Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details.
AbstractThe derivation of weights from preference statements is subject to difficulties, some of which are due to the unreliability of the judgement of the decision maker. To overcome this Jaynes' principle of maximum entropy has been invoked and may be applied either to weights or to the linear weighted scores of the candidates in a selection problem. When candidates are relatively few the two strategies give different styles of interaction. These are discussed and illustrated by application to a problem of personnel selection.
. (2014) 'IMP : a decision aid for multiattribute evaluation using imprecise weight estimates. ', Omega., Further information on publisher's website:http://dx.doi.org/10.1016/j.omega.2014.05.001Publisher's copyright statement: NOTICE: this is the author's version of a work that was accepted for publication in Omega. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be re ected in this document. Changes may have been made to this work since it was submitted for publication. A de nitive version was subsequently published in Omega, 49, 2014, 10.1016/j.omega.2014.05.001.
Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.