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Brownian agent-based technology forecasting

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dc.contributor.authorShin, Juneseuk-
dc.contributor.authorPark, Yongtae-
dc.date.accessioned2012-03-05T02:32:00Z-
dc.date.available2012-03-05T02:32:00Z-
dc.date.issued2009-10-01-
dc.identifier.citationTECHNOLOGICAL FORECASTING AND SOCIAL CHANGE; Vol.76 8; 1078-1091-
dc.identifier.issn0040-1625-
dc.identifier.urihttps://hdl.handle.net/10371/75358-
dc.description.abstractToday''''''''s innovation process is best characterized by nonlinearity and interaction. Agent-based models build on these concepts, but have not been useful in practice because they are either too complex or too simple to make a good match with reality. As a remedy, we employ a Brownian agent model with intermediate complexity to produce value-added technology forecasting. As an illustration with Korea''''''''s software industry data, computer simulation is carried out. Attracted by higher technology value, agents concentrate on specific technology regions, and form co-existing major technology regions of high density. A rough comparison with actual software production data exhibits a fair reflection of reality, and supports the underlying idea that economic motivation of agents should be considered. (C) 2009 Elsevier Inc. All rights reserved.-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE INC-
dc.subjectBrownian agent-
dc.subjectSoftware industry-
dc.subjectSimulation-
dc.subjectTechnology forecasting-
dc.subjectIntermediate complexity-
dc.titleBrownian agent-based technology forecasting-
dc.typeArticle-
dc.contributor.AlternativeAuthor신준석-
dc.contributor.AlternativeAuthor박용태-
dc.identifier.doi10.1016/j.techfore.2009.04.001-
dc.citation.journaltitleTECHNOLOGICAL FORECASTING AND SOCIAL CHANGE-
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