Zobrazit minimální záznam

dc.contributor.authorAmin, Gholam R.
dc.contributor.authorAl-Muharrami, Saeed
dc.contributor.authorToloo, Mehdi
dc.date.accessioned2018-11-12T13:10:32Z
dc.date.available2018-11-12T13:10:32Z
dc.date.issued2019
dc.identifier.citationExpert Systems with Applications. 2019, vol. 115, p. 412-417.cs
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.urihttp://hdl.handle.net/10084/133149
dc.description.abstractThis paper suggests a novel method to deal with target setting in mergers using goal programming (GP) and inverse data envelopment analysis (InvDEA). A conventional DEA model obtains the relative efficiency of decision making units (DMUs) given multiple inputs and multiple outputs for each DMU. However, the InvDEA aims to identify the quantities of inputs and outputs when efficiency score is given as a target. This study provides an effective method that allows decision makers to incorporate their preference in target setting of a merger for saving specific input(s) or producing certain output(s) as much as possible. The proposed method is validated through an illustrative application in banking industry.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesExpert Systems with Applicationscs
dc.relation.urihttp://doi.org/10.1016/j.eswa.2018.08.018cs
dc.rights© 2018 Elsevier Ltd. All rights reserved.cs
dc.subjectdata envelopment analysiscs
dc.subjectgoal programmingcs
dc.subjectinverse data envelopment analysiscs
dc.subjectmergerscs
dc.subjectbanking industrycs
dc.titleA combined goal programming and inverse DEA method for target setting in mergerscs
dc.typearticlecs
dc.identifier.doi10.1016/j.eswa.2018.08.018
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume115cs
dc.description.lastpage417cs
dc.description.firstpage412cs
dc.identifier.wos000448097700029


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