DBpedia – Linked Data Fragments

Matches in DBpedia 2016-04 for { <http://wikidata.dbpedia.org/resource/Q647974> ?p ?o }

• Q647974 subject Q7013789.
• Q647974 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" which are 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).Attempts to synthesize DEA and SFA, improving upon their drawbacks, were also made in the literature, via proposing various versions of non-parametric SFA and Stochastic DEA.".
• Q647974 wikiPageExternalLink dea2013.huji.ac.il.
• Q647974 wikiPageExternalLink dea.
• Q647974 wikiPageExternalLink j.ejor.2010.07.025.
• Q647974 wikiPageExternalLink j.eswa.2012.08.027.
• Q647974 wikiPageExternalLink j.eswa.2013.08.061.
• Q647974 wikiPageExternalLink j.seps.2007.07.002.
• Q647974 wikiPageExternalLink dea.html.
• Q647974 wikiPageExternalLink abstract=1353122.
• Q647974 wikiPageExternalLink www.deafrontier.net.
• Q647974 wikiPageExternalLink www.deaos.com.
• Q647974 wikiPageExternalLink www.deasoftware.co.uk.
• Q647974 wikiPageExternalLink www.deazone.com.
• Q647974 wikiPageExternalLink DEA-socioEcoPlanning.pdf.
• Q647974 wikiPageExternalLink EJOR_free1.pdf.
• Q647974 wikiPageExternalLink display.php?file=wg_info.php&wgid=17&title=EWG-WS-EPA-WS-Efficiency-WS-and-WS-productivity-WS-analysis&parent=303.
• Q647974 wikiPageExternalLink index.php.
• Q647974 wikiPageExternalLink 2343100.
• Q647974 wikiPageExternalLink index.php?title=Open_Source_DEA.
• Q647974 wikiPageExternalLink principles-of-using-efficiency-measures-for-yardstick-regulation.
• Q647974 wikiPageExternalLink S0038012107000420.
• Q647974 wikiPageExternalLink 100296.
• Q647974 wikiPageExternalLink v174y2006i2p1076-1086.html.
• Q647974 wikiPageExternalLink v238y2014i3p774-785.html.
• Q647974 wikiPageExternalLink v240y2015i1p269-277.html.
• Q647974 wikiPageExternalLink v22y2007i7p1367-1394.html.
• Q647974 wikiPageExternalLink v25y2006i4p497-522.html.
• Q647974 wikiPageWikiLink Q1097688.
• Q647974 wikiPageWikiLink Q1513886.
• Q647974 wikiPageWikiLink Q15733703.
• Q647974 wikiPageWikiLink Q15766418.
• Q647974 wikiPageWikiLink Q15781333.
• Q647974 wikiPageWikiLink Q1744931.
• Q647974 wikiPageWikiLink Q1849855.
• Q647974 wikiPageWikiLink Q1888574.
• Q647974 wikiPageWikiLink Q194292.
• Q647974 wikiPageWikiLink Q202843.
• Q647974 wikiPageWikiLink Q282942.
• Q647974 wikiPageWikiLink Q2912993.
• Q647974 wikiPageWikiLink Q36829.
• Q647974 wikiPageWikiLink Q39072.
• Q647974 wikiPageWikiLink Q5333340.
• Q647974 wikiPageWikiLink Q6294781.
• Q647974 wikiPageWikiLink Q6296171.
• Q647974 wikiPageWikiLink Q6296202.
• Q647974 wikiPageWikiLink Q7013789.
• Q647974 wikiPageWikiLink Q7247859.
• Q647974 wikiPageWikiLink Q7617818.
• Q647974 wikiPageWikiLink Q8019772.
• Q647974 wikiPageWikiLink Q8134.
• Q647974 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.".
• Q647974 label "Data envelopment analysis".