A Consumer e-Loyalty Assessment Model: B2C Service Management by Fuzzy MCDM Techniques

Abstract

Customer loyalty is one of the critical motivations that facilitate the intentions and the actions of repurchase at a website stores and create marketing values for business-to-consumer service firms. However, 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. Therefore, this paper presents a novel fuzzy multiple criteria decision making (FMCDM) model to cope with the assessment issue of B2C service e-loyalty construct. First, the analytic network process (ANP) will be used for evaluating essential factors that enhance B2C retailing service loyalty. Secondly, the logic of triangular fuzzy numbers will be applied to transform the satisfaction level of consumers into explicit numbers by fuzzy linguistic variable modeling and Converting fuzzy data into Crisp Set (CFCS) algorithm. Finally, a fuzzy MCDM model is used to determine consumers' subjective loyalty degree among B2C e-service providers. An empirical case assessed the consumer loyalty towards three Taiwanese B2C e-retailing service websites will demonstrate the feasibility of this approach. In addition, we validated the importance of the satisfactory degree resulted from a new exploratory pillar criteria of personalized product recommendations (PPRs) of B2C services for online marketing by our FMCDM model. The result of this study carried out that five main criteria of the antecedent for B2C services loyalty and the fuzzy e-loyalty scores are obtained for loyalty ranking of the case companies. The derived e-loyalty values of B2C retailing services are then employed to construct the fuzzy synthetic IPA (importance-performance analysis) matrix, expecting to support decision making on B2C services content selection and extend to strategic management directions to digital service innovation in e-markets.