Demand forecasting for multigenerational products combining discrete choice and dynamics of diffusion under technological trajectories

Cited 37 time in webofscience Cited 0 time in scopus
  • Hit : 413
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKim, Wonjoonko
dc.contributor.authorLee, JDko
dc.contributor.authorKim, TYko
dc.date.accessioned2009-12-28T02:42:16Z-
dc.date.available2009-12-28T02:42:16Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2005-09-
dc.identifier.citationTECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, v.72, pp.825 - 849-
dc.identifier.issn0040-1625-
dc.identifier.urihttp://hdl.handle.net/10203/15871-
dc.description.abstractThe discrete choice model generally captures consumers' valuation of the product's quality within the framework of a cross-sectional analysis, while the diffusion model captures the dynamics of demand within the framework of a time-series analysis. We propose an adjusted discrete choice model that incorporates the choice behavior of the consumer into the dynamics of product diffusion. In addition, a new estimation structure is proposed, within the framework of the time-series analysis, which enables the estimation of the discrete choice model on market-level data to be performed in such a way as to avoid the problem of price endogeneity and to obtain greater flexibility in forecasting demand. As an empirical application, the suggested model is applied to the case of the worldwide DRAM (dynamic random access memory) market. In forecasting future demand of DRAM generations, we integrate Moore's law and learning by doing to reflect the future technological trajectories of DRAM innovations, as well as consumers' consumption trends to reflect the dynamics of demand environments. As a result, the suggested model shows better performance in explaining the diffusion of new-generation product with limited number of data observations. (c) 2003 Elsevier Inc. All rights reserved.-
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherELSEVIER SCIENCE INC-
dc.subjectSUCCESSIVE GENERATIONS-
dc.subjectSEMICONDUCTOR INDUSTRY-
dc.subjectMODEL-
dc.subjectSUBSTITUTION-
dc.subjectDRAMS-
dc.titleDemand forecasting for multigenerational products combining discrete choice and dynamics of diffusion under technological trajectories-
dc.typeArticle-
dc.identifier.wosid000231304100006-
dc.identifier.scopusid2-s2.0-22644447053-
dc.type.rimsART-
dc.citation.volume72-
dc.citation.beginningpage825-
dc.citation.endingpage849-
dc.citation.publicationnameTECHNOLOGICAL FORECASTING AND SOCIAL CHANGE-
dc.identifier.doi10.1016/j.techfore.2003.09.003-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorKim, Wonjoon-
dc.contributor.nonIdAuthorLee, JD-
dc.contributor.nonIdAuthorKim, TY-
dc.type.journalArticleArticle-
dc.subject.keywordAuthormultigeneration product-
dc.subject.keywordAuthordiscrete choice-
dc.subject.keywordAuthordiffusion-
dc.subject.keywordAuthorMoore&apos-
dc.subject.keywordAuthors law-
dc.subject.keywordAuthorlearning by doing-
dc.subject.keywordPlusSUCCESSIVE GENERATIONS-
dc.subject.keywordPlusSEMICONDUCTOR INDUSTRY-
dc.subject.keywordPlusMODEL-
dc.subject.keywordPlusSUBSTITUTION-
dc.subject.keywordPlusDRAMS-
Appears in Collection
MG-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 37 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0