dc.contributor.author | Mahdiloo, Mahdi | |
dc.contributor.author | Noorizadeh, Abdollah | |
dc.contributor.author | FarzipoorSaen, Reza | |
dc.date.accessioned | 2017-05-03T16:04:59Z | |
dc.date.available | 2017-05-03T16:04:59Z | |
dc.date.issued | 2013 | |
dc.date.modified | 2014-04-02T04:48:30Z | |
dc.identifier.issn | 14680394 | |
dc.identifier.doi | 10.1111/exsy.12011 | |
dc.identifier.uri | http://hdl.handle.net/10072/57762 | |
dc.description.abstract | Data envelopment analysis (DEA) is a mathematical programming technique that is frequently used for measuring and benchmarking efficiency of the homogenous decision-making units (DMUs). This paper proposes a new use of DEA for customers scoring and particularly their direct mailing modelling. Moreover, because DEA models suffer from some weaknesses, that is, unrealistic weighting scheme of the inputs and outputs and incomplete ranking among efficient DMUs, the present paper compares different ways of solving these problems and concludes that common set of weights method, as a result of some advantages, outperforms other procedures. | |
dc.description.peerreviewed | Yes | |
dc.description.publicationstatus | Yes | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Wiley-Blackwell | |
dc.publisher.place | United Kingdom | |
dc.relation.ispartofstudentpublication | Y | |
dc.relation.ispartofpagefrom | 1 | |
dc.relation.ispartofpageto | 9 | |
dc.relation.ispartofjournal | Expert Systems | |
dc.rights.retention | Y | |
dc.subject.fieldofresearch | Artificial Intelligence and Image Processing | |
dc.subject.fieldofresearch | Cognitive Sciences | |
dc.subject.fieldofresearchcode | 0801 | |
dc.subject.fieldofresearchcode | 1702 | |
dc.title | Optimal direct mailing modelling based on data envelopment analysis | |
dc.type | Journal article | |
dc.type.description | C1 - Articles | |
dc.type.code | C - Journal Articles | |
gro.date.issued | 2013 | |
gro.hasfulltext | No Full Text | |
gro.griffith.author | Mahdiloo, Mahdi | |