Relevant bibliographies by topics / Data envelopment analysis (DEA)

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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  6. Reports

Academic literature on the topic 'Data envelopment analysis (DEA)'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 September 2023

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Journal articles on the topic "Data envelopment analysis (DEA)"

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Schumacher, Christin. "Data Envelopment Analysis (DEA)." Controlling 25, no. 6 (2013): 336–37. http://dx.doi.org/10.15358/0935-0381_2013_6_336.

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Bhat, Ramesh, Bharat Bhushan Verma, and Elan Reuben. "Data Envelopment Analysis (DEA)." Journal of Health Management 3, no. 2 (October 2001): 309–28. http://dx.doi.org/10.1177/097206340100300207.

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Pereira, José Veiga. "Data Envelopment Analysis." Review of Business and Legal Sciences, no. 6 (July 5, 2017): 29. http://dx.doi.org/10.26537/rebules.v0i6.811.

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A avaliação das organizações e a deterntinação da performance obtida pelo exercício da gestão, tem sido uma preocupação constante de gestores e accionistas, embora com objectivos diversos. Nos dias de hoje, a questão coloca-se com maior acuidade quer pela competitividade acrescida quer pela dimensão e complexidade actual das empresas. Pretendemos com este trabalho fazer uma descrição da metodologia DEA - Data Envelopment Analysis - nas suas formulações iniciais mais simples. A metodologia do DEA, pretende obter uma medida única e simples de avaliação da eficiência, combinando um conjunto de outputs e de inputs relativos às diferentes unidades homogéneas que se pretendem avaliar.O método DEA é um método não paramétrico que pelas suas características é particularmente adequado à avaliação de unidades homogéneas não necessariamente lucrativas.Concluímos, em geral, que são úteis e constituem um avanço importante, as informações obtidas através do DEA mas que outros métodos, designadamente rácios e análises de regressão, podem dar um contributo importante para complementar aquela análise.
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Shewell, Patricia, and Stephen Migiro. "Data envelopment analysis in performance measurement: a critical analysis of the literature." Problems and Perspectives in Management 14, no. 3 (November 10, 2016): 705–13. http://dx.doi.org/10.21511/ppm.14(3-3).2016.14.

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This study examines the benefits of data envelopment analysis (DEA) in evaluating the performance of decision making units (DMUs). DEA is a mathematical programming tool applied in performance measurement. The problem identified is establishing business support units as value adding business units. A case is made for applying DEA when evaluating the performance of such business support units. To this end, a literature review of the results of applications of DEA to the evaluation of information technology and purchasing supply chain management functions was conducted. The findings indicate the benefits of DEA are that the method identifies efficient performers in a given population and, therefore, allows for benchmarking against the ’best in class’ performer. This as opposed to more commonly used parametric methods, such as regression analysis, which result in a comparator that represents the average performance for a given population, therefore, allowing only for measurement against the average. In addition, the findings indicate that in respect of business support units, the DEA methodology allows for the incorporation of intermediate outcomes, which facilitates the measurement of the contribution of these units to overall company performance. Although the DEA methodology has been widely applied, it is still not as well known or generally applied as the more common approaches. The recommendations made in this paper will be beneficial in bringing DEA to the attention of decision-makers. The recommendations will also raise awareness of the potential benefits to be realised when applying the method in developing performance measurement frameworks for business support units. Keywords: performance measurement, data envelopment analysis, decision making units, business support units. JEL Classification: C61, L25
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Ji, Aibing, Hui Liu, Hong-jie Qiu, and Haobo Lin. "Data envelopment analysis with interactive variables." Management Decision 53, no. 10 (November 16, 2015): 2390–406. http://dx.doi.org/10.1108/md-11-2014-0631.

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Purpose – The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs). Design/methodology/approach – Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs. Findings – It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model. Practical implications – The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs. Originality/value – This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.
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Golpîra, Hêriş. "A Hybrid Clustering Method Using Balanced Scorecard and Data Envelopment Analysis." International Journal Of Innovation And Economic Development 1, no. 7 (2015): 15–25. http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.17.2002.

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This paper introduces a new hybrid clustering method using Data Envelopment Analysis (DEA) and Balanced Scorecard (BSC) methods. DEA cannot identify its’ input and output itself, and it is a major weakness of the DEA. In the proposed method, this gap is resolved by integrating DEA with BSC. Some decision-making units (DMUs) needed in DEA method, in compliance with some inputs and outputs is the major drawback of this integration. To deal with this disadvantage, the proposed method selects the most important strategic factors, attained from the BSC method. These data considered to be the input data for the DEA method to calculate relative closeness (RC) of each DMU to the ideal one. Plotting the screen diagram regarding RC index leads us to the final clustering method. Finally, computational results show the applicability and usefulness of the method.
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Li, Ling, and Fengshan Wang. "Hybrid Dynamic Network Data Envelopment Analysis." Discrete Dynamics in Nature and Society 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/989581.

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Conventional DEA models make no hypothesis concerning the internal operations in a static situation. To open the “black box” and work with dynamic assessment issues synchronously, we put forward a hybrid model for evaluating the relative efficiencies of a set of DMUs over an observed time period with a composite of network DEA and dynamic DEA. We vertically deal with intermediate products between divisions with assignable inputs in the network structure and, horizontally, we extend network structure by means of a dynamic pattern with unrelated activities between two succeeding periods. The hybrid dynamic network DEA model proposed in this paper enables us to (i) pry into the internal operations of DEA by another network structure, (ii) obtain dynamic change of period efficiency, and (iii) gain the overall dynamic efficiency of DMUs over the entire observed periods. We finally illustrate the calculation procedure of the proposed approach by a numerical example.
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WEI, QUANLING, HONG YAN, and LIYONG PANG. "COMPOSITE NETWORK DATA ENVELOPMENT ANALYSIS MODEL." International Journal of Information Technology & Decision Making 10, no. 04 (July 2011): 613–33. http://dx.doi.org/10.1142/s0219622011004488.

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This paper extends the DEA model to considering the decision-making unit (DMU) with the network structure. We define the network DMU and its network DEA efficiency based on the postulate system. On the series structure of the DMU, we further discuss a sequential optimization model originally proposed by Sexton and Lewis.1,2 Based on their work, we extend to the DMU with general network of k stages and propose a composite network DEA model which evaluate the network DEA efficiency by solving only one linear programming. We show that the network efficiency obtained from the composite model is equivalent to that obtained by the sequential optimization model. We show that a network DMU is network-efficient if and only if it is efficient at all stages. That is, the network-efficient DMU follows the "Bellman Optimal Principle." Our model shows that if a network DMU is not DEA-efficient, then it is not efficient at one stage at least. We also define the projection of the network DMU on the corresponding production possibility set of network DMUs. Finally, we discuss other basic structures of the network DMU and show that the overall network DEA model can be extended to the general network DMU.
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UEDA, Toru. "Data Envelopment Analysis and Fuzzy DEA." Journal of Japan Society for Fuzzy Theory and Systems 10, no. 2 (1998): 193–99. http://dx.doi.org/10.3156/jfuzzy.10.2_13.

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Oral, Muhittin. "E-DEA: Enhanced data envelopment analysis." European Journal of Operational Research 207, no. 2 (December 2010): 916–26. http://dx.doi.org/10.1016/j.ejor.2010.05.035.

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Dissertations / Theses on the topic "Data envelopment analysis (DEA)"

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Radomski, Błażej. "Fusionen deutscher Sparkassen : eine Anwendung der Data-envelopment-Analysis (DEA) /." Hamburg : Kovač, 2008. http://d-nb.info/988938782/04.

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Ashoor, Khalil Layla Ali. "Performance analysis integrating data envelopment analysis and multiple objective linear programming." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/performance-analysis-integrating-data-envelopment-analysis-and-multiple-objective-linear-programming(65485f28-f6c5-4eff-b422-6dd05f1b46fe).html.

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Firms or organisations implement performance assessment to improve productivity but evaluating the performance of firms or organisations may be complex and complicated due to the existence of conflicting objectives. Data Envelopment Analysis (DEA) is a non-parametric approach utilized to evaluate the relative efficiencies of decision making units (DMUs) within firms or organizations that perform similar tasks. Although DEA measures the relative efficiency of a set of DMUs the efficiency scores generated do not consider the decision maker’s (DM’s) or expert preferences. DEA is used to measure efficiency and can be extended to include DM’s and expert preferences by incorporating value judgements. Value judgements can be implemented by two techniques: weight restrictions or constructing an equivalence Multiple Objective Linear Programming (MOLP) model. Weight restrictions require prior knowledge to be provided by the DM and moreover the DM cannot interfere during the assessment analysis. On the other hand, the second approach enables the DM to interfere during performance assessment without prior knowledge whilst providing alternative objectives that allow the DM to reach the most preferred decision subject to available resources. The main focus of this research was to establish interactive frameworks to allow the DM to set targets, according to his preferences, and to test alternatives that can realistically be measured through an interactive procedure. These frameworks are based on building an equivalence model between extended DEA and MOLP minimax formulation incorporating an interactive procedure. In this study two frameworks were established. The first is based on an equivalence model between DEA trade-off approach and MOLP minimax formulation which allows for incorporating DM’s and expert preferences. The second is based on an equivalence model between DEA bounded model and MOLP minimax formulation. This allows for integrating DM’s preferences through interactive steps to measure the whole efficiency score (i.e. best and worst efficiency) of individual DMU. In both approaches a gradient projection interactive approach is implemented to estimate, regionally, the most preferred solution along the efficient frontier. The second framework was further extended by including ranking based on the geometric average. All the frameworks developed and presented were tested through implementation on two real case studies.
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CARMO, Cinthya Melo do. "Avaliação da Eficiência Técnica das Empresas de Saneamento Brasileiras Utilizando a Metodologia DEA." Universidade Federal de Pernambuco, 2003. https://repositorio.ufpe.br/handle/123456789/5836.

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Made available in DSpace on 2014-06-12T17:42:06Z (GMT). No. of bitstreams: 2 arquivo7386_1.pdf: 425635 bytes, checksum: 9de5460b11e129c770e1c77bc83f93ae (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2003
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Atualmente, o setor de saneamento básico brasileiro está passando por estudos para modernização das empresas responsáveis pelos serviços d água e captação de esgoto nos âmbitos regionais, estaduais e municipais, a fim de mapear, conhecer a qualidade, amplitude e eficiência desses serviços. Essa dissertação determinou o grau de eficiência técnica das 26 companhias estaduais de saneamento básico, através da metodologia DEA - Análise Envoltória de Dados (Data Envelopment Analysis), cuja metodologia baseia-se em procedimentos de programação matemática e possibilita a obtenção de uma fronteira não-paramétrica de eficiência. O procedimento selecionado para assegurar um resultado satisfatório foi à aplicação do software Analyst Frontier, com o propósito de avaliar a eficiência. Nesse sentido, é apresentada uma visão geral do tema e objetivos seguido por um estudo detalhado do setor de saneamento brasileiro e das fronteiras de produção e eficiência produtiva. Para isso, foram escolhidos os modelos a serem utilizados, a amostra, os inputs e output para aplicação às empresas do setor de saneamento. Finalmente são apresentados os escores de eficiência obtidos nos modelos DEA, os quais foram analisados segundo os critérios de localização, retornos de escalas e indicadores técnicos. As companhias estaduais de saneamento básico, de um modo geral apresentaram bons resultados nos dois modelos DEA. Entretanto, observou-se que, a ineficiência técnica foi mais expressiva que a ineficiência de escala
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Diagne, Djily. "La performance des écoles de maturité suisses romandes : une évaluation par la méthode DEA /." [S.l.] : [s.n.], 2003. http://aleph.unisg.ch/hsgscan/hm00074577.pdf.

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Jardim, João Pedro Fernandes. "Airports efficiency evaluation based on MCDA and DEA multidimensional tools." Master's thesis, Universidade da Beira Interior, 2012. http://hdl.handle.net/10400.6/2011.

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Airport benchmarking depends on airport operational performance and efficiency indicators, which are important issues for business, operational management, regulatory agencies, airlines and passengers. There are several sets of single and complex indicators to evaluate airports efficiency as well as several techniques to benchmark such infrastructures. The general aim of this work is the development of airport performance and efficiency predictive models using robust but flexible methodologies and incorporating simultaneously traditional indicators (number of movements and passengers, tons of cargo, number of runways and stands, area of terminals both of passenger and cargo) as well as new constraints as emerging situations and/or sudden natural phenomenon (ramp accidents and incidents, and volcano ashes and weather constraints, respectively). Firstly this work shows the efficiency evaluation of either a set of airports or the same airport along several years and under several constraints based on two multidimensional tools, Multicriteria Decision Analysis (MCDA, particularly through Measuring Attractiveness by a Categorical Based Evaluation Technique - MACBETH) and Data Envelopment Analysis (DEA). Secondly this work compares the obtained results using both MACBETH and DEA evidencing pros and cons of each multidimensional tool and searching for the best conditions to apply one or the other within airport management decision processes.
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Wilkinson, Robert H. "The measurement of university performance using concepts derived from data envelopment analysis (DEA)." Thesis, University of Stirling, 1991. http://hdl.handle.net/1893/2113.

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Performance measurement in higher education is examined during this study, in particular university performance indicators are reviewed and discussed. The conclusion is made that appropriate input and output indicators require some form of combination in order to allow practical consideration to be made. The technique of Data Envelopment Analysis (DEA) is reviewed and found to have a number of conceptual drawbacks. The model is considerably developed within the thesis, primarily by the introduction of weight restrictions on the variables. Taken as a whole the developments, coined the DEAPMAS process, create a technique which can be used to assess cost effectiveness rather than simply efficiency. Data for two examples of subject areas, defined by recognised accounting units, are applied to the program as inter-university comparison was felt to be impractical at institutional level; due to differing subject mixes. A considerable computer implementation of the developed theory was written and utilised to provide results over a number of data runs for the examples. It was concluded that the results obtained represented a considerable improvement over separate consideration of numerous performance indicators.
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LeBel, Luc. "Performance and efficiency evaluation of logging contractors using data envelopment analysis." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-06062008-152114/.

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Ozpeynirci, Nail Ozgur. "New Approaches For Performance Evaluation Using Data Envelopment Analysis." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12604977/index.pdf.

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Data Envelopment Analysis (DEA) assigns efficiency values to decision making units (DMU) in a given period by comparing the outputs with the inputs. In many applications, inputs and outputs of DMUs are monitored over time. There might be a time lag between the consumption of inputs and production of outputs. We develop approaches that aim to capture the time lag between the outputs and the inputs in assigning the efficiency values to DMUs. We present computational results on randomly generated problems as well as on an application to R&
D institutes of the Scientific and Technical Research Council of Turkey (TÜ
BiTAK).
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Hjalmarsson, Victoria. "Värdeflödesanalys och Data Envelopment Analysis : En fallstudie för att värdera effektiviteten hos ett logistikföretag." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-28011.

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Companies face new challenges almost every day. In order to stay competitive, it is important that companies strive for continuous development and improvement. By describing companies through their processes it is possible to get a clear overview of the entire operation, which can contribute, to a well-established overall understanding of the company. This is a case study based on Stort AB which is a small logistics company specialized in international transportation and logistics solutions. The purpose of this study is to perform value stream mapping in order to create a more efficient production process and propose possible improvements in order to reduce processing time. After performing value stream mapping, data envelopment analysis is used to calculate how lean Stort AB is today and how lean the company can become by implementing the proposed improvements. The results show that the production process can improve efficiency by minimizing waste produced by a bad workplace layout and over-processing. The authors suggested solution is to introduce standardized processes and invest in technical instruments in order to automate the process to reduce process time. According to data envelopment analysis the business is 41 percent lean at present and may soon become 55 percent lean and finally reach an optimum 100 percent lean mode if the process is automated.
Företag står idag inför ständigt nya utmaningar. För att behålla sin konkurrenskraft är det viktigt att företag ständigt utvecklas och förbättras. Att beskriva företag genom deras processer och kartlägga alla flöden som genomströmmar företaget så uppstår en tydlig överblick över hela verksamheten som bidrar till en bra helhetsförståelse av företaget. Denna studie baseras på en fallstudie hos Stort AB som är ett mindre logistikföretag med specialisering på internationella transporter och logistiklösningar. Syftet med studien är att utföra en värdeflödesanalys med mål att effektivisera pakethanteringen och föreslå möjliga förändringsalternativ hur Stort AB kan effektivisera den befintliga pakethanteringen med fokus på tidsreducering. Efter värdeflödesanalysen användes data envelopment analysis för att beräkna hur lean verksamheten är idag och hur lean verksamheten kan bli genom förbättringsförslagen. Resultaten visar att pakethanteringen kan effektiviseras genom att minimera slöseri i form av onödiga rörelser och överbearbetning, införa standardiserade processer och genom att investera i teknik för att automatisera processen. Enligt beräkningar är verksamheten 41 procent lean i nuläget och kan inom kort framtid bli 55 procent lean och slutligen nå ett optimalt 100 procentigt lean-läge om pakethanteringen automatiseras.
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Kabnurkar, Amit. "Mathematical Modeling for Data Envelopment Analysis with Fuzzy Restrictions on Weights." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/31992.

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Data envelopment analysis (DEA) is a relative technical efficiency measurement tool, which uses operations research techniques to automatically calculate the weights assigned to the inputs and outputs of the production units being assessed. The actual input/output data values are then multiplied with the calculated weights to determine the efficiency scores. Recent variants of the DEA model impose upper and lower bounds on the weights to eliminate certain drawbacks associated with unrestricted weights. These variants are called weight restriction DEA models. Most weight restriction DEA models suffer from a drawback that the weight bound values are uncertain because they are determined based on either incomplete information or the subjective opinion of the decision-makers. Since the efficiency scores calculated by the DEA model are sensitive to the values of the bounds, the uncertainty of the bounds gets passed onto the efficiency scores. The uncertainty in the efficiency scores becomes unacceptable when we consider the fact that the DEA results are used for making important decisions like allocating funds and taking action against inefficient units. In order to minimize the effect of the uncertainty in bound values on the decision-making process, we propose to explicitly incorporate the uncertainty in the modeling process using the concepts of fuzzy set theory. Modeling the imprecision involves replacing the bound values by fuzzy numbers because fuzzy numbers can capture the intuitive conception of approximate numbers very well. Amongst the numerous types of weight restriction DEA models developed in the research, two are more commonly used in real-life applications compared to the others. Therefore, in this research, we focus on these two types of models for modeling the uncertainty in bound values. These are the absolute weight restriction DEA models and the Assurance Region (AR) DEA models. After developing the fuzzy models, we provide implementation roadmaps for illustrating the development and solution methodology of those models. We apply the fuzzy weight restriction models to the same data sets as those used by the corresponding crisp weight restriction models in the literature and compare the results using the two-sample paired t-test for means. We also use the fuzzy AR model developed in the research to measure the performance of a newspaper preprint insertion line.
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Books on the topic "Data envelopment analysis (DEA)"

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Mantri, Jibendu Kumar. Research methodology on data envelopment analysis (DEA). Boca Raton: Universal-Publishers, 2008.

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Başkaya, Sait. Beurteilung der Hochschuleffizienz mittels Data Envelopment Analysis (DEA). Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-30351-8.

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Cooper, William W. Data envelopment analysis: A comprehensive text with models, applications, references, and DEA-Solver software. Boston: Kluwer Academic, 2000.

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DEA furekkusu sōgō hyōkahō: Shakai shisutemu bunseki e no tekiyō. Ibaraki-ken Tsukuba-shi: Tsukuba Daigaku Shuppankai, 2015.

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Cooper, William W. Introduction to data envelopment analysis and its uses: With DEA-solver software and references. New York: Springer, 2005.

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Barr, Richard S. Predicting bank failure using DEA to quantify management quality. [Dallas: Federal Reserve Bank of Dallas, 1994.

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Barr, Richard S. Predicting bank failure using DEA to quantify management quality. [Dallas: Federal Reserve Bank of Dallas, 1994.

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service), SpringerLink (Online, ed. Health Care Benchmarking and Performance Evaluation: An Assessment using Data Envelopment Analysis (DEA). Boston, MA: Springer Science+Business Media, LLC, 2008.

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Cooper, William W. Introduction to data envelopment analysis and its uses: With DEA-solver software and references. New York, NY: Springer, 2006.

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Lars, Otto, ed. Benchmarking with DEA, SFA, and R. New York: Springer, 2011.

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Book chapters on the topic "Data envelopment analysis (DEA)"

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Wen, Meilin. "Stochastic DEA." In Uncertain Data Envelopment Analysis, 61–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43802-2_3.

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Wen, Meilin. "Fuzzy DEA." In Uncertain Data Envelopment Analysis, 83–116. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43802-2_4.

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Wen, Meilin. "Uncertain DEA." In Uncertain Data Envelopment Analysis, 117–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43802-2_5.

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Wen, Meilin. "Hybrid DEA." In Uncertain Data Envelopment Analysis, 139–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43802-2_6.

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Wen, Meilin. "Introduction to DEA." In Uncertain Data Envelopment Analysis, 45–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43802-2_2.

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Bogetoft, Peter, and Lars Otto. "Data Envelopment Analysis DEA." In International Series in Operations Research & Management Science, 81–113. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7961-2_4.

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Kerpen, Philip. "Kritische Diskussion einer DEA-Anwendung." In Praxisorientierte Data Envelopment Analysis, 253–80. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-15460-8_5.

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Sengupta, Jati K. "Theory of DEA Models." In Dynamics of Data Envelopment Analysis, 1–37. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8506-4_1.

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Sengupta, Jati K. "Economic Theory and DEA." In Dynamics of Data Envelopment Analysis, 250–76. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8506-4_7.

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Emrouznejad, Ali, Konstantinos Petridis, and Vincent Charles. "Extensions of DEA Models." In Data Envelopment Analysis with GAMS, 41–73. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-30701-0_3.

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Conference papers on the topic "Data envelopment analysis (DEA)"

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Russo, F., and C. Rindone. "Data Envelopment Analysis (DEA) for evacuation planning." In RISK ANALYSIS 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/risk100391.

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Kuah, Chuen Tse, Kuan Yew Wong, and Farzad Behrouzi. "A Review on Data Envelopment Analysis (DEA)." In 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation. IEEE, 2010. http://dx.doi.org/10.1109/ams.2010.45.

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Zhang, Wenwen. "Performance Evaluation Model Based on Data Envelopment Analysis(DEA)." In 2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2022. http://dx.doi.org/10.1109/iiotbdsc57192.2022.00053.

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Ojaraida, Lolo, Omowumi Iledare, and Adekunle Idowu. "Data Envelopment Analysis DEA of Natural Gas Utilization in Nigeria." In SPE Nigeria Annual International Conference and Exhibition. Society of Petroleum Engineers, 2019. http://dx.doi.org/10.2118/198783-ms.

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Pessanha, José, Alexandre Marinho, Luiz Laurencel, and Marcus Souza. "Teaching data envelopment analysis in undergraduate statistics courses." In Advances in Statistics Education: Developments, Experiences, and Assessments. International Association for Statistical Education, 2015. http://dx.doi.org/10.52041/srap.15313.

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In general the undergraduate curriculum in statistics offers one semester basic course on linear programming (LP). The conventional course on LP includes simplex algorithm, duality theory, sensitivity analysis and some applications like the feedmix and transport problems. This outline seems to be distant from the mainstream curriculum in statistics. In order to partially overcome this shortcoming, we propose to introduce a technique based on linear programming called Data Envelopment Analysis (DEA) on the LP courses for students of statistics. DEA has gained momentum as a powerful complementary method for statistical tools in the research agenda as well as in practical activities of economic efficiency evaluation.
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Huang, Si-chong, Da-cheng Liu, and Zhi-fang Lu. "Measuring efficiency of hand surgery departments using data envelopment analysis(DEA)." In EM2010). IEEE, 2010. http://dx.doi.org/10.1109/icieem.2010.5645985.

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Bay, Alexandra. "Efficiency measurement of Swiss shopping centers using Data Envelopment Analysis (DEA)." In 22nd Annual European Real Estate Society Conference. European Real Estate Society, 2015. http://dx.doi.org/10.15396/eres2015_53.

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Luna, Dolores E., J. Ramon Gil-Garcia, Luis F. Luna-Reyes, Rodrigo Sandoval-Almazán, and Abel Duarte-Valle. "Using data envelopment analysis (DEA) to assess government web portals performance." In the 13th Annual International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2307729.2307748.

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Hastutik, Nadita, and M. Nurzaman. "Efficiency Analysis of Zakat Intitutions in Indonesia by using Data Envelopment Analysis (DEA)." In Proceedings of the 1st International Conference on Economics, Management, Accounting and Business, ICEMAB 2018, 8-9 October 2018, Medan, North Sumatra, Indonesia. EAI, 2019. http://dx.doi.org/10.4108/eai.8-10-2018.2288725.

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Zhou, Chao, and Mingzhe Wang. "The Evaluation Research on Higher Education Efficiency with Data Envelopment Analysis (DEA)." In 2009 International Conference on Management and Service Science (MASS). IEEE, 2009. http://dx.doi.org/10.1109/icmss.2009.5304303.

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Reports on the topic "Data envelopment analysis (DEA)"

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Ahn, T., A. Charnes, and W. W. Cooper. A Note on the Efficiency Characterizations Obtained in Different DEA (data Envelopment Analysis) Models. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada201343.

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Arias, Karla, Segundo Camino-Mogro, Mariana Weiss, David Matías, Yuri Daltro, Franco Carvajal, and Michelle Carvalho Metanias Hallack. Measuring the Efficiency in Energy Distribution Firms in LAC: A Service Provision and Financial Performance Approach. Inter-American Development Bank, December 2022. http://dx.doi.org/10.18235/0004547.

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This study identifies and analyzes the evolution of efficiency in providing services and in the financial performance of the LAC electricity distribution companies between 2014-2020. In addition, it examines firms characteristics that might be related to efficiencies, such as quality of service, corporate governance, firm size, and ownership. This paper uses a twostep procedure. First, it considers the efficiency levels and the total factor productivity (TFP) changes using the Malmquist index and breaks down the total change by relying on a nonparametric data envelopment analysis (DEA) approach. The second stage focuses on the drivers of efficiency obtained in the first stage using the Tobit technique. The main results suggest that there is no significant improvement in the levels of efficiency in the period analyzed in the energy distribution firms in LAC. When analyzing the heterogeneity of a company's efficiency, the evidence shows a relation between companies efficiency and the quality perceived by users, higher efficiency is related to better-perceived quality. Besides, companies characteristics, such as firm size, corporate governance, and ownership, are related to the heterogeneity of efficiency.
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Inman, Oliver. Technology Forecasting Using Data Envelopment Analysis. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2678.

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Nin Pratt, Alejandro, and Héctor Valdés Conroy. After the Boom: Agriculture in Latin America and the Caribbean. Inter-American Development Bank, December 2020. http://dx.doi.org/10.18235/0002955.

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The convergence of a favorable macroeconomic environment and high prices of primary commodities between 2000 and 2011 contributed to the best performance of agriculture in Latin America and the Caribbean (LAC) since the 1980s, with steady growth of total factor productivity (TFP) and output per worker and a reduction in the use of input per worker. The end of the upward phase of the commodity cycle in 2011 together with less favorable external markets and a deterioration of the policy environment in several countries, motivates us to revisit the situation of agriculture in LAC in recent years to analyze how these changes have affected its performance. This study applies a framework that uses index numbers together with data envelopment analysis (DEA) to estimate levels of productivity and efficiency, incorporating technical change together with technical (TE) and environmental efficiency (EE) into the decomposition of TFP. The EE index adjusts the TFP measure for pollution, treating GHG emissions as a by-product of the desired crop or livestock outputs. TFP and efficiency of crop and livestock sub-sectors was calculated for 24 LAC countries from 2000 to 2016. Our results show that the period of fast agricultural growth in LAC, driven by technical change and resource reallocation, transformed agriculture in the region leaving it in a better position to cope with the more unfavorable regional macroeconomic environment and the less dynamic global markets observed after 2011.
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Chapman, Robert E. Using data envelopment analysis to assess performance of manufacturing extension centers. Gaithersburg, MD: National Institute of Standards and Technology, 1998. http://dx.doi.org/10.6028/nist.ir.6198.

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Retzlaff-Roberts, Donna, Jose H. Dula, and James Van Scotter. Classification and Selection for Personnel Applications Using a Data Envelopment Analysis Approach. Fort Belvoir, VA: Defense Technical Information Center, December 2002. http://dx.doi.org/10.21236/ada409042.

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Charnes, A., and L. Neralic. Sensitivity Analysis of the Simultaneous Proportionate Change of Inputs and Outputs in Data Envelopment Analysis. Fort Belvoir, VA: Defense Technical Information Center, August 1991. http://dx.doi.org/10.21236/ada254821.

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Charnes, A., W. W. Cooper, and R. M. Thrall. A Structure for Classifying and Characterizing Efficiencies and Inefficiencies in Data Envelopment Analysis. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada176141.

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Charnes, A. Measuring the Impact of Advertising on Army Recruiting: Data Envelopment Analysis and Advertising Effectiveness. Fort Belvoir, VA: Defense Technical Information Center, July 1990. http://dx.doi.org/10.21236/ada236779.

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Benton, Tereca V. Data Envelopment Analysis to Assess Productivity in the United States Air Force Medical Supply Chain. Fort Belvoir, VA: Defense Technical Information Center, June 2011. http://dx.doi.org/10.21236/ada545186.

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