Chinese urbanization and the rapid development of county economy, the demand to energy becomes more and more. In this case, the resources and energy in the country must be made the best use for a long time in the future, so as to realize the overall targets of the development of China. The energy resources have played a very significant role in urbanization of China. Thus, it is an important task to increase the efficiency of energy consumption in counties. So we provide a non-parametric method for analyzing the energy efficiency of county based on DEA theory. Then we analyze the energy efficiency of nine counties in Chifeng City from 2008 to 2012 by using above method.
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Petrov, Ph V. "Assessment of the Economic Security of Russia in the Foreign Economic Sphere on the Basis of the Non-parametric Method." MIR (Modernization. Innovation. Research) 13, no. 1 (2022): 27–41. http://dx.doi.org/10.18184/2079-4665.2022.13.1.27-41.
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Purpose: is to assess the security of Russia's economic security in the foreign economic sphere.Methods: the article is based on the analysis of the theoretical foundations of the formation of target values of economic security indicators, the study of the methodology for applying the non-parametric method for assessing data envelopment analysis and the use of the statistical method of information processing. The method of comparative analysis of the economic development of foreign countries was also used. To form a holistic view of the results of the assessment, the data visualization method was used.Results: based on the result of considering the methodology of the non-parametric data envelopment analysis estimation method, the advantages of its application are described, as well as the key features that need to be paid attention to when assessing by this method. The content of two main assessment models used in the framework of the data envelopment analysis (DEA) method is disclosed, the use of one of them in the context of assessing the country's economic security is justified. By using specialized software (Deap version 1.2), the economic security of Russia in the foreign economic sphere was assessed, as a result of which the target value of the economic security indicator for the long term was obtained.Conclusions and Relevance: the method for assessing economic security considered in the article makes it possible to deepen the existing assessment tools, supplement the existing methods for calculating the target indicators of economic security and, if necessary, adjust the current target indicators. The information obtained on the basis of the DEA method can be used in the formation of plans and forecasts in the field of economic security, as well as in the development of methodological support for the Economic Security Strategy of the Russian Federation for the period up to 2030.
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Deng, Jin. "DEA-Nadaraya-Watson Two-Stage Method and Urban Transit Service Efficiency Evaluation Based on Nonparametric Regression Technique." Advanced Materials Research 869-870 (December 2013): 305–9. http://dx.doi.org/10.4028/www.scientific.net/amr.869-870.305.
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In view of the problem of DEA-Tobit Two-stage method, nonparametric regression technique was applied in the second stage. By this way, the proposed method could guarantee the consistency hypothesis at both stages.And empirical analyses were carried on based on the actual transit operation datain China.The Nadaraya-Watson non-parametric regressiondemonstrates thatfiscal subsidy has a promoting effect on bus service efficiency.Furthermore, transit service efficiencydecreases withthe increase ofpopulation density andmotor vehicle ownership. In addition, the analysis also suggests that there is no clear correlation between the transit service efficiency and the travelleddistance factor.
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Ben Abdelkader, Ines, and Faysal Mansouri. "Performance of microfinance institutions in the MENA region: a comparative analysis." International Journal of Social Economics 46, no. 1 (2019): 47–65. http://dx.doi.org/10.1108/ijse-06-2017-0242.
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Purpose The purpose of this paper is to provide preliminary efficiency assessment of Arab microfinance institutions (MFIs) within the period 2002–2012. Microfinance is defined as the provision of financial services to poor and low-income households and their microenterprises on a sustainable basis. Design/methodology/approach The authors first present the main features of microfinance in the Middle East and North Africa (MENA) region. Second, based on a simple of 72 microfinance institutions issued from ten countries of the region, they develop a bootstrap–data envelopment analysis (bootstrap–DEA) framework to measure Arab MFIs’ efficiency. Finally, they apply parametric and non-parametric tests to compare the performance and identify factors that contribute to the efficiency of Arab Islamic microfinance institutions. Findings Efficiency scores of the MENA region exhibit high variability, both across time and countries. Significant difference in efficiency was found due to MFI age or regulation. Results also reveal the ability of Arab MFIs to combine social and financial performance and their solidity in time of crisis. Originality/value In this paper, the authors apply DEA–bootstrap method on a large sample of Arab MFI with special look at the peer group differences. Unlike most previous relevant studies, the paper overcomes many of the drawbacks of the DEA method by using, in addition to the DEA–bootstrap approach, a test of return to scale and a combination of three procedures to detect outliers. Furthermore, this paper analyses the efficiency of MFI in the MENA region in the light of financial crises and Arab Spring.
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Seyed Mehdi Nassiri and Surendra Singh. "Optimization of Energy Inputs for Wheat Cultivation in Punjab Using Data Envelopment Analysis Technique." Journal of Agricultural Engineering (India) 45, no. 3 (2008): 1–11. http://dx.doi.org/10.52151/jae2008453.1333.
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Production function is used for optimizing purposes. Such functions are established by parametric or non-parametric approaches. In this study non-parametric method i.e. Data Envelopment Analysis (DEA) has been used to optimize the applied energy in wheat production system in Punjab. Two basic DEA models i.e. input-oriented CCR (Charnes, Cooper and Rhodes) and BCC (Banker, Charnes and Cooper) models were subjected on operation-wise and sourcewise energy inputs. BCC model could classify the inefficient farmers to different categories of returns-to-scale (RTS), namely, increasing, decreasing and constant. Results revealed that the yield was mostly dependent upon tillage, irrigation and sowing, respectively, with the mean share of 23, 21.6 and 17.4% for CCR efficient farmers and 26.4, 19.2 and 18% for BCC efficient farmers in all zones. Also the yield was sensitive to human, diesel and seed energy sources with mean shares of32, 18 and 18.6% for CCR efficient farmers and 37, 23.6 and 12.4% for BCC, respectively. Weeding and fertilizer application used energy in excess by 46% and 31.3% for CCR inefficient farmers and by 34% and 29% for BCC, respectively. Electricity and machinery possessed the highest use among all energy sources. It was 43.8% and 21.7 % for CCR inefficient farmers and 33.6% and 15.5% for BCC ones, respectively. Trend of excessive use of energy was the same for both the models
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Firdaus, Muhammad faza, and Muhamad Nadratuzzaman Hosen. "EFISIENSI BANK UMUM SYARIAH MENGGUNAKAN PENDEKATAN TWO-STAGE DATA ENVELOPMENT ANALYSIS." Buletin Ekonomi Moneter dan Perbankan 16, no. 2 (2014): 167–88. http://dx.doi.org/10.21098/bemp.v16i2.31.
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The aim of this study is to measure the efficiency of Islamic Bank in Indonesia, to analyze the factors that affect the level of efficiency which is known as Two-Stage Data Envelopment Analysis method and to propose measurement of Bank Soundness with modified CAMELS. The objects of this study are 10 (ten) Islamic Bank (BUS) in Indonesia which analyzes from the second Quarter of 2010 until the fourth Quarter of 2012. There are 2 (two) methods which are used in this study, namely non-parametric method of Data Envelopment Analysis (DEA) on the first stage and Tobit model on the second stage. In addition, this study will illustrate the formulation of the financial factors of CAELS instead of CAMEL by integrating the results of efficiency level measurement using DEA in CAELS formulation. Overall, the results, show that the efficiency level of Islamic banks in Indonesia during the time period in this study, have not yet reach the optimum level of efficiency. In addition, modification of CAELS for the bank performance level method by integrating the result of DEA shows that the modification of CAELS could be more accurate in describing the bank performance level, particularly for Islamic Bank in Indonesia. Keywords: Efficiency, Data Envelopment Analysis (DEA), Tobit Model, CAELS + DEAJEL Classification: C02, C14, C54,G21
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Firdaus, Muhammad Faza, and Muhamad Nadratuzzaman Hosen. "Efficiency of Islamic Banks Using Two Stage Approach of Data Envelopment Analysis." Buletin Ekonomi Moneter dan Perbankan 16, no. 2 (2014): 155–76. http://dx.doi.org/10.21098/bemp.v16i2.442.
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The aim of this study is to measure the efficiency of Islamic Bank in Indonesia, to analyze the factors that affect the level of efficiency which is known as Two-Stage Data Envelopment Analysis method and to propose measurement of Bank Soundness with modified CAMELS. The objects of this study are 10 (ten) Islamic Bank (BUS) in Indonesia which analyzes from the second Quarter of 2010 until the fourth Quarter of 2012. There are 2 (two) methods which are used in this study, namely non-parametric method of Data Envelopment Analysis (DEA) on the first stage and Tobit model on the second stage. In addition, this study will illustrate the formulation of the financial factors of CAELS instead of CAMEL by integrating the results of efficiency level measurement using DEA in CAELS formulation. Overall, the results, show that the efficiency level of Islamic banks in Indonesia during the time period in this study, have not yet reach the optimum level of efficiency. In addition, modification of CAELS for the bank performance level method by integrating the result of DEA shows that the modification of CAELS could be more accurate in describing the bank performance level, particularly for Islamic Bank in Indonesia. Keywords: Efficiency, Data Envelopment Analysis (DEA), Tobit Model, CAELS + DEAJEL Classification: C02, C14, C54,G21
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Hou, Yi Wen, Hong Yin Song, and Li Hong Wang. "Provincial Energy Conservation Visual Potential Analysis Based on DEA Model." Advanced Materials Research 962-965 (June 2014): 1461–67. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.1461.
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As the basic study of energy conservation, Apparent Potential of Energy Saving and Emission Reduction (AP-ESER) analysis is a key link of energy conservation work in China. Compared with developed countries, the performances of energy conservation are not remarkable in most developing countries, which ensured the dominant position of apparent potential in the whole potential field. Based on the non-parametric Data Envelopment Analysis (DEA) method model and total-factor framework, the study established an AP-ESER analysis system. We investigated a sample of 30 provinces in China, used K-means clustering method, GIS special labeling method and radar graphic method to analyze the results, and divided the 30 provinces into 5 clusters according to the visual potential of energy conservation. At the same time, we tried to find the key factors of energy conservation in each province following the status comparison of radar graphic method, and listed it under the sort of critical degree of the factors.
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Moh Farih Fahmi, Binti Mutafarida, and Farid Fathur Rohman. "Comparison of Efficiency of Islamic Commercial Banks Using the Data Envelopment Analysis (DEA) Method: Studies On Pt. Bank Mega Syariah Indonesia, Pt. Bank Central Asia Syariah And Pt. Bank Muamalat Indonesia." Ulum Islamiyyah 35, no. 02 (2023): 16–36. https://doi.org/10.33102/uij.vol35no02.497.
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This article discusses the comparison of the efficiency of PT. Bank Mega Syariah Indonesia, PT. Bank Central Asia Syariah and PT. Bank Muamalat Indonesia in 2014-2021 using the data envelopment analysis (DEA) method. The efficiency will be tested using quantitative research using the DEA method which is interpreted as a non-parametric method based on a linear program used to compare efficiency. The DEA model used in this study is the Variable Return to Scale (VRS) model and is assisted by technical software with DEAP Version 2.1 software with Windows OS. The results of the test are (1) Bank Mega Syariah, BCA Syariah and BANK Muamalat are always in an efficient condition from 2014-2021. Overall, the efficiency performance achieved by the three banks above has included a projection summary of each input and output which consists of original input and output values, radial movement, slack movement, and projected value. If the value of the radial movement and slack movement is 0, 000, it means that each input or output variable is in an optimal and efficient state
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Xia, Meimei. "Choquet-Integral-Based Data Envelopment Analysis with Stochastic Multicriteria Acceptability Analysis." Symmetry 14, no. 4 (2022): 642. http://dx.doi.org/10.3390/sym14040642.
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Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiencies of decision-making units (DMUs) by using a set of inputs and a set of outputs. However, traditional DEA models always assume that the inputs or outputs are independent of each other, which is unrealistic in practical problems. To reflect the interactions between inputs or outputs, the Choquet integral is employed in DEA models. The traditional DEA models are usually used to find some specific input and output weights of DMUs to optimize the efficiency score of DMUs, but the corresponding input and output weights for the optimal efficiency score of a DMU may not be distributed symmetrically, that is to say, the space of weights may be different for different DMUs. Instead of finding the self-efficiency score and the cross-efficiency score of a DMU in traditional DEA models based on some specific input and output weights, stochastic multicriteria acceptability analysis is used to explore the input or output evaluation space and weight space to calculate the Choquet-integral-based acceptability indices of DMUs. The proposed method considers the interactions between inputs or outputs, which can make more DMUs efficient and can also measure the acceptability of a DMU to become an efficient one by exploring the supporting information space. Examples are given to illustrate the proposed method.
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Erdkhadifa, Rendra. "PEMODELAN DEA AGGRESSIVE - BOOTSTRAP REGRESSION PADA FAKTOR YANG MEMPENGARUHI EFISIENSI PERBANKAN SYARIAH INDONESIA." Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika 5, no. 1 (2024): 216–31. http://dx.doi.org/10.46306/lb.v5i1.442.
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Data Envelopment Analysis is a non-parametric method developed based on linear programs with objective functions and weight functions. DEA is an analytical technique used to measure the efficiency of a process which the decision making units (DMUs) are homogeneous. The application of the DEA method in various fields yields in steps in determining policies in a process. This study aims to measure the efficiency of Indonesian Islamic banking by applying DEA method with aggressive weighting. The efficiency result of the method is then combined with bootstrap regression method to find out the variables that significantly influence the efficiency value. The data in the research process was taken from the monthly financial reports of Indonesian Islamic banking from 2018 to 2022 with a quantitative research approach and associative research type. The input variables used to measure efficiency include total assets, total labor, labor operating costs, total deposits, and fixed assets.While the output variables include total financing funds, net operating margin, and other operating income. Meanwhile, the independent variables to estimate the factors that influence the efficiency value of DEA include capital adequacy ratio, return on assets, company size, and financing to deposit ratio.The result of the analysis shows the goodness of the model which is the coefficient of determination worth 40.95%. Independent variables that significantly affect the efficiency of DEA aggressive are capital adequacy ratio, return on assets, and financing to deposit ratio
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Abidin, Zaenal, R. Mahelan Prabantarikso, Edian Fahmy, and Amabel Nabila. "Comperative Efficiency using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) in the Banking Industry." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 21 (November 2, 2023): 109–20. http://dx.doi.org/10.37394/23207.2024.21.10.
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This study’s objective is to employ data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to investigate the efficiency accomplishments of Indonesian commercial banking from 2018 to 2019. The first method of measuring efficiency employing a non-parametric data envelopment analysis (DEA) technique reveals that the average efficiency of 71 banks fell from 2018 (0.82) to 2019 (0.81). According to DEA findings, major banks outperform small banks on average. According to the approximated SFA Cobb-Douglas (CD) function, interest expenditure and labor expense have a positive and considerable influence on interest income. This occurs when deposit interest rates rise, banks gain interest revenue by raising lending rates, and banks increase non-interest income. According to the SFA of the Cobb-Douglas function, many banks are inefficient, particularly the first to 49th banks that arise from small banks. The Gamma value is near one (0.999), while the LR test yields a significant result of 36.14. The Cobb-Douglas SFA model is therefore applicable. The efficiency performance findings from the two models above reveal the same thing: large banks are more efficient than small banks.
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Hajduk, Sławomira. "Efficiency evaluation of urban transport using the DEA method." Equilibrium 13, no. 1 (2018): 141–57. http://dx.doi.org/10.24136/eq.2018.008.
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Research background: An efficient and effectively functioning transport of a city is of great importance both for people who reside within it, as well as companies doing business there. It is an integral part of modern economy and society in the dimension of production and consumption. However, apart from having a positive impact, transport also carries many social costs including congestion, traffic accidents and a negative influence on the natural environment. Consequently, urban transport is an increasingly important area of city management.
 Purpose of the article: The aim of this study is to assess the technological effectiveness of transport in selected Polish cities. The author created a ranking of cities and identified ways of improve efficiency.
 Methods: The test procedure used the non-parametric method of Data Envelopment Analysis (DEA). The data for analysis was drawn from the Local Data Bank of the Central Statistical Office defining expenses in the transport section as well as data on the condition and use of transport infrastructure. Calculations were made using Frontier Analyst Application software dedicated to the DEA method. Performance results were determined using the BCC model. The analysis was con-ducted for 18 cities with district status from 150 to 500 thousands inhabitants.
 Findings & Value added: The main result is the author’s ranking of transport effectiveness in Polish cities. The analysis showed that urban transport is characterized by a rather low technological effectiveness. Full technological efficiency has been shown by five cities: Białystok, Sosonowiec, Bielsko-Biała, Olsztyn and Rzeszów. An average of the urban transport efficiency reached 51.1%. The lowest effectiveness was only 2.77%. This means that a substantial number of cities do not use optimal inputs. The DEA method enriches the methodology used by scientists to study transport effectiveness.
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Simonović, Dragoljub, Stefan Milojević, Marko Milašinović, and Mlađan Dimitrijević. "Analysis of the efficiency of banks in Serbia and Montenegro using the DEA method." International Review, no. 3-4 (2023): 184–94. http://dx.doi.org/10.5937/intrev2304181s.
Full textAbstract:
The banking sector of a country plays a crucial role in the overall economy of a nation. The efficiency of banks is a critical factor in assessing their financial performance and competitiveness. The aim of this paper is to measure the relative efficiency of the commercial banks in Serbia and Montenegro by using the non-parametric methodology Data Envelopment Analysis (DEA). The efficiency of banks will be measured using DEA for two models with different input and output variables. The sample consists of banks from Serbia (21) and banks from Montenegro (11) for the period 2017-2022. According to the obtained results, there are four banks that are relatively efficient every year, two from Serbia and two from Montenegro (AIK banka and 3M banka according to the first model and Crnogorska komercijalna banka and Hipotekarna banka according to the second model). The findings from the paper are valuable for further use by regulators, policy makers and bank management who are expected to identify a sustainable business strategy in line with the company's capabilities.
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Tan, Yong, and Dimitris Despotis. "Investigation of efficiency in the UK hotel industry: a network data envelopment analysis approach." International Journal of Contemporary Hospitality Management 33, no. 3 (2021): 1080–104. http://dx.doi.org/10.1108/ijchm-07-2020-0641.
Full textAbstract:
Purpose This paper aims to investigate efficiency in the UK hotel industry and further evaluate the impacts of hotel characteristics and industry environment on efficiency. Design/methodology/approach The network data envelopment (DEA) weak link approach is used for the efficiency analysis, while the determinants of efficiency are evaluated by bootstrapped truncated regression. Findings The findings show that the UK hotel industry is very inefficient. The results of overall efficiency deconstruction show that the second-stage production process experiences an even lower level of efficiency than that of the first stage. The second-phase analysis shows that both the hotel-specific characteristics and the industry-specific characteristics are significantly related to UK hotel efficiency. Research limitations/implications The robustness of the results is affected because a single set of input-intermediate product-outputs and a single DEA method were used. Therefore, further studies can use alternate inputs, intermediate measures and outputs in the efficiency analysis. In addition, the robustness of the efficiency score can be checked using alternate parametric or non-parametric methods. Practical implications Hotels in the UK should focus on cost reduction, business diversification, improvement in the capital level and labor productivity, while at industry and macroeconomic level, discounts are recommended to be provided to international tourism and the tourism industry should be further opened. Originality/value The weak-link approach has been applied to estimate the efficiency level, as this provides more robust and accurate results compared to other non-parametric methods in the existing empirical studies and unique hotel-specific and industry-specific determinants of efficiency are considered in the second-stage analysis.