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dc.contributor.authorJeeva, Ananda
dc.contributor.authorGuo, W.
dc.contributor.editorYang Xiang, Javier Lopez and Haining Wang
dc.date.accessioned2017-01-30T11:14:23Z
dc.date.available2017-01-30T11:14:23Z
dc.date.created2010-03-23T20:02:49Z
dc.date.issued2009
dc.identifier.citationJeeva, Ananda and Guo, William. 2009. Determining supply chain flexibility using statistics and neural networks: a comparative study, in Yang Xiang, Javier Lopez and Haining Wang (ed), International Conference on Network and System Security, Oct 19 2009, pp. 506-509. Gold Coast, Queensland, Australia: Conference Publishing Services.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/9696
dc.identifier.doi10.1109/NSS.2009.87
dc.description.abstract

The purpose of this paper is to examine the application of neural networks as a flexibility andperformance measure in supplier-manufacturer activities. The dimensions of information exchange,supplier integration, product delivery, logistics, and organisational structure are used as determinantsfactors affecting this supply chain flexibility. The data set was collected from more than 200 Australianmanufacturing firms evaluating their suppliers. Our study shows that neural networks can accuratelydetermine a supplier's flexibility with an error within 1%, which is more accurate than the conventional multivariate regression can.

dc.publisherConference Publishing Services
dc.subjectneural network
dc.subjectsupply chain
dc.subjectmultivariate regression
dc.subjectflexibility
dc.titleDetermining supply chain flexibility using statistics and neural networks: a comparative study
dc.typeConference Paper
dcterms.source.startPage506
dcterms.source.endPage509
dcterms.source.titleProceedings of the network and system security 2009
dcterms.source.seriesProceedings of the network and system security 2009
dcterms.source.isbn9780769538389
dcterms.source.conferenceNetwork and system security 2009
dcterms.source.conference-start-dateOct 19 2009
dcterms.source.conferencelocationGold Coast, Queensland, Australia
dcterms.source.placeLos Alamitos, California USA
curtin.note

Copyright © 2009 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

curtin.accessStatusOpen access
curtin.facultyCurtin Business School
curtin.facultySchool of Information Systems


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