Journal of the Korean Society for information Management
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v.37
no.4
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pp.1-26
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2020
In today's increasingly data-intensive academic environment, data is becoming the foundation of academic communication as a research outcome rather than a research by-product. However, there is a limit to guaranteeing actual data reuse only by expanding the data supply or securing accessibility. In order to overcome this, it is necessary to understand the data reuse behavior and data needs in-depth. Therefore, this study attempted to identify the major data reuse behavior and data needs among researchers. To this end, the authors of KCI papers among the data reuse documents of the Korea Social Science Data Archive (KOSSDA) for the past 3 years were targeted. An in-depth interview was conducted with 12 researchers who accepted the interview. As a result, factors considered when reusing data were personal, economic, technical, and social aspects, and it was found that the data itself was used or contextual information of the data was used depending on the purpose of data reuse. The path to acquiring data is a web-based source of information, and a path through informal communication can also be found. In terms of the data needs, it was found that they prefer English, the United States, and institutional producers. Also they have a clear preference for quantitative data from an interviewer-filled interpersonal interview survey method, rich metadata along with raw data, and data that contains identification information. However, due to the lack of confidence in the value, it is negative for the use of data with controlled access and use, and it is difficult to confirm a clear preference because there is no similar data available for selection in terms of size and freshness.
Kim, Ga-Eun;Choi, Yoon-Ha;Kang, Su-Min;Lee, Jongseok;Jung, Deuk
Journal of the Korea Convergence Society
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v.12
no.8
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pp.85-92
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2021
This study was conducted to identify the impact of adolescents' dietary behavior on their stress perception and provide basic data for education programs linked to customized nutrition education by gender. In this study, the 2019 Korea Youth Risk Behavior Web-based Survey was used, and a total of 57,303 middle·high school students were selected. Controlling adolescents' age, school record, economic status, residence type, subjective health and body type perception, and the dietary life variables designed with breakfast, fresh foods(fruit, vegetables, milk, water), processed foods(carbonate beverage, energy beverage, sweet beverage, fast food) were analyzed to have an effects on the stress recognition of adolescents. Breakfast had a negative(-) effect on stress perception in all genders of adolescents, and in the case of fresh food, water for boys and fruit for girls had the highest negative(-) effect on stress perception, and in the case of processed foods, energy drink was the dietary factor that had the highest positive(+) effect on adolescents' stress perception. These results suggest that it is necessary to develop a dietary education program tailored to the gender of adolescents to improve their stress perception, and to provide continuous guidance to form a healthy diet.
In mathematics classes, the verbal explanation may contain diverse mathematical concepts and principles in short sentences. It may also include mathematics symbols and terms that might not be used in everyday life. Therefore, students may need particular listening ability in order to understand and participate in mathematics communication. Unlike general listening, the listening ability for mathematics classes may require student to integrate their mathematical and linguistic knowledge. The aim of this study is to reveal the subdomains of listening ability for mathematics classes in a elementary school. I categorized listening ability for mathematics classes in a elementary school from the literature. The categories of listening ability for mathematics are Interpretive Listening, Evaluative Listening, Hermeneutic Listening, Selective Listening, Pretend Listening, and Ignored Listening. In order to develop a framework for understanding listening ability for mathematics classes, I investigated a hierarchy of 412 South Korean elementary teachers' perception. Through a web-based survey, the teachers were asked to rank order their beliefs about and students' listening ability. Findings show that teachers' perceptions about listening ability for mathematics classes are divergent from current research trends. South Korean elementary teachers perceived Interpretive Listening as the most important listening.
This study is to investigate consumers' acceptance and their willingness to pay for clothes made of materials with low microplastic emissions as an alternative to synthetic fibers made of plastics by applying the contingent valuation method. A nationwide web-based survey was conducted for 1,052 respondents proportional to region, age, and gender during February 2021. More than 75% of the sample expressed intentions to purchase microplastic emission-reducing clothing instead of synthetic fiber clothing, and more than 80% of them have stated their willingness to pay for additional prices. A variation of Heckman's sample selection model was adopted to estimate factors affecting respondents' intentions to pay for additional prices, in which the probit model of intentions to purchase the clothing with alternative materials was used as a sample selection equation. While respondents were sensitive to the amounts of price increases suggested in the CV scenario, they expressed high acceptance and preferences for eco-friendly materials regardless of the microplastic emission-reducing levels. Consumers in the circular economy were willing to pay for the range of 41,000 to 51,000 won for a pair of clothing made with microplastic emission-reducing materials. In addition, as the microplastic emission-reducing rate has increased from 50% to 80%, the willingness to pay estimates were also significantly increased, ranging from 41,000~50,500 to 42,000~51,700 won.
The medium-large cladoceran species Simocephalus spp. predominantly occur in habitats with developed aquatic vegetation. Accordingly, due to Simocephalus' high contribution to zooplankton community biomass in the lake's littoral zone and wetland habitats, estimating their biomass is important to understand the matter cycling based on biological interactions within the aquatic food web. In this study, we reviewed the length-weight regression equations used previously to estimate Simocephalus biomass, directly measured S. serrulatus' body specification (length, width and area) and their biomass(dry weight) using instruments such as a microscopic digital camera and a microscale, and performed regression analysis between each other. When S. serrulatus biomass was estimated using the equation (Kawabata and Urabe, 1998) presented in 『Biomonitoring Survey and Assessment Manual』, Korea, errors between estimates and measures were relatively large compared to the S. serrulatus species-specific biomass estimate equation developed by Lemke and Benke (2003). In addition, both equations showed not only increasing trends in error (estimate-measure) with increasing S. serrulatus' body length, but also in error variance among similar-sized individuals. The results of regression analysis with dry weight by body specifications indicated that the most appropriate equation for estimating the biomass of S. serrulatus was derived from the width-dry weight exponential regression equation (R2=0.9555). The review and development study of such species-specific biomass estimation equations for zooplankton can be used as a tool to understand their role and function in aquatic ecosystem food webs.
Journal of Korea Entertainment Industry Association
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v.13
no.5
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pp.127-138
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2019
This study was a secondary data analysis using statistics from the 13th (2017) Korea Youth Risk Behavior Web-based Survey (KYRBS) to investigate the relationship between health behaviors and physical activity among Korean adolescents. A total of 62,276 adolescents in middle and high schools enrolled in this study. Physical activity utilized moderate and vigorous physical activity variables. Health behaviors used smoking, drinking, eating, sedentary behavior, and sleep duration variables. Statistical analyses were performed applying complex sample analysis method. Chi-square tests were used to compare physical activity according to health behaviors. Multivariate multinomial logistic regression analyses were conducted to examine the relationship between health behaviors and physical activity, adjusted for general characteristics. Current smoking and current drinking were associated with high levels of moderate and vigorous physical activity. Consuming fruits≥1 times/day, vegetables≥3 times/day, and sweet drinks≥3 times/week were associated with high levels of moderate and vigorous physical activity. Eating breakfast≥5 times/week was associated with high levels of moderate physical activity, but not with vigorous physical activity. Sedentary behavior≥2 hour/day was associated with low levels of moderate and vigorous physical activity. Sleep duration<7 hour/day was associated with high levels of moderate physical activity and low levels of vigorous physical activity. These findings suggest that since there is an interrelationship between health behaviors and physical activity among adolescents, intervention programs aiming at promoting physical activity and healthy lifestyles should consider a multiple behavior approach rather than an individual behavior approach.
Purpose:From a societal perspective, we evaluated the cost-effectiveness of a novel sustained-release injection of recombinant human growth hormone (GH) administered on a weekly basis compared with that of the present daily GH injection for the treatment of children with GH deficiency. Methods:Health-related utility for GH therapy was measured based on the visual analogue scale. During July 2008, caregivers of 149 children receiving GH therapy form 2 study sites participated in a web-based questionnaire survey. The survey required the caregivers to rate their current subjective utility with daily GH injections or expected utility of weekly GH injections. Because there was no difference in the costs of the daily and weekly therapies, for the purposes of this study, only drug acquisition costs were considered. Results:Switching from daily to weekly injection of GH increased the utility from 0.584 to 0.784 and incurred an extra cost of 4,060,811 Korean won (KW) per year. The incremental cost-utility ratio (ICUR) for a base case was 20,305,055 KW per quality-adjusted life year (QALY) gained. Scenario analyses showed that the ICUR ranged from 15,751,198 to 25,489,929 KW per QALY. Conclusion:The ICUR for a base case and worst case scenario analyses ranged from 0.85 to 1.37-times per capita gross domestic product of Korea, which is considered to be within the generally accepted willingness-to-pay threshold. Thus, it is concluded that switching from daily to weekly injection of GH would be cost-effective.
Yoon, Mi Ock;Lee, Hyun Sook;Kim, Kirang;Shim, Jae Eun;Hwang, Ji-Yun
Journal of Nutrition and Health
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v.50
no.5
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pp.504-518
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2017
Purpose: The objective of this study was to develop a processed foods database (DB) for estimation of processed food intake in the Korean population using data from the Korea National Health and Nutrition Survey (KNHANES). Methods: Analytical values of processed foods were collected from food composition tables of national institutions (Development Institute, Rural Development Administration), the US Department of Agriculture, and previously reported scientific journals. Missing or unavailable values were substituted, calculated, or imputed. The nutrient data covered 14 nutrients, including energy, protein, carbohydrates, fat, calcium, phosphorus, iron, sodium, potassium, vitamin A, thiamin, riboflavin, niacin, and vitamin C. The processed food DB covered a total of 4,858 food items used in the KNHANES. Each analytical value per food item was selected systematically based on the priority criteria of data sources. Results: Level 0 DB was developed based on a list of 8,785 registered processed foods with recipes of ready-to-eat processed foods, one food composition table published by the national institution, and nutrition facts obtained directly from manufacturers or indirectly via web search. Level 1 DB included information of 14 nutrients, and missing or unavailable values were substituted, calculated, or imputed at level 2. Level 3 DB evaluated the newly constructed nutrient DB for processed foods using the 2013 KNHANES. Mean intakes of total food and processed food were 1,551.4 g (males 1,761.8 g, females 1,340.8 g) and 129.4 g (males 169.9 g, females 88.8 g), respectively. Processed foods contributed to nutrient intakes from 5.0% (fiber) to 12.3% (protein) in the Korean population. Conclusion: The newly developed nutrient DB for processed foods contributes to accurate estimation of nutrient intakes in the Korean population. Consistent and regular update and quality control of the DB is needed to obtain accurate estimation of usual intakes using data from the KNHANES.
Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.
Nowadays, it is common that most consumers are purchasing goods in e-stores. The e-stores eager to attract, revisit, retain, and finally convert them into loyal customers. The e-store marketers have planned and executed numerous marketing efforts. As one of the marketing activities, e-store managers attempt to build web sites that meet customers' functional and psychological needs. A wide array of studies has been done to identify factors that could affect customers' response of web sites. Majority of studies were conducted to verify technology-related and functional variables of the website which facilitate transactions and enhance customer responses such as purchase intention and website loyalty. However, there has been little research on the external cues of website and psychological variables of consumer that could have positive influences on customer response. The purpose of this study is to investigate the influence of e-store personality on e-store loyalty through mediating variables such as e-store identification, e-store trust, and e-store engagement. The authors of this study develop the model and set up the six main hypotheses and a set of sub-hypotheses based on a literature review, shown in
. This model is composed of four paths such as dimensions of e-store personality${\rightarrow}$e-store identification, e-store identification${\rightarrow}$e-store loyalty, e-store identification ${\rightarrow}$e-store trust${\rightarrow}$e-store loyalty, and e-store identification${\rightarrow}$e-store engagement${\rightarrow}$e-store loyalty. II. Research Method Ladies under 30s were the respondents of this survey. Data were collected from January 20th to February 26th in 2010. A total of 200 questionnaires were distributed and 169 respondents were analysed finally to test hypotheses because 31 questionnaires had incorrect or missing responses. SPSS 12.0 and LISREL 7.0 program were used to test frequency, reliability, factor, and structural equation modeling analysis. III. Result and Conclusion According to results from factor analysis, eigen value was over 1.0 and items which were below 0.6 were deleted. Consequently, 9 factors(% of total variance is 72.011%) were searched. All Cronbach's ${\alpha}$ values are over the recommended level(${\alpha}$ > 0.7). The overall fit indices are acceptable such as ${\chi}^2$=2028.36(p=0.00), GFI=0.87, AGFI=0.82, CFI=0.81, IFI=0.92, RMR=0.075. All factor loadings were over the recommended level. As the result of discriminant validity check with chi-square difference test between paired constructs, each construct has good discriminant validity. The overall fit indices of final model are acceptable such as ${\chi}^2$=340.73(df=36, p=0.00), GFI=0.92, AGFI=0.81, CFI=0.91, IFI=0.91, RMR=0.085. As test results, 5 out of 6 hypotheses are supported because there are statistically significant casual relationships in structural equation model, shown in
. First of all, hypothesis 1 is partially supported because sub-hypothesis 1-1 and 1-2 are supported, whereas sub-hypothesis 1-3, 1-4, and 1-5 are rejected. Specifically, it reveals that warmth and sophistication dimensions in e-store personality have positive influence on e-store identification, however, activity, progressiveness, and strictness does not have any significant relationship on e-store identification. Secondly, hypothesis 2 was supported. Therefore, it can be said that e-store identification has a positive impact on e-store trust. Thirdly, hypothesis 3 is also supported. Hence, there is a positive relationship between e-store identification and e-store engagement. Fourthly, hypothesis 4 is supported too. e-store identification has a positive influence on e-store loyalty. Fifthly, hypothesis 5 is also accepted. This indicates that e-store trust is a precedent variable which positively affects e-store loyalty. Lastly, it reveals that e-store engagement has a positive impact on e-store loyalty. Therefore, hypothesis 6 is supported. The findings of the study imply that some dimensions of e-store personality have a positive influence on e-store identification, and that e-store identification has direct and indirect influence on e-store loyalty through e-store trust and e-store engagement positively. These results also suggest that the e-store identification in e-store personality is a precedent variable which positively affects e-store loyalty directly and indirectly through e-store trust and engagement as a mediating variable. Therefore, e-store marketers need to implement website strategy based on e-store personality, e-store identification, e-store trust, and e-store engagement to meet customers' psychological needs and enhance e-store loyalty. Finally, the limitations and future study directions based on this study are discussed.
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