• Journal of the Society of Cosmetic Scientists of Korea
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• v.43 no.4
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• pp.349-355
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• 2017

Skin tone plays a key role in one of the determinant for facial attractiveness. Most female customers have an interest in choosing skin color and improving their skin tone and their needs have been contributed the expansion of cosmetic products in the market. Recently, cosmetic customers, who want bright skin, are also interested in healthy and lively-looking skin. However, there is no method to evaluate the skin tone with the complexion-describing adjectives (CDAs). Therefore, this study was conducted to find the ways to objectify and digitize the CDA. We obtained that quasi $L^*$ at dark skin is 65 and quasi $L^*$ at bright skin is 74 for standard images, which are selected from our data base. To match the following seven CDAs: pale, clear, radiant, lively, healthy, rosy and dull, the colors of both images were adjusted by 30 panels. The quasi $L^*$, $a^*$ and $b^*$ were converted from the RGB values of the manipulated images. The differences between the quasi $L^*$, $a^*$ and $b^*$ values of standard images and manipulated images reflecting each CDA were statistically significant (p < 0.05). However, there were no statistical significances between the $L^*$ values of dark and bright skin images that were modified in accordance with each CDA and there also were no statistical significances between the quasi $a^*$ values of dark and bright skin for pale and clear CDAs. From the statistical analysis, the CDAs were observed to form three groups: (i) pale-clear-radiant, (ii) lively-healthy-rosy and (iii) dull. We recognized that people have a similar opinion about perception of CDAs. Following our results of this study, we establish new standard method for sensibility evaluation which is difficult to carry out scientifically or objectively.

• Knowledge Management Research
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• v.22 no.3
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• pp.273-293
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• 2021

Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contact-less communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and steaming technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderate the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an one of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.