A Method for Detecting Brand Loyal Customers using Brand Equity Measurement Model Implemented by Real Valued Flexibly Connected Neural Network

This paper proposes a new method of Brand Equity Measurement Model (BEMM) to detect brand loyal customers based on the Real valued Flexibly Connected Neural Network (RFCN). Brand equity has been measured by several methods such like SEM and ANN. However, these previous methods have difficulties for...

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Bibliographic Details
Published inNihon Kansei Kougakkai rombunshi Vol. 17; no. 1; pp. 31 - 40
Main Authors WATANUKI, Shinya, NAGAO, Tomoharu
Format Journal Article
LanguageEnglish
Published Japan Society of Kansei Engineering 2018
Subjects
Brand informatics
Genetic algorithm
Neural network
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Summary:This paper proposes a new method of Brand Equity Measurement Model (BEMM) to detect brand loyal customers based on the Real valued Flexibly Connected Neural Network (RFCN). Brand equity has been measured by several methods such like SEM and ANN. However, these previous methods have difficulties for measuring brand equity and describing consumer information process in views of the restriction on addressing data and the flexibility of designing the structure. In this study, we conducted online survey about brand equity. We then verified the effectiveness for our proposal method in comparison with the previous method by analyzing the survey data. As a result, we showed that our proposal method is better than the previous one. We have demonstrated that RFCN is one of the appropriate methods for BEMM and has strong capability of detecting brand loyal customer.
ISSN:1884-5258
1884-5258
DOI:10.5057/jjske.TJSKE-D-17-00053