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• Data_envelopment_analysis abstract "Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. It is used to empirically measure productive efficiency of decision making units (or DMUs). Although DEA has a strong link to production theory in economics, the tool is also used for benchmarking in operations management, where a set of measures is selected to benchmark the performance of manufacturing and service operations. In the circumstance of benchmarking, the efficient DMUs, as defined by DEA, may not necessarily form a “production frontier”, but rather lead to a “best-practice frontier” (Cook, Tone and Zhu, 2014). DEA is referred to as "balanced benchmarking" by Sherman and Zhu (2013).Non-parametric approaches have the benefit of not assuming a particular functional form/shape for the frontier, however they do not provide a general relationship (equation) relating output and input. There are also parametric approaches which are used for the estimation of production frontiers (see Lovell & Schmidt 1988 for an early survey). These require that the shape of the frontier be guessed beforehand by specifying a particular function relating output to input. One can also combine the relative strengths from each of these approaches in a hybrid method (Tofallis, 2001) where the frontier units are first identified by DEA and then a smooth surface is fitted to these. This allows a best-practice relationship between multiple outputs and multiple inputs to be estimated."The framework has been adapted from multi-input, multi-output production functions and applied in many industries. DEA develops a function whose form is determined by the most efficient producers. This method differs from the Ordinary Least Squares (OLS) statistical technique that bases comparisons relative to an average producer. Like Stochastic Frontier Analysis (SFA), DEA identifies a "frontier" on which the relative performance of all utilities in the sample can be compared: DEA benchmarks firms only against the best producers. It can be characterized as an extreme point method that assumes that if a firm can produce a certain level of output utilizing specific input levels, another firm of equal scale should be capable of doing the same. The most efficient producers can form a 'composite producer', allowing the computation of an efficient solution for every level of input or output. Where there is no actual corresponding firm, 'virtual producers' are identified to make comparisons" (Berg 2010)".
• Data_envelopment_analysis wikiPageExternalLink dea2013.huji.ac.il.
• Data_envelopment_analysis wikiPageExternalLink index.php?option=com_content&view=article&id=102&Itemid=70&lang=en.
• Data_envelopment_analysis wikiPageExternalLink j.ejor.2010.07.025.
• Data_envelopment_analysis wikiPageExternalLink j.eswa.2012.08.027.
• Data_envelopment_analysis wikiPageExternalLink j.seps.2007.07.002.
• Data_envelopment_analysis wikiPageExternalLink dea.html.
• Data_envelopment_analysis wikiPageExternalLink abstract=1353122.
• Data_envelopment_analysis wikiPageExternalLink www.deafrontier.net.
• Data_envelopment_analysis wikiPageExternalLink www.deaos.com.
• Data_envelopment_analysis wikiPageExternalLink www.deasoftware.co.uk.
• Data_envelopment_analysis wikiPageExternalLink www.deazone.com.
• Data_envelopment_analysis wikiPageExternalLink DEA-socioEcoPlanning.pdf.
• Data_envelopment_analysis wikiPageExternalLink EJOR_free1.pdf.
• Data_envelopment_analysis wikiPageExternalLink display.php?file=wg_info.php&wgid=17&title=EWG-WS-EPA-WS-Efficiency-WS-and-WS-productivity-WS-analysis&parent=303.
• Data_envelopment_analysis wikiPageExternalLink index.php.
• Data_envelopment_analysis wikiPageExternalLink 2343100.
• Data_envelopment_analysis wikiPageExternalLink principles-of-using-efficiency-measures-for-yardstick-regulation.
• Data_envelopment_analysis wikiPageExternalLink 100296.
• Data_envelopment_analysis wikiPageID "917966".
• Data_envelopment_analysis wikiPageRevisionID "593490740".
• Data_envelopment_analysis date "July 2011".
• Data_envelopment_analysis hasPhotoCollection Data_envelopment_analysis.
• Data_envelopment_analysis reason "what is a production frontier".
• Data_envelopment_analysis subject Category:Operations_research.
• Data_envelopment_analysis comment "Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. It is used to empirically measure productive efficiency of decision making units (or DMUs). Although DEA has a strong link to production theory in economics, the tool is also used for benchmarking in operations management, where a set of measures is selected to benchmark the performance of manufacturing and service operations.".
• Data_envelopment_analysis label "Análise por envoltória de dados".
• Data_envelopment_analysis label "Data Envelopment Analysis".
• Data_envelopment_analysis label "Data envelopment analysis".
• Data_envelopment_analysis label "Data-Envelopment-Analysis".
• Data_envelopment_analysis label "Анализ среды функционирования".
• Data_envelopment_analysis label "数据包络分析".
• Data_envelopment_analysis sameAs Data-Envelopment-Analysis.
• Data_envelopment_analysis sameAs Data_Envelopment_Analysis.
• Data_envelopment_analysis sameAs Análise_por_envoltória_de_dados.
• Data_envelopment_analysis sameAs m.03pssy.
• Data_envelopment_analysis sameAs Q647974.
• Data_envelopment_analysis sameAs Q647974.
• Data_envelopment_analysis wasDerivedFrom Data_envelopment_analysis?oldid=593490740.
• Data_envelopment_analysis isPrimaryTopicOf Data_envelopment_analysis.