Full metadata record
DC FieldValueLanguage
dc.contributor.authorChern, Yuchingen_US
dc.contributor.authorTzeng, Gwo-Hshiungen_US
dc.date.accessioned2014-12-08T15:33:16Z-
dc.date.available2014-12-08T15:33:16Z-
dc.date.issued2012en_US
dc.identifier.isbn978-1-4673-2056-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/23147-
dc.description.abstractCustomer store loyalty is one of the most important motivations that facilitate the intentions of repatronizing a retailer's website and create marketing values for firms. Research on survey-based for measuring consumers' loyalty to persist in online shopping environment has been developed. But while the measured values of human perceptions towards various attributes are often uncertain data, most conventional measurement methods could not precisely clarify the incomplete information by numerical format. Thus, this paper focused on employing the proposed fuzzy multiple attribute decision making (FMADM) model to cope with this issues within context of B2C retailer loyalty construct. First, the analytic network process (ANP) will be used for determining the relative importance weights for each attributes and identifying key factors that promote B2C loyalty. Second, the logic of triangular fuzzy numbers will be leveraged to transform the satisfaction level of consumers into explicit numbers. Further, considering the complex characteristic between attributes that interdependently interact with one another, we applied the addictive simple weighted aggregation and the non-addictive type fuzzy integral to obtain the fuzzy synthetic utility measures representing for loyalty level and assess the alternatives. In this paper, an empirical case assessed the consumer loyalty towards three Taiwanese B2C e-commerce websites will demonstrate the feasibility of this approach. In addition, we validated the satisfactory degree of a new elements of Personalized Product Recommendations (PPRs) attribute in B2C e-retailing in subject of online marketing by FMADM. In the evaluation process, five main antecedents of B2C retailing services loyalty are obtained and the fuzzy synthetic utility scores are measured for loyalty ranking of the case companies. The results also revealed the different ranking result derived from simple aggregation method and from non-addictive perspective of multiple attributes utility. The multi-attributes consumers' loyalty key measures derived from this study could further support decision making in B2C e-retailing and provide strategic directions to service innovation in markets.en_US
dc.language.isoen_USen_US
dc.subjectfuzzy integralen_US
dc.subjectanalytic network process (ANP)en_US
dc.subjectlinguistic variableen_US
dc.subjectB2C retailing e-loyaltyen_US
dc.subjectpersonalized recommendations (PPRs)en_US
dc.subjectmultiple attributes decision making (MADM)en_US
dc.titleMeasuring Consumer Loyalty of B2C e-Retailing Service by : a FANP-Based Synthetic Modelen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2012 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY2012)en_US
dc.citation.spage48en_US
dc.citation.epage56en_US
dc.contributor.department科技管理研究所zh_TW
dc.contributor.departmentInstitute of Management of Technologyen_US
dc.identifier.wosnumberWOS:000326810700008-
Appears in Collections:Conferences Paper