• Journal of the Ergonomics Society of Korea
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• v.19 no.3
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• pp.23-37
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• 2000

Usability is one of the most important factors that affect customers' decision to purchase a product. Several studies have been conducted to model the relationship between the product design variables and the product usability. Since there could be hundreds of design variables to be considered in the model, a variable screening method is required. Traditional variable screening methods are based on expert opinions (Expert screening) in most Kansei engineering studies. Suggested in this study are statistical methods for screening important design variables by using the principal component regression(PCR), cluster analysis, and partial least squares(PLS) method. Product variables with high effect (PCR screening and PLS screening) or representative variables (Cluster screening) can be used to model the usability. Proposed variable screening methods are used to model the usability for 36 audio/visual products. The three analysis methods (PCR, Cluster, and PLS) show better model performance than the Expert screening in terms of $R^2$, the number of variables in the model, and PRESS. It is expected that these methods can be used for screening the product design variables efficiently.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.397-412
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• 2023

In order for social robots to take root in human life, it is important to consider the technical implementation of social robots and human psychology toward social robots. This study aimed to derive potential social robot clusters based on the emotions consumers feel about social robot appearance design, and to identify and compare important design characteristics and emotional differences of each cluster. In our study, we established a social robot emotion framework to measure and evaluate the emotions consumers feel about social robots, and evaluated the emotions of social robot designs based on the semantic differential method, an kansei engineering approach. We classified 30 social robots into 4 clusters by conducting a multidimensional scaling method and K-means cluster analysis based on the emotion evaluation results, confirmed the characteristics of design elements for each cluster, and conducted a comparative analysis on consumer emotions. We proposed a strategic direction for successful social robot design and development from a human-centered perspective based on the design characteristics and emotional differences derived for each cluster.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.25-31
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• 2010

It is known from consumer surveys that the interior design of cars greatly influences on consumers' affection. Most notably, the instrument panel which occupies the driver's attention while driving would be one of the main components that affect consumer's affection, but the designer does not often put due importance to this design component. The purpose of this study is to define consumers' affection on the instrument cluster panel in terms of its design factors: color of panel lighting and layout of meters as independent factors. Semantic differentials or affective adjectives that are related to the instrument panel were first derived from surveys, existing studies and the available literature. Then, representative affective factors were drawn using factor analysis and multi-dimensional scaling (MDS). Evaluation of the instrument panel was performed and analyzed by Taguchi's robust design to provide more robust results under various noise factors which are color and material of car interior. Experiment revealed that consumers had five affective factors on the instrument panel and luxurious, charming, and visible affections are grouped into a factor and unique and dynamic affections in another factor. Evaluation of the instrument panel by Taguchi's robust design found that the white color of panel lighting and the panel with four meters was the most preferred design in terms of both the affection of luxury and uniqueness.

• Archives of design research
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• v.17 no.3
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• pp.413-420
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• 2004

New design method has been required for web designers to grasp the proper emotion, impression, and feeling of a web site and reflect these elements in web design. It is certain that such a new methodology can be a useful design tool, although web designers have only relied on their intuition and experience to induce users to perceive specific emotion of web sites. In this study, Kansei Engineering Type Ⅰ (Nagamachi, 2002 and Park, 2000) method was applied to develop the methodology. One hundred thirty six web sites believed to convey emotions effectively were first selected by recommendation of professional web designers and twenty two web sites were finally chosen and evaluated using questionnaire. The web sites were then objectively and quantitatively assessed by measuring the degree of utilization of the design elements, balance, overall density, and homogeneity. We examined the cause-and-effect between the results of emotional and quantitative analysis by multiple regression and introduced the design methodology based on the examination. The research method and procedures applied to this study would be applicable to design studies related to the emotional inducement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.597-607
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• 2008

ATIS(Advanced Traffic Information System) provide valuable information as the travel time and traffic congestion, detour, traffic accident information to drivers, so it is being in the spotlight. But so far, the study on the consumer satisfaction with providing traffic information is incomplete. So, this study run a Canonical discriminant analysis and a Canonical correlation analysis by a QuantificationIItheory based on a Traffic Information Satisfaction image data through questionnaires, and found out the factors with influence on the consumer satisfaction. And this study definitely found out the correlation between consumer's recognition and traffic information satisfaction through understanding the change on the recognition about traffic information satisfaction by a QuantificationItheory. Finally, this study found out the change on the sensibility recognition of drivers by running the principal component anlysis, developed the traffic information satisfaction evaluation model considering the change on the recognition by using the structural equation model.