Abstract
The trend of new product development taking into account a customer’s feeling and needs has become very important for companies’ development and competition in the market. Kansei engineering is a consumer-oriented technology that seeks to capture the voice of the customer to produce a successful product. This method helps to transform customers feeling into the design parameters. In order to improve customer satisfaction, it is very important to determine the design parameters that make up the product. This paper presents a design support system intended for use in designing new product. A product has a lots of design attributes. For this reason, the product design attributes are reduced with Rough sets theory and main design attributes are obtained for developing a new product. Rough sets theory deals with uncertain or conflicting data. After determining product design attributes, the different products are produced for evaluating customer’s feel with Kansei adjectives. Customer evaluations were conducted using the semantic differential method to examine the relationship between users’ assessments of product and design elements. Kansei results are analyzed by applied Principle Component Analysis to determine the relationships between products and emotions that affect the general preferences of customers. Baby cradle design is taken as a case study; but this method can be used to develop other products. As a result, this paper presents a design support system intended for use in designing new product, so the designed product can fit more closely to the consumers’ desires.
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This work was supported by the Scientific and Technological Research Council of Turkey “TÜBİTAK-TEYDEB” programme with the project number-5170065.
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Aydoğan, E.K., Akgul, E., Delice, Y., Sinanoglu, C. (2020). Determining of Customer’s Kansei Needs and Product Design Attributes by Rough Set Theory. In: Kavoura, A., Kefallonitis, E., Theodoridis, P. (eds) Strategic Innovative Marketing and Tourism. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-36126-6_18
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DOI: https://doi.org/10.1007/978-3-030-36126-6_18
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