• Journal of Agricultural Extension & Community Development
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• v.8 no.1
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• pp.25-40
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• 2001

The purposes of the study were to identify satisfaction and achievement of learning by female learner's characteristics, and to suggest measures to improve quality of education in internet education programs. In order to determine the educational effectiveness associated with the characteristics of learners, this study attempted to employ two way approaches by observing the degree of achievement for learning, which represents an instructor-oriented approach, and the degree of satisfaction for education, which represents a learner-oriented approach to enhance the quality of internet education for female learners. As an approach to evaluate the educational effectiveness, the degree of achievement in learning(Tyler's classical approach), and the degree of satisfaction for education (Scriven's consumer-oriented evaluation model) were utilized. A survey form was developed by the researcher after reviewing the various tools originated from Boshier, Cross, Gagne and Choi, and distributed to a panel of judges that examined the content validity of the instrument. The sample for the study consisted of 160 female learners from three universities in Seoul and capital area, and the survey form was used to collect data for this study. The SPSS WIN program was used in analyzing the data and a series of statistical tests were conducted including frequency, percentile, t-test, ANOVA, correlation, multiple regression, and factor analysis. The statistical significance level was 0.05. The following conclusion were drawn from this study of female internet education. First, it was evident that female internet learners tend to utilize information from internet, and this can be interpreted as participants' positive attitude, and voluntary participation. Second, educational facilities and services should be improved in the future, because the level of satisfaction was low in these areas compared to curriculum and educational methodology. Third, the participating factors influenced by the level of satisfaction for education of learner characteristics were the 'formation of inter-personal relationship and willingness to change' and the 'needs for education on internet', thus appeared that both social and educational needs influenced the level of satisfaction for education. Fourth, the degree of achievement in learning was higher in the order of 1) attitude 2) function 3) knowledge, thus, attitude change was the most important in achievement of learning. Fifth, the individual background that influenced the level of achievement in learning were age and educational experience. As for the individual level of achievement for learning, the younger and more educated group were more satisfied.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.423-431
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• 2021

This paper examines the impact of university social responsibility on brand image and student satisfaction. Social responsibility impact on consumer behavior has been studied extensively. But the same impact has not been rigorously tested to the same extend in the education sector. Firstly, we analyze the perception of university social responsibility (USR) and its components, including (1) the quality of teaching programs, facilities, and academic staff; (2) supporting learning activities; and (3) human resource policies. Secondly, we investigate the relationship between university social responsibility, brand image, and student satisfaction. The study examined these relationships through a proposed economic model based on answers from a survey of 298 students at the University of Food Industry Ho Chi Minh City. From the above survey data, the author proceeds to quantify variables and, based on Cronbach's Alpha reliability coefficient, EFA factor analysis, and linear regression, to measure the impact of each social responsibility factor on business of the university and student satisfaction. The results show that university social responsibility actually affects the university's brand image and student satisfaction. Our findings suggest that universities should develop an appropriate marketing strategy to reinforce brand image and student satisfaction through the university social responsibility model.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.354-360
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• 2022

Metabolic disease is a disease with a prevalence of 26% in Korean, and has three of the five states of abdominal obesity, hypertension, hunger glycemic disorder, high neutral fat, and low HDL cholesterol at the same time. This paper links the consumer panel data of the Rural Development Agency(RDA) and the medical care data of the National Health Insurance Service(NHIS) to generate a classification model that can be divided into a metabolic disease group and a control group through food consumption characteristics, and attempts to compare the differences. Many existing domestic and foreign studies related to metabolic diseases and food consumption characteristics are disease correlation studies of specific food groups and specific ingredients, and this paper is logistic considering all food groups included in the general diet. We created a classification model using regression, a decision tree-based classification model, and a classification model using XGBoost. Of the three models, the high-precision model is the XGBoost classification model, but the accuracy was not high at less than 0.7. As a future study, it is necessary to extend the observation period for food consumption in the patient group to more than 5 years and to study the metabolic disease classification model after converting the food consumed into nutritional characteristics.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.471-483
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• 2012

The demand of using educational applications for 'smart' devices has recently increased. Accordingly, this study analyzed the satisfaction of educational applications and the factors which affect to purchase intention suggesting optimal development and use for the future. Based on searching for the theoretical background, the research model for the study was set: Appropriateness, interactivity, amusement and ubiquity were designated as independent variables, consumer satisfaction as parameter variable, and purchase intention as dependent variable. Through conducting structural equation modeling with the variables, the results showed that appropriateness, amusement and ubiquity had significant impacts on consumer satisfaction and purchase intention of educational applications. The results were expected to give suggestions as presenting guideline for educational application, improving mobile learning and vitalizing mobile contents.

• Human Ecology Research
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• v.51 no.5
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• pp.497-511
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• 2013

This study aimed to examine Korean men's experiences of work-family balance in dual income families with children under six years of age. We focused on identifying the difficulty of balancing work and family considering their individual, social, and cultural conditions. The method was a qualitative study involving two in-depth interviews with each of 12 men, and analyzing the data through the grounded theory approach. From the results, a model of men's work-family experience was constructed. It demonstrates the central phenomena (difficulties of balancing), the causal conditions (lacking time for family, seeking support from the employer, and learning husband's roles insufficiently), the contextual conditions (remaining paternalism and changing husband's roles), the intervening conditions (workplace, childcare support, and wife characteristics), and strategies (help from relatives, utilizing daycare centers, controlling birth, managing work conditions, and using family polices). We clarify the overall picture of working and family life experiences, and also show how men deal with their problems in their circumstances by balancing working and family life. In conclusion, males have difficulty participating in family life autonomously because of having less decision-making power than the wife. Moreover, the great responsibilities of the breadwinner disturb the work-family balance. Men devote themselves to working to hold a job instead of spending time with their family. However, they ultimately value work-family balance with respect to 'keeping a peaceful family life'.

• Health Policy and Management
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• v.21 no.1
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• pp.115-131
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• 2011

Several common issues are encountered by countries - Germany, Japan, and the United States - that adopted long-term care (LTC) system. First, the demand for LTC and its associated costs have steeply risen following the implementation of the LTC policy. Second, ensuring the quality of services have been difficult. Third, the coordination of services among providers and between LTC and medical care has been inadequate. Learning from their experience, we suggest ways to improve the LTC system in Korea. The basic approach aims for efficiency over equity in the system. This would require promoting provider competition and consumer choice. We propose several policy options according to the major stakeholders. For consumers, cash benefits at fixed rates and personal savings accounts are feasible options to self-contain the demand and cost of services. On the insurer's side, creating an environment of multiple insurers will engender competition, leading to cost savings and quality care. For providers, delivery of quality services through competition, cost-containment through capitated reimbursements, and coordination of services through integrated delivery system can be achieved. From the assessors' perspective, establishing an information system to monitor the activities of insurers and providers would be important, empowering consumers with information to choose cost-effective service providers. In summary, the suggested approach would provide cost-effective LTC services by guaranteeing consumer choice and promoting major stakeholder accountability. Further studies are needed to test the feasibility of this model in ensuring quality LTC in Korea.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• IE interfaces
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• v.20 no.4
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• pp.448-457
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• 2007

The small & micro business has the characteristics of both consumer credit risk and business credit risk. In predicting the bankruptcy for small-micro businesses, the problem is that in most cases, the financial data for evaluating business credit risks of small & micro businesses are not available. To alleviate such problem, we propose a bankruptcy prediction mechanism using the credit card sales information available, because most small businesses are member store of some credit card issuers, which is the main purpose of this study. In order to perform this study, we derive some variables and analyze the relationship between good and bad signs. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. The experimental result shows that credit card sales information could be a good substitute for the financial data for evaluating business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0 multivariate discriminant analysis (MDA), and logistic regression.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.653-663
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• 2021

There has been a massive increase in household debt in China, especially in the last five of years. Learning from past experiences, the country needs careful forecasting that may help to form new policies or make amendments to the existing ones. This research paper aims to highlight the impact of the monetary policy on household debt in China. The study covers the time period from 1996 to 2020 The study employs a cointegration test, Autoregressive Distributed Lag Bound Test (ARDL) approach, a Augmented Dicky Fuller (ADF) and PP test (PMG) and time series data. The findings suggest on a quantitative analysis using a time-series model in which gdp per capita and interest rate has a positive impact on household debt whereas, cpi doesn't have significant impact. In a short-term variables relationship, household debt responds more to an increase in income than in the long-term. Also, the impact of interest rate changes on household debt is lower than income in the short run.The research suggests that there should be some restrictions on household debt and consumer financing provided to citizens and for this, appropriate leverage measures should be taken in order for the central bank to sustain robust macroeconomic conditions.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.69-78
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• 2024

Recently, consumers have shown an increasing tendency to seek information related to environmental, social, and governance (ESG) aspects in order to choose products with higher social value and environmental friendliness. In this paper, we proposes a product recommendation system applying ESG indicators tailored to the recent consumer trend of value-based consumption, utilizing a model called MultiSAGE that combines GraphSAGE and GAT. To achieve this, ESG rating data for 1,033 companies in 2022 collected from the Korea ESG Standard Institute and actual product data from N companies were transformed into a Heterogeneous Graph format through a data processing pipeline. The MultiSAGE model was then applied in machine learning to implement a recommendation system that, given a specific product, suggests eco-friendly alternatives. The implementation results indicate that consumers can easily compare and purchase products with ESG indicators applied, and it is anticipated that this system will be utilized in recommending products with social value and environmental friendliness.