Customer satisfaction and loyalty analysis with classification algorithms and Structural Equation Modeling

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dc.contributor.authorAktepe, Adnan
dc.contributor.authorErsoz, Suleyman
dc.contributor.authorToklu, Bilal
dc.date.accessioned2020-06-25T18:13:04Z
dc.date.available2020-06-25T18:13:04Z
dc.date.issued2015
dc.departmentKırıkkale Üniversitesi
dc.descriptionAktepe, Adnan/0000-0002-3340-244X
dc.description.abstractBusinesses can maintain their effectiveness as long as they have satisfied and loyal customers. Customer relationship management provides significant advantages for companies especially in gaining competitiveness. In order to reach these objectives primarily companies need to identify and analyze their customers. In this respect, effective communication and commitment to customers and changing market conditions is of great importance to increase the level of satisfaction and loyalty. To evaluate this situation, level of customer satisfaction and loyalty should be measured correctly with a comprehensive approach. In this study, customers are investigated in 4 main groups according to their level of satisfaction and loyalty with a criteria and group based analysis with a new method. We use classification algorithms in WEKA programming software and Structural Equation Modeling (SEM) with LISREL tools together to analyze the effect of each satisfaction and loyalty criteria in a satisfaction-loyalty matrix and extend the customer satisfaction and loyalty post-analysis research bridging the gap in this field of research. To convert developed conceptual thought to experimental study, white goods industry is exemplified. 15 criteria are used for evaluation in 4 customer groups and a satisfaction-loyalty survey developed by experts is applied to 200 customers with face-to-face interviews. As a result of the study, a customer and criteria grouping method is created with high performance classification methods and good fit structural models. In addition, results are evaluated for developing a customer strategy improvement tool considering method outcomes. (C) 2014 Elsevier Ltd. All rights reserved.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1016/j.cie.2014.09.031
dc.identifier.endpage106en_US
dc.identifier.issn0360-8352
dc.identifier.issn1879-0550
dc.identifier.scopus2-s2.0-84952865437
dc.identifier.scopusqualityQ1
dc.identifier.startpage95en_US
dc.identifier.urihttps://doi.org/10.1016/j.cie.2014.09.031
dc.identifier.urihttps://hdl.handle.net/20.500.12587/6115
dc.identifier.volume86en_US
dc.identifier.wosWOS:000358804500010
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofComputers & Industrial Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassification algorithmsen_US
dc.subjectCustomer satisfactionen_US
dc.subjectCustomer loyaltyen_US
dc.subjectStructural Equation Modelingen_US
dc.subjectWEKAen_US
dc.subjectLISRELen_US
dc.titleCustomer satisfaction and loyalty analysis with classification algorithms and Structural Equation Modelingen_US
dc.typeArticle

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