Abstract
This study proposes a model which shows the importance of Kansei Engineering (KE) methodology in supporting the design of robust services. The KE methodology is enhanced by the Kansei-based mining process, SERVQUAL, and Kano categorization in order to conceptualize robust service design and development. Due to complexity and contextual based, Kansei words as emotion representative are usually formed in fuzzy and abstract terms. It may lead to ambiguous and unclear meaning. Mapping and structuring more representative Kansei is needed. Hence, through Kansei mining system, historical data includes customer Kansei feedbacks are critical. KE model incorporating Kansei mining process followed by expected contribution which captures more organized and captured Kansei of product and service experience is proposed and discussed.
Highlights
Affective design or known as Kansei Engineering-based (KE-based) product design and development has received much attention from both researchers and practitioners
This study proposes a model which shows the importance of Kansei Engineering (KE) methodology in supporting the design of robust services
The KE methodology is enhanced by the Kansei-based mining process, SERVQUAL, and Kano categorization in order to conceptualize robust service design and development
Summary
Affective design or known as Kansei Engineering-based (KE-based) product design and development has received much attention from both researchers and practitioners. Kansei Engineering (KE) has shown its ability and superiority in capturing, identifying, and mapping customer affective/emotional needs into design characteristics [2][3]. This method has been used ranging from physical products to service attributes, e.g., shampoo bottle, audio system, virtual kitchen, hotel services, logistics services [1][2][4][5]. This study shows the milestones of KE application in services [5], and current research direction (see Table 1).
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