• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.35-48
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• 2015

It is frequently found in daily life that people who experience good luck as lottery winners try to improve their background (e.g., home, car) but it has not been empirically validated why they do that. Present research attempts to explore the prediction that people who experience good luck expand the scope of attention to background and those who undergo bad luck shrink the scope of attention to adjacent objects. Findings from Experiment 1a indicate that participants who experienced good luck (won the rock-paper-scissors game) paid more attention to background and performed worse in the "find the hidden picture" (below FHP) task while those who underwent bad luck (lost the rock-paper-scissors game) paid more attention to objects, leading to better performance in the FHP task. It is also found in Experiment 1a that, if people washed their hands after experiencing good or bad luck, the opposite result occurred. Experiment 1b confirmed that the rock-paper-scissor game manipulated good and bad luck successfully and did not influence self-control. Experiment 2 shows that people who strongly believe in good luck performed poorly in FHP task while those who do not believe in good luck performed well in FHP task. Overall, three experiments support the proposed research hypotheses. Implications of the study findings for cognitive psychology and related fields including consumer and sports psychology are discussed.

• Journal of Korean Home Economics Education Association
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• v.24 no.2
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• pp.135-154
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• 2012

The purpose of this study was to investigate the trends of HE exam questions through analyzing the examination items for secondary Home Economics(HE) teaching certification from 2002 to 2011. The results of the study were as follows: First, regarding the analysis on pedagogy of HE course, it accounted for 30.9% of the total questions, and recently, it increased to 35%. Regarding the ratio of questions by each evaluation element, 'practice of teaching and learning methods for HE course'(33.2%) had the highest ratio, and 'essence of the education of HE'(3.2%) had the lowest ratio. Second, regarding the analysis on eating habits, it amounted to 17.5% of the total questions, and recently reached 15%. With regard to the ratio of each evaluation element, 'cooking theory and practice'(26.1%) had the highest ratio, and 'culture of eating habits'(3.7%) had the lowest ratio. Third, regarding the analysis on clothing habits, it accounted 15% of the total questions, and recently reached 12.5%. With regard to the ratio of each evaluation element, 'clothing management'(25.1%) and 'production of clothing and living necessaries'(25.1%) had the highest ratio, and 'selection of clothing and self-expression'(3.0%) had the lowest ratio. Fourth, regarding the analysis on housing life, it accounted for 11% of the total questions, and recently reaches 12.5%. With regard to each evaluation element, 'the understanding of housing life culture'(22.5%) had the highest ratio, and 'the understanding of housing interior design'(10.7%) had the lowest ratio. Fifth, regarding the analysis on daily life as a consumer, it accounted for 12.4%, and recently reaches 12.5%. With regard to the ratio of each evaluation element 'management of domestic resources'(34%) had the highest ratio, and 'planning of entire life and domestic welfare'(0%) had the zero ratio. Sixth, regarding the analysis on family life, it accounted for 13.3% of the total questions, and recently reaches 12.5%. With regard to the ratio of each evaluation element, 'the understanding of family and the changes in family'(23.8%) had the highest ratio, and 'marriage and the development of family'(2%) had the lowest ratio.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.6
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• pp.893-903
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• 2009

Smart clothing represents the future of both the textile/clothing industry and electronic industry and has an effort to make electronic devices a genuine part of our daily life. The researches about technologies innovation and application of smart clothing can be found in previous studies. But consumer researches about perception or attitude toward smart clothing can be hardly found. Therefore, we proposed a conceptual framework that explores the impact of perceived risks on perceived attributes to adopt smart clothing. In addition, we compared differences of this framework among three counties. Korea, U.S. and Spain. Based on the literature review and hypotheses development, a research model was constructed. After data analysis using Amos 7.0, the results can be concluded as following: First, the influences of psychological risk among Korea, U.S. and Spain are same. Psychological risk has negative effect on relative advantage and complexity, but has positive effect on trialability. Second, loss risk was found to have nothing to do with relative advantage. But it negatively influences complexity for Korean consumers and positively influences trialability for both Korean and American consumers. Third, the influences of performance risk for different consumers are different. At last, based on our discussion, some implications were also concluded.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.75-95
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• 2020

With the growth of social networks, various forms of SNS have emerged. Based on various motivations for use such as interactivity, information exchange, and entertainment, SNS users are also on the fast-growing trend. Facebook is the main SNS channel, and companies have started using Facebook pages as a public relations channel. To this end, in the early stages of operation, companies began to secure a number of fans, and as a result, the number of corporate Facebook fans has recently increased to as many as millions. from a corporate perspective, Facebook is attracting attention because it makes it easier for you to meet the customers you want. Facebook provides an efficient advertising platform based on the numerous data it has. Advertising targeting can be conducted using their demographic characteristics, behavior, or contact information. It is optimized for advertisements that can expose information to a desired target, so that results can be obtained more effectively. it rethink and communicate corporate brand image to customers through contents. The study was conducted through Facebook advertising data, and could be of great help to business people working in the online advertising industry. For this reason, the independent variables used in the research were selected based on the characteristics of the content that the actual business is concerned with. Recently, the company's Facebook page operation goal is to go beyond securing the number of fan pages, branding to promote its brand, and further aiming to communicate with major customers. the main figures for this assessment are Facebook's 'OK', 'Attachment', 'Share', and 'Number of Click' which are the dependent variables of this study. in order to measure the outcome of the target, the consumer's response is set as a key measurable key performance indicator (KPI), and a strategy is set and executed to achieve this. Here, KPI uses Facebook's ad numbers 'reach', 'exposure', 'like', 'share', 'comment', 'clicks', and 'CPC' depending on the situation. in order to achieve the corresponding figures, the consideration of content production must be prior, and in this study, the independent variables were organized by dividing into three considerations for content production into three. The effects of content material, content structure, and message styles on Facebook's user behavior were analyzed using regression analysis. Content materials are related to the content's difficulty, company relevance, and daily involvement. According to existing research, it was very important how the content would attract users' interest. Content could be divided into informative content and interesting content. Informational content is content related to the brand, and information exchange with users is important. Interesting content is defined as posts that are not related to brands related to interesting movies or anecdotes. Based on this, this study started with the assumption that the difficulty, company relevance, and daily involvement have an effect on the dependent variable. In addition, previous studies have found that content types affect Facebook user activity. I think it depends on the combination of photos and text used in the content. Based on this study, the actual photos were used and the hashtag and independent variables were also examined. Finally, we focused on the advertising message. In the previous studies, the effect of advertising messages on users was different depending on whether they were narrative or non-narrative, and furthermore, the influence on message intimacy was different. In this study, we conducted research on the behavior that Facebook users' behavior would be different depending on the language and formality. For dependent variables, 'OK' and 'Full Click Count' are set by every user's action on the content. In this study, we defined each independent variable in the existing study literature and analyzed the effect on the dependent variable, and found that 'good' factors such as 'self association', 'actual use', and 'hidden' are important. Could. Material difficulties', 'actual participation' and 'large scale * difficulties'. In addition, variables such as 'Self Connect', 'Actual Engagement' and 'Sexual Sexual Attention' have been shown to have a significant impact on 'Full Click'. It is expected that through research results, it is possible to contribute to the operation and production strategy of company Facebook operators and content creators by presenting a content strategy optimized for the purpose of the content. In this study, we defined each independent variable in the existing research literature and analyzed its effect on the dependent variable, and we could see that factors on 'good' were significant such as 'self-association', 'reality use', 'concernal material difficulty', 'real-life involvement' and 'massive*difficulty'. In addition, variables such as 'self-connection', 'real-life involvement' and 'formative*attention' were shown to have significant effects for 'full-click'. Through the research results, it is expected that by presenting an optimized content strategy for content purposes, it can contribute to the operation and production strategy of corporate Facebook operators and content producers.

• Archives of design research
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• v.19 no.5 s.67
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• pp.203-212
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• 2006

With interests and participation in the costumeplay that mimics characters appeared on carton or animation in recent days, the costumeplay becomes one of cultural phenomena. Using a qualitative research method, this study identified costumeplayers' costume consumption pattern and explored its meanings from the perspective of consumption culture. Indeed, this study intended to help for understanding costumeplayer group as a consumer, and to provide basic knowledge about new market analysis related to fashion design and marketing. The results from the analyzing participant observation and in-depth interviews data are as follows: first, costumeplayers usually begin costumeplay by friends' invitations or by themselves and then continue on participating. Through the costumeplay, participants have benefits such as fun, departure from the daily life, and social interaction. Second, participants acquire costumes through purchase, rent, producing or combination of daily wear, but both purchase and rent account high. Third, the meanings of consumption culture in costumeplay include consumption behavior repeating possession and disposal. Also, costumeplayers concerns efficiency when purchasing or renting the costumes, and internet is a place where information search, comparison, and actual purchasing are occurred. Based on the results, fashion design and marketing implication, limitation of this study and further research ideas were suggested.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.37-56
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• 2007

The purpose of this study is to provide basic resources to the first-grade Home Economics Regular Teacher Qualification Program (FGHERTQP) in order to improve its operation plans. For the study, the three methods were carried out: an analysis on the curricula of FGHERTQP over six years since 2000, a questionnaire asking their satisfaction degrees and needs on the programs which was answered by the home economics teachers who were the participants of FGHERTQP, and several statistical analyses such as a descriptive-test, a $X^2$-test, a t-test, and one way ANOVA by using SPSS Win ver 10.0. The results of the study were as follows; Firstly, FGHERTQP has been operated ten times by five training centers during resent six years. Subject matters ($1{\sim}7$), whole numbers of lectures ($11{\sim}29$), and their allotted working hours ($111{\sim}136$) vary with individual training centers and operation years. Secondly, when using 5 point likert scales, Contents and Methods of evaluation marked 3.08 which were the lowest scores, and Qualification Training in General marked 3.72 which was the highest score among five fields of Qualification Training in General, Contents, Organizations, Methods and Evaluation. The overall scores were low. Thirdly, in needs analysis on offering subject matters, the participants wanted to study the field of home economics education more than that of subject contents. Looking about the highest needs classified by domains, Food Principles & Meal Management showed the highest in Foods. And Consumer Issues in Clothing & Textiles in Textiles, Upcoming Housing Cultures in Housing, Family Relationship in Child Development & Family Relationship, Juveniles and their daily life as a consumer in Family & Consumer Resources Management. Fourthly, training centers' lectures available had a significant influence on the satisfaction degrees according to general characteristic variations of the participants. That is, as a training center offers more lectures in the field of subject education than those of subject contents, the participants showed higher satisfaction degrees (p<.05).

• Journal of the Korean Society of Food Culture
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• v.13 no.1
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• pp.19-26
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• 1998

This study was carreid out to investigate present comsuming behavior and consumer preference of SEAFOODS as a stuff in KIMCHI making, adopting a questionaire survey for 500 housewives living in Korea except Chejudo Province. Frequency distribution and percentage of preferences were measured. Out of total housewives responded, 65.5% consider, THEY SHOULD EAT KIMCHI DAILY. Which conforms, kimchi is still an important side dish at most of the households On the other hand, some others consider EATING KIMCHI EVERY DAY is not neccesary(6.0%) or dislike it(0.5%). This result might suggest that kimchi may or may not be an essential sidedish for every households in the future. 96.3% of Housewives used fermented salited fish and 45% used seafoods as a staffing in making kimchi. Major reasons for adding seafoods in kimchi were: it improves teste and flavor(79.5%) and nutritional value(54.2%). Reasons for rejecting seafoods as a stuffing in making kimchi were: it worsens taste and flavor(13.5%), hygenic treatments of seafoods are below the necessary level(13.5%) and shelf life become shorter(12.8%), respectively. Among the fermented salted sauces, 84.9% and 69.1% of house wives responded as anchovy and shrimp sause were most favorite(base) material in Kimchi making, respectively. Out of total seafoods utilized in making kimchi,76.4%, 54.7% and 31.4% of housewives responded as oyster, small shrimp and sea-staghorn as the favorite seafoods in Kimchi making(raw material). Majority of housewives responded to develop it's taste and flavor to meet that of international one(86.5%) and that hygienic level(treatments) should be upgraded(50.9%).

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.89-111
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• 2008

Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj $R^2$=.223) and purchase intention (adj $R^2$=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj $R^2$=.692) and partial mediating effect between perceived attributes and purchase intention (adj $R^2$=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj $R^2$=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj $R^2$=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj $R^2$=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj $R^2$=.122) and purchase intention (adj $R^2$=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj $R^2$=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.