Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/1241
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dc.contributor.authorPuumalainen, Kaisu-
dc.contributor.authorSundqvist, Sanna-
dc.contributor.authorHuiskonen, Janne-
dc.date.accessioned2008-05-05T11:25:14Z-
dc.date.available2008-05-05T11:25:14Z-
dc.date.issued2007-04-
dc.identifier.issn0022-4456-
dc.identifier.urihttp://hdl.handle.net/123456789/1241-
dc.description299-304en_US
dc.description.abstractThe study presents how adding more independent explaining variables and applying neural networks for forecasting purposes could improve the forecasting accuracy of the diffusion of innovations. The paper proposes a set of uncertainty sources of telecommunications industry that have notable affect on the diffusion of innovations in the field. Diffusion patterns and uncertainty indicators of 81 countries were classified using self-organizing map neural network approach, and the results indicate that various levels and types of uncertainty are likely to produce different types of diffusion patterns.en_US
dc.language.isoen_USen_US
dc.publisherCSIRen_US
dc.sourceJSIR Vol.66(4) [April 2007]en_US
dc.subjectCellular subscriptionsen_US
dc.subjectDiffusion of innovationsen_US
dc.subjectNeural networksen_US
dc.subjectSOMen_US
dc.subjectTelecommunicationsen_US
dc.subjectUncertaintyen_US
dc.titleManaging uncertainty in forecasting the diffusion of telecommunications innovationsen_US
dc.typeArticleen_US
Appears in Collections:JSIR Vol.66(04) [April 2007]

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