Identification of Customers’ Latent Kansei Needs and Product Design by Rough Set Based Approach

Tatsuo Nishino
Dept. of Kansei Design, Hiroshima International University, Japan

Ryoichi Satsuta
Sugihara, Co., Ltd., Japan

Mika Uematsu
Sugihara, Co., Ltd., Japan

Shigeru Sugihara
Sugihara, Co., Ltd., Japan

Mitsuo Nagamachi
International Kansei Design Institute, Ltd., Japan

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Ingår i: 11th QMOD Conference. Quality Management and Organizational Development Attaining Sustainability From Organizational Excellence to SustainAble Excellence; 20-22 August; 2008 in Helsingborg; Sweden

Linköping Electronic Conference Proceedings 33:29, s. 341-350

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Publicerad: 2008-12-09


ISSN: 1650-3686 (tryckt), 1650-3740 (online)


Purpose: This paper proposes a new rough set based kansei engineering methodology; in which rough set model analyzes the interaction effects between principal components presenting customers’ need element and between product design category elements; and discusses its effectiveness and limitation through an application example to kansei product development.

Methodology/approach: Rough set model is a promising method to analyze the interaction effects; important information for kansei product design which traditional statistical analysis was difficult to find out. We applied the proposed methodology to kansei product development project of car floor carpet for new car design and compared it with traditional kansei engineering methodology. Based on the proposed methodology; we clarified the patterns of customers’ needs to car floor carpet and identified design element pattern rules to realize customers’ needs.

Findings: Rough set based approach was very useful in that it is able to clarify customers’ latent needs as a combination of principal component elements and relates them to product specification considering its significant interaction effects. Rough set model could clarify customers’ latent needs; and then find new design elements interacting the design elements; which were not found out by traditional statistical analysis. At the present research stage; this paper suggests that it is beneficial for product designer/engineer to use rough set model; statistical analysis and his/her expert knowledge.

Research limitation/implication: Rough set based approach to kansei engineering provides more information on customers’ needs about product and product design specification. Moreover; it enables a consistent analysis from the identification of customers’ needs to design specifications fitted to customers needs. The proposed methodology provides a useful procedure for product designer/engineer to develop “customer-oriented product”.

Originality/value: This paper challenges traditional kansei engineering methodology and offers a new rough set based methodology for kansei engineering. It was shown that the proposed methodology was more useful in the practical kansei product design than the existing methodology; especially in the identification of customers’ latent needs and the clarification of interaction effects between design elements.


Customers’ needs; kansei product design; rough set based kansei engineering methodology


Nishino; T. (2005a): “Rough Sets and Kansei”; In Nagamachi; M. (ed.) (2005); Product Development and Kansei; Kaibundou; Tokyo.

Nishino; T. Nagamachi; M and Tanaka; H. (2005b). Variable Precision Bayesian Rough Sets Model and Its Application to Human Evaluation Data; RSFDGrC; LNAI 3641; Springer; 294-303.

Nishino; T. Nagamachi; M and Tanaka; H. (2006a): Variable Precision Bayesian Rough Sets Model and Its Application to Kansei Engineering; Transactions on Rough Sets V (International Journal of Rough Set Society); LNCS 4100; Springer; 190-206.

Nishino; T.; Nagamachi; M. and Sakawa; M. (2006b): Acquisition of Kansei Decision Rules of Coffee Flavor Using Rough Set Method; Kansei Engineering International; Vol. 5; No.4; 41-50.

Nishino; T.; Nagamachi; M.; Sakawa; M.; Kato; K. and Tanaka; H. (2006c): A Comparative Study on Approximations of Decision Class and Rule Acquisition by Rough Sets Model; Kansei Engineering International; Vol. 5; No.4; 51-60.

Nishino; T. and Nagamachi; M. (2007a): Rough set model and its application to kansei engineering; QMOD 2007; CD-ROM.

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