Please use this identifier to cite or link to this item: https://doi.org/10.1057/palgrave.jors.2602006
DC FieldValue
dc.titleKnowledge acquisition and revision using neural networks: An application to a cross-national study of brand image perception
dc.contributor.authorSetiono, R.
dc.contributor.authorPan, S.-L.
dc.contributor.authorHsieh, M.-H.
dc.contributor.authorAzcarraga, A.
dc.date.accessioned2013-07-11T10:08:15Z
dc.date.available2013-07-11T10:08:15Z
dc.date.issued2006
dc.identifier.citationSetiono, R., Pan, S.-L., Hsieh, M.-H., Azcarraga, A. (2006). Knowledge acquisition and revision using neural networks: An application to a cross-national study of brand image perception. Journal of the Operational Research Society 57 (3) : 231-240. ScholarBank@NUS Repository. https://doi.org/10.1057/palgrave.jors.2602006
dc.identifier.issn01605682
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/42398
dc.description.abstractA three-tier knowledge management approach is proposed in the context of a cross-national study of car brand and corporate image perceptions. The approach consists of knowledge acquisition, transfer and revision using neural networks. We investigate how knowledge acquired by a neural network from one car market can be exploited and applied in another market. This transferred knowledge is subsequently revised for application in the new market. Knowledge revision is achieved by re-training the neural network. Core knowledge common to both markets is retained while some localized knowledge components are introduced during network re-training. Since the knowledge acquired by a neural network can be expressed as an accurate set of simple rules, we are able to compare the knowledge extracted from one network with the knowledge extracted from another. Comparison of the originally acquired knowledge with the revised knowledge provides us with insights into the commonalities and differences in car brand and corporate perceptions across national markets. © 2006 Operational Research Society Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1057/palgrave.jors.2602006
dc.sourceScopus
dc.subjectGlobal brand image perceptions
dc.subjectKnowledge revision
dc.subjectKnowledge transfer
dc.subjectNeural networks
dc.typeArticle
dc.contributor.departmentINFORMATION SYSTEMS
dc.description.doi10.1057/palgrave.jors.2602006
dc.description.sourcetitleJournal of the Operational Research Society
dc.description.volume57
dc.description.issue3
dc.description.page231-240
dc.description.codenJORSD
dc.identifier.isiut000235621600001
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

4
checked on Apr 5, 2020

WEB OF SCIENCETM
Citations

4
checked on Mar 25, 2020

Page view(s)

80
checked on Mar 31, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.