• The Research Journal of the Costume Culture
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• v.16 no.4
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• pp.681-695
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• 2008

This study was accomplished to investigate the preference of clothing materials and the clothing demand performance for underwear and everyday dress of atopic patients. As this study was the research study by a use of a questionnaire, the finally total 987 copies of the collected questionnaires were used to analyze the data. SPSS was used for the statistical analysis of data. To analyze the data, frequency analysis, percentage, $X^2$-test, reliability analysis, factor analysis, t-test, ANOVA and Duncan's multiple comparisons were used. The results obtained are as follows. In factor analysis for clothing materials and the demand performance which atopic patients favor, the preference factors for underwear materials were classified as pliability/a sense of weight, a sense of cold and warmth, tactility, and elasticity. Those for everyday wear were classified as pliability/surface roughness, a sense of cold and warmth, a sense of weight, and elasticity. And the demand performance factors for underwears were classified as thermophysiology, care convenience, and skin contact. Those for everyday wear were classified as comfortableness and care convenience. In the difference analysis for the preference and the demand performance, Both everyday wear and underwear showed a significant difference for the preference and the demand performance according to gender, age, income, education level, and occupation.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.8
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• pp.1165-1176
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• 2002

This study intended to provide more refined information on color preferences by systematizing the concept of the color preference(general color preference, apparel color preference) and revealing different trends in the color preference and the actual possession of apparels. We collected data from 303 females in the ages between 20 and 40 in Seoul and analyzed by paired t-test. The results were as follows: 1. The analysis on general color preference, apparel color preference, and apparel possession color revealed that the cold colors such as blue and violet marked higher, and the warm colors such as yellow and orange marked lower in general color preference. For apparel color preference, neutral and brown were among the highest and the rest of the colors were in the same trend as general color preference. Apparel possession color showed defined accordance with apparel color preference. In terms of tones, pale tone marked the highest in general color preference and was followed by vivid, dull, and dark tones in decreasing order. For apparel color preference, pastel, dul1, and dark tones were among the highest. 2. Comparison between general color preference and apparel color preference in terms of hue showed that, except for orange, every hue showed disagreement in general color preference and apparel color preference. Neutral and brown hues marked higher in apparel color preference than in general color preference where as a]1 the other hues marked higher in general color preference. Comparison between apparel color preference and apparel possession color in terms of hue revealed that in most hues, apparel possession color was lower than apparel color preference. In terms of tones, vivid and pale tones marked higher in general color preference than in apparel color preference while dull and dark tones marked higher in apparel color preference than in general color preference.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.61-69
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• 2014

Collaborative filtering recommendation creates similar item subset or similar user subset based on user preference about items and predict user preference to particular item by using them. Thus, if preference matrix has low density, reliability of recommendation will be sharply decreased. To solve these problems we suggest Hybrid Preference Prediction Technique Using Weighting based Data Reliability. Preference prediction is carried out by creating similar item subset and similar user subset and predicting user preference by each subset and merging each predictive value by weighting point applying model condition. According to this technique, we can increase accuracy of user preference prediction and implement recommendation system which can provide highly reliable recommendation when density of preference matrix is low. Efficiency of this system is verified by Mean Absolute Error. Proposed technique shows average 21.7% improvement than Hao Ji's technique when preference matrix sparsity is more than 84% through experiment.

• Journal of Korean Critical Care Nursing
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• v.9 no.2
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• pp.36-47
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• 2016

Purpose: The study examined core job characteristics and job preference to explain work performance among critical care nurses. The theoretical model was constructed based on the job characteristics model with core job characteristics as exogenous variables, and work performance and job preference as endogenous variables. Methods: A total of 228 hospital nurses participated in the study from May to September, 2015. Data were collected through structured questionnaires and analyzed using structural equation modeling. Results: The model showed a good fit to the data with $x^2/df=2.90$, goodness of fit index = .91, root mean square residual = .20, comparative fit index = .93, and incremental fit index = .93. The core job characteristics explained 64% of the variance in job preference. The core job characteristics and job preference explained 52% of the variance in work performance. Conclusions: The core job characteristics can explain the work performance among critical care nurses through job preference. Effective strategies to improve the work performance among critical care nurses should focus on the application of the core job characteristic into a productive work environment. Further studies are warranted to explore the role of job preference of critical care nurses in promoting their work performance.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.5 s.153
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• pp.800-806
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• 2006

The purpose of this study was to investigate the differences in the make-up behavior influenced by make-up preference images, and the order of importance in the make-up behaviors. The questionnaires were given to female residents in the ages between $20\sim45$ in Seoul and Kyung-gi province during October 2004. 322 questionnaires were used for data analysis. The collected data were analyzed by using SPSS 10.0 software with various techniques such as ANOVA test, Duncan test and Paired t-test. The make-up behaviors were divided into three main categories: facial make-up behavior, color make-up behavior, and additional make-up behavior. The results showed that the skin care behavior was considered the most important among other make-up behaviors. Generally facial make-up was thought to be most important and color make-up, and additional make-up were followed orderly. The results of the make-up behavior differences by make-up preference image. The natural make-up preference image group considered all the make-up behavior less important than other make-up preference image groups. The modern make-up preference image group considered additional make-up behavior more important.

• The Journal of Industrial Distribution & Business
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• v.12 no.10
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• pp.7-17
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• 2021

Purpose: Studies on social exclusion from a sensory perspective are rather limited in state-of-the-art literature, especially in exploring the relationship between social exclusion and shape preference from a sensory marketing perspective. The present study aims to explore the effect of social exclusion on consumers' shape preference (angular vs. rounded) and the underlying mechanism. Research design, data and methodology: The relationship between social exclusion and consumers' shape preference was investigated in Study 1 using a one-way between-subject design (being excluded vs. being included), and the mediation effect of sense of control has been examined in Study 2 via a between-subjects design (being excluded vs. being included) ×2 (angular vs. rounded). Both studies were conducted on the Credamo data platform in China, and evaluated by one-way ANOVA. Results: The results showed socially excluded consumers prefer the product with angular design rather than socially included consumers, and this effect can be mediated by sense of control. Conclusions: This paper contributes academically for investigating the research area of the sense of control and explores the influence of the control needs of humans on consumer behaviors. Furthermore, it also clarifies new potential psychological role of shape preference - the recovery of the sense of control - to enrich the psychological mechanisms of shape preference.

• Korean Institute of Interior Design Journal
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• no.17
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• pp.210-215
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• 1998

The purpose of study was to identify the interior design preference according to age gender and monthly income of subjects. Interior Image Preference Scale was used to measure Interior design preference of consumers. Data were collected from Oct. 10th 1997. to Nov. 13th 1997. The subjects were 609 adults living in Seoul. Frequency percentage mean Generalized Linear Models and Duncan's multiple range test were used for data analysis, The major results of this study were 1) the subjects generally preferred feminity complexity and modernity of interior design 2) this study revaled relative difference in interior design preference according age gender and monthly income.

• Journal of the Korean Home Economics Association
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• v.39 no.10
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• pp.29-37
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• 2001

The purpose of this study is to investigate the preference and the use of the bedclothes. The data were obtained from market research of 12 department stores which were located in Seoul, Daegu and Busan, and from questionnaires completed by 356 women in Daegu area whose age was 20 years and older. The SPSS package was used for data analysis which includes frequency, percentage, $X^2$test, ANOVA, and Scheffe test. Cotton was the most popular fiber for coverings and fillings. Color preference was in the order of pastel, non-chromatic, vivid, and white color and pattern preference was in order of floral, check, and stripe pattern. Practicality, color and fabric were the most important factors and price was the most unsatisfied factor when bedclothes were purchased. Also, information for bedclothes was obtained mainly through internet shopping, home shopping or catalog shopping.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1286-1295
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• 2014

This paper suggests the way that it could improve the reliability about preference of user's feedback by adding weighting factor on sentiment analysis, and efficiently make a sentiment analysis of users' emotional perspective on the big data massively generated on twitter. To solve errors on earlier studies, this paper has improved recall and precision of sensibility determination by using sensibility dictionary subdivided sentiment polarity based on the level of sensibility and given impotance to sensibility determination by populating slang, new words, emoticons and idiomatic expressions not in the system dictionary. It has considered the context through conjunctive adverbs fixed in korean characteristics which are free to the word order. It also recognize sensibility words such as TF(Term Frequency), RT(Retweet), Follower which are weighting factors of preference and has increased reliability of preference analysis considering weight on 'a very emotional tweet', 'a recognised tweet from users' and 'a tweeter influencer'

• Journal of Korean Society of Transportation
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• v.10 no.3
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• pp.21-42
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• 1992

As for the travel demand analysis of the past, forcasting has been conducted by the use of revealed preference(RP) informations about actual or observed choices made by individuals. Forcasting method using RP data needs implicit assumptions that there will be no remarkable changes in existing transport conditions. However in case of occuring the great changes in existing conditions or adding a new choice-set of hypothetical options, it is very difficult to predict future travel demand. Fortunately in recent years, especially in the mode choice analysis, it has been perceived that the importance of individual performance data using stated preference(SP) experiments as well as RP data. But the research reports has not been reported sufficiently from models estimated using SP data. Under this background, we analyze the factors affecting the mode choice behavior as a fundamental study against the modelling task with SP choice data. For this analysis, we assumed subway operations in the secondary cities where there are no subway lines until now, and set up a choice-set of hypothetical options based on Experimental Design Method.