Multicriteria decision analysis with minimum information: Combining DEA with MAVT

Mavrotas, G; Trifillis, P

dc.contributor.author	Mavrotas, G	en
dc.contributor.author	Trifillis, P	en
dc.date.accessioned	2014-03-01T01:24:40Z
dc.date.available	2014-03-01T01:24:40Z
dc.date.issued	2006	en
dc.identifier.issn	0305-0548	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17387
dc.subject	Cross-efficiency	en
dc.subject	DEA	en
dc.subject	Multiple criteria	en
dc.subject	Value functions	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Industrial	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Computer system recovery	en
dc.subject.other	Evaluation	en
dc.subject.other	Information analysis	en
dc.subject.other	Sensitivity analysis	en
dc.subject.other	Cross-efficiency	en
dc.subject.other	Data envelopment analysis (DEA)	en
dc.subject.other	Multicriteria decision	en
dc.subject.other	Multicriteria decision analysis (MCDA)	en
dc.subject.other	Value functions	en
dc.subject.other	Decision theory	en
dc.title	Multicriteria decision analysis with minimum information: Combining DEA with MAVT	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.cor.2004.11.023	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.cor.2004.11.023	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	In this paper we use some basic principles from data envelopment analysis (DEA) in order to extract the necessary information for solving a multicriteria decision analysis (MCDA) problem. The proposed method (enhanced alternative cross-evaluation, ACE+) is appropriate when either the decision maker is unwilling (or hardly available) to provide information, or there are several decision makers, each one supporting his/her own option. It is similar to the AXE method of Doyle, but it goes one step further: each alternative uses its most favourable weights (as in AXE) and its most favourable value functions in order to perform a self evaluation, according to multi attribute value theory (MAVT). These self-evaluations are averaged in order to derive the overall peer-evaluation for each alternative. The minimum information required from the decision maker is to define the weight interval for each criterion. Beside the peer evaluation and the final rating of the alternatives, the method provides useful conclusions for the sensitivity analysis of the results. (c) 2004 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Computers and Operations Research	en
dc.identifier.doi	10.1016/j.cor.2004.11.023	en
dc.identifier.isi	ISI:000235584900001	en
dc.identifier.volume	33	en
dc.identifier.issue	8	en
dc.identifier.spage	2083	en
dc.identifier.epage	2098	en