2010
DOI: 10.1016/j.ins.2010.01.025
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A Dominance-based Rough Set Approach to customer behavior in the airline market

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Cited by 125 publications
(36 citation statements)
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“…These attributes are leveraged to devise core classification rules. The success of rough sets in data mining is exemplified by research works for a variety of domains such as medical (Hassanien et al, (Liou & Tzeng, 2010), and Web (Formica, 2012), to cite a few.…”
Section: Rough Set Based Classification Of Service Behaviorsmentioning
confidence: 99%
“…These attributes are leveraged to devise core classification rules. The success of rough sets in data mining is exemplified by research works for a variety of domains such as medical (Hassanien et al, (Liou & Tzeng, 2010), and Web (Formica, 2012), to cite a few.…”
Section: Rough Set Based Classification Of Service Behaviorsmentioning
confidence: 99%
“…The E-spread system is analyzed by the formal context through the concept of covering approximation relationship, which can be extended from the classical RSA (Rough Sets Approach) or DRSA (Dominance-Based Rough Sets Approach) (see [23,24]). Remark 4.5.…”
Section: Remark 44mentioning
confidence: 99%
“…Usage becomes further problematic in business applications as metrics determining value can include variables within the calculative technologies such as age, class, race and gender, which are already seen as important variables in applications of CLV and CRM in both the airline industry (Liou and Tzeng 2010) and commercial banking (Haenlein et al 2007) as these can drive (or decrease) firm value and therefore act as important segmentation variables. Religious affiliation can also become a determinant in CLV calculations, and additionally a factor of customer value.…”
Section: Malevolence Of Customer Managementmentioning
confidence: 99%