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dc.contributor.authorLiou, James J. H.en_US
dc.contributor.authorTzeng, Gwo-Hshiungen_US
dc.date.accessioned2014-12-08T15:06:49Z-
dc.date.available2014-12-08T15:06:49Z-
dc.date.issued2010-06-01en_US
dc.identifier.issn0020-0255en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.ins.2010.01.025en_US
dc.identifier.urihttp://hdl.handle.net/11536/5352-
dc.description.abstractMarket segmentation is a crucial activity in the present business environment. Data mining is a useful tool for identifying customer behavior patterns in large amounts of data. This information can then be used to help with decision-making in areas such as the airline market. In this study, we use the Dominance-based Rough Set Approach (DRSA) to provide a set of rules for determining customer attitudes and loyalties, which can help managers develop strategies to acquire new customers and retain highly valued ones. A set of rules is derived from a large sample of international airline customers, and its predictive ability is evaluated. The results, as compared with those of multiple discriminate analyses, are very encouraging. They prove the usefulness of the proposed method in predicting the behavior of airline customers. This study demonstrates that the DRSA model helps to identify customers, determine their characteristics, and facilitate the development of a marketing strategy. (C) 2010 Elsevier Inc. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectDominanceen_US
dc.subjectRough seten_US
dc.subjectCustomer behavioren_US
dc.subjectData miningen_US
dc.subjectMarketing strategyen_US
dc.titleA Dominance-based Rough Set Approach to customer behavior in the airline marketen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.ins.2010.01.025en_US
dc.identifier.journalINFORMATION SCIENCESen_US
dc.citation.volume180en_US
dc.citation.issue11en_US
dc.citation.spage2230en_US
dc.citation.epage2238en_US
dc.contributor.department科技管理研究所zh_TW
dc.contributor.departmentInstitute of Management of Technologyen_US
dc.identifier.wosnumberWOS:000276819200012-
dc.citation.woscount32-
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