Consumers’ Kansei Needs Clustering Method for Product Emotional Design Based on Numerical Design Structure Matrix and Genetic Algorithms

Abstract

Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design.

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A Method for Consensus Reaching in Product Kansei Evaluation Using Advanced Particle Swarm Optimization

“…A case study of electric scooter was used to determine the proposed method's ability for reaching consensus in product Kansei evaluation process. The author's previous study has gained six primary Kansei needs through investigating and clustering about the target product, seen in [ 1 ]. Each Kansei adjective was given the antonym and a seven-point Likert scale was used to evaluate customers' response about product design alternatives, shown as follows: (1) untechnical–technological; (2) inactive–dynamic; (3) outdated–futuristic; (4) feminine–manly; (5) dimmed–vivid; (6) partial–integral.…”

“…As the international market is globalizing at high speed, new opportunities have been opened up for businesses with successful new products. In an era of highly competitive and uncertain market, companies that listen to their consumers are more likely to be successful [ 1 ]. With the increasing trend of emotional consumption, consumers making purchase decisions is no longer merely a consideration regarding function or practical use, but a comprehensively and perceptually assessment process through sense perception [ 2 ].…”

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

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