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dc.contributor.authorHuang, Chi-Yoen_US
dc.contributor.authorYang, Ya-Lanen_US
dc.contributor.authorTzeng, Gwo-Hshiungen_US
dc.contributor.authorYu, Hsiao-Chengen_US
dc.contributor.authorLee, Hong-Yuhen_US
dc.contributor.authorCheng, Shih-Tsunsgen_US
dc.contributor.authorLo, Sang-Yengen_US
dc.date.accessioned2017-04-21T06:50:02Z-
dc.date.available2017-04-21T06:50:02Z-
dc.date.issued2010en_US
dc.identifier.isbn978-3-642-14615-2en_US
dc.identifier.issn2190-3018en_US
dc.identifier.urihttp://hdl.handle.net/11536/134398-
dc.description.abstractConsumer behavior analysis and prediction are both important for marketers in general and high technology marketers in special. At the moment of fast evolutions of high technology products, precise predictions of consumer behaviors can serve as the foundation of product/specification definitions. Traditionally, qualitative approaches (e.g. brain storming) or multivariate statistical (e.g. principal component analysis, factor analysis, etc.) were applied widely on consumer behavior analysis. However, the qualitative methods can be objective while the statistical approaches could be hard to be manipulated. Thus, a rule-based prediction method can be very helpful for analyzing and predicting consumer behavior. Moreover, precise prediction rules for consumer behavior being derived by the forecast mechanism can be very useful for marketers and designers to define the features of the products. Therefore, this research intends to define a Cluster Analysis (CA), Rough Set Theory (RST), flow graph (FG) and formal concept analysis (FCA) based forecast mechanism for predicting segmental consumer behavior. An empirical study on 124 Taiwanese 4G handset users was leveraged for verifying the feasibility of the proposed forecast mechanism. The empirical study results demonstrate the feasibility of this proposed framework. Meanwhile, the proposed consumer behavior forecast mechanism can be leveraged on defining features of other high technology products/services.en_US
dc.language.isoen_USen_US
dc.subject4Gen_US
dc.subjectMobile phoneen_US
dc.subjectConsumer behavioren_US
dc.subjectRough Set Theory (RST)en_US
dc.subjectFormal Concept Analysis (FCA)en_US
dc.subjectFlow Graph (FG)en_US
dc.titleDerivations of Factors Influencing Segmental Consumer Behaviors Using the RST Combined with Flow Graph and FCAen_US
dc.typeProceedings Paperen_US
dc.identifier.journalADVANCES IN INTELLIGENT DECISION TECHNOLOGIESen_US
dc.citation.volume4en_US
dc.citation.spage687en_US
dc.citation.epage+en_US
dc.contributor.department科技管理研究所zh_TW
dc.contributor.departmentInstitute of Management of Technologyen_US
dc.identifier.wosnumberWOS:000292845100067en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper