• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.6 s.165
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• pp.869-878
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• 2007

The purpose of this study was to investigate perception of risks among South Korean female college students within the process of purchasing apparel products through the Internet. The study was implemented by descriptive survey method using questionnaire and subjects consisted of 324 South Korean female college students. Findings of the study showed that the purchasing process particularly regarding delivery and security issues seemed to be a strong concern. On the other hand, unique selection such as apparel brands only available through the Internet was a strong appeal to 37.7% of subjects. Factor analysis profiled risk perception as: 1) Internet Shopping Selection Preference, 2) Delivery Problems and Lack of Security 3) Product Quality and Characteristics 4) Return Policy Difficulties and 5) Fair Prices. Discriminant analysis showed Factors 1, 2 and 3 were significant in helping to differentiate among Non-Purchasers, Fewer-purchasers and Many-Purchasers. Factor 1 and 3 helped differentiate among respondents relative to age range. Across all types of purchasers, offering unique selections of cutting edge fashions and improving risk perception relative to delivery and security concerns seemed important for gaining greater market share. Being able to delivery quality products and communicate product characteristics would be a powerful competitive edge to add to the incentive of convenience in shopping for apparel on the Internet.

• Journal of Distribution Science
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• v.14 no.4
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• pp.117-125
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• 2016

Purpose - As consumers' needs for purchasing fresh and safe food have been bigger in Korea, their interest in local food is also growing recently. So, the number of local food stores has been increased from 3 in 2012 to 103 in 2015. Local food stores should operate a business responding consumers' needs in order that local food stores are not to be a one-time fad. Therefore, the purpose of this study is to analyze the characteristics of consumers who use a local food store and provide helpful implications to design a strategy for sustainable growth of local food store. Research design, data, and methodology - In this study, Probit model was used for empirical analysis in order to examine the effect of purchase choice attributes of agricultural products, consumer's satisfaction, and their demographic factors upon the intention to use a local food store. After estimating coefficients of the probit model, marginal effects were calculated as a standard normal, and cumulative distribution is differentiated with respect to explanatory variables. To collect the data, questionnaire survey was carried out with the consumers using the local food store (Youngjin Nonghyup near to Jeonju city located in Jeollabuk-do). Result - The data analysis found that the more consumers are satisfied with local food store, the higher intention they have to use the local food store. In addition, it was known that the factors related to quality of agricultural products and shopping convenience among the purchase choice attributes have a considerable impact on the purchase intention of a local food store. In demographic factors, income was turned out to be an important factor affecting purchase intention of local food. Such a result supports the hypothesis that high income consumers are likely to purchase local food, which is based on the inference that consumers who have a high income tend to pursue wellbeing life. Futhermore, information delivery, through a reputable media source among general factors, was known to play an important role in forming an intention to purchase local food. According to the analysis of marginal effects, probability of purchase intention of a local food store is increased by 11.4%, if a monthly average income of a household is above 4.5 million Won(Korean currency). If purchasing satisfaction with local food stores is high, the probability of purchase intention would be increased by 24.1%. Likewise, such a probability goes up by 8.7%, 5.8%, respectively as an increasing one unit of quality of agricultural products and shopping convenience of local food stores, respectively. Conclusion - For attaining sustainable growth in a local food store, it is considered necessarily to establish a proper store operation system to meet consumers' needs, especially for quality and shopping convenience of local food. Moreover, as it was found that appropriate communication through media source has a positive effect on the intention to use local food store, PR activity seems to be necessary to expand the consumers' demands for local foods.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• Journal of the Korean Society of Food Culture
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• v.27 no.6
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• pp.646-658
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• 2012

This study was conducted to investigate the differences in households, parental perception, and dietary behaviors of preschool children from kindergartens with environment-friendly food service (environment-friendly food service group; EFG) versus children from kindergartens with general food service (general food service group; GFG). We sought this basic information to examine the impact of environment-friendly agricultural products in preschool food services. Age, education level, and monthly family income of the EFG were significantly higher than the GFG. The frequency of purchasing environment-friendly agricultural products was significantly higher in the EFG than the GFG, with the most frequently purchased items in both groups being vegetables. The GFG had a significantly higher perception than the EFG in the superior quality of environment-friendly agricultural products; however, a greater proportion of the GFG than the EFG thought environment-friendly products were too expensive. The most frequent reason for purchasing environment-friendly agricultural products in both groups was safety. When purchasing environment-friendly agricultural products, the most important selection factor for the majority of both groups was the label certifying quality assurance. Both groups also considered price reduction as essential for promoting environment-friendly agricultural products. In regard to parental perceptions on food service in kindergarten, the EFG had a significantly higher satisfaction with the nutritional adequacy of the menu compared to the GFG. Both groups considered food safety and health as primary reasons for using environment-friendly foods in the preschool food service, with a greater proportion of the EFG than the GFG responding this way. There were significant differences between the EFG and GFG, as the main satisfaction from using environment-friendly foods in the EFG was safety, freshness, and good hygiene, whereas the main satisfaction in the GFG was a good food service menu, freshness and good hygiene. Dietary behaviors of preschool children in the EFG were also significantly superior to the GFG. Thus, environment-friendly agricultural products have positive effects on the dietary behaviors of preschool children and should be increased in the preschool food service. Lowering prices and a strict supervision of quality assurance is also necessary to promote consumption of environment-friendly food materials.

• Korean Journal of Community Nutrition
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• v.25 no.6
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• pp.464-473
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• 2020

Objectives: The purpose of this study was to compare and analyze e-commerce food purchase behavior and the perceptions of adult women according to their household types. Methods: The e-commerce food purchases of 318 adult women were surveyed and analyzed according to their household types (one-person or couple household (OCH); a household with children (HC); a household with parents (HP)). Results: The total amount of food purchases over 6 months through e-commerce according to household types was in the descending order of OCH (60.3%), HC (57%), and HP (55.1%) thus showing a significant difference (P < 0.05) in behavior between household types. The reasons for purchasing food through e-commerce included: a lower price than offline (30.8%), convenient delivery and transportation (30.2%), and food diversity (21.1%). When purchasing food online, the most important factor was price and quality, followed by quick and accurate delivery for OCH, exact information given about the product for HC, and recommendation from other consumers for HP (P < 0.01). The main foods purchased through e-commerce were coffee, tea (42.1%), instant and frozen foods (39.9%), water, beverages, dairy products (37.7%), snacks, bread, rice cakes (31.5%), and functional foods (27.4%). The percentage of respondents who were very satisfied or satisfied with their e-commerce food purchases was HP (84.1%), OCH (69.9%), and HC (65.6%) in that order (P < 0.05), and 96.5% of all subjects stated that they would be willing to purchase food through e-commerce in the future. The advantages of purchasing food through e-commerce were seen to be the highest in order and payment convenience with 4.1 points out of 5, followed by low price (4.0), variety of products (3.9), and ease of food purchase (3.9). Among the disadvantages listed, concerns about product damage and deterioration during delivery and differences between the displayed product and the delivered product were the highest with 3.7 points. Conclusions: The characteristics and perceptions of female consumers according to household types are important factors in enhancing the reach of e-commerce, and in preparing guidelines for food selection through e-commerce.

• Korean Journal of Human Ecology
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• v.23 no.6
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• pp.1171-1189
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• 2014

In order to provide the basic data for creating the environment which can efficiently reflect prefer fit along with body size when selecting clothes size in the indirect purchasing environment, this study analyzed the difference of ready-made jacket part-specific fit preferred by fashion models in their twenties and female college students. This study was to analyze the impact of body size, recognition of body part-specific characteristics shape, body satisfaction on prefer fit of jacket. As for the difference of prefer fit depending on the body size, female college students preferred more loose fit than models. The difference according to recognition of body part-specific characteristics shape turned out to be significant for prefer fit depending on the degree of bend of neck, arm length, bend of back recognition and matching fit was found to be preferred as they recognize their body shape to be normal and the difference according to body satisfaction appeared to be significant in the terms of bend of back, hip width/protrusion, torso size/length, sleeve length, whole body shape and they turned out to prefer matching fit as they are satisfied with their body. As shown above, body size, recognition of body part-specific characteristics shape, especially body satisfaction have a great influence on prefer fit of jacket and therefore, if preparing for a size selection step according to body shape and satisfaction in the jacket size selection process, customers' satisfaction in jacket size may be improved and it is considered to be helpful for both consumers and sellers.

• Health Policy and Management
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• v.15 no.2
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• pp.16-36
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• 2005

Due to the existence of asymmetry of information between doctor and patient, it has been believed that doctor might affect patient's decision making process of purchasing medical care. Based on this notion, doctor's reimbursement method has been suggested as an effective policy device of improving efficiency of patient's medical care use by way of its affecting doctor's practice pattern. By using the Community Tracking Study (CTS) household and physician data set, which includes not only various information on patient's medical care use, but doctor's practice arrangements and sources of practice revenue, this paper investigates the effect of community doctor's characteristics of reimbursement method on community patient's medical care use under the control of patient's socio-demographic characteristics and community doctor's practice type. In the process of estimating econometric model, the endogeneity problem of individual health insurance purchase was corrected by using 2818. And due to the existence of sample selection problem, Heckman's two-step estimation method was used for strengthen the robustness of estimation which was adversely affected by sample selection problem The empirical results show that as the average value of community doctor's portion of practice revenue determined by prospective method out of total revenue increases, the community patient's total out-of-pocket medical cost decreases. This results suggest, as doctor's practice revenues are mainly determined by prospective method, such as capitation, doctors would be more conscious about practice cost, which might affect doctor's practice pattern and by which his/her patient's use of medical care would decrease.

• Journal of the East Asian Society of Dietary Life
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• v.19 no.6
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• pp.1009-1017
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• 2009

This study was performed to analyze the preferences and actual use patterns of university students (96 males and 187 females) for bakeries in the Gyeongju area of Korea. A total of 283 questionnaires were used for the examination and statistical analyses were completed using SPSS Win (14.0) by descriptive analysis and $x^2$-tests. The most favored bakery products were prepared items such as sandwiches and toast. Most of the respondents (92.9%) typically used bread for snacks, and the main places of purchase were well-known bakery shops (38.5%) in which females preferred well-known shops more than males. In addition, the respondents liked milk (79.9%) and jam (39.7%) as the beverage and food, respectively, to eat with bread. When choosing bread, the main selection point was taste (80.2%) and the cost per person per visit was usually 1,000~5,000 won (63.3%). The consumption frequency rate revealed that 49.1% of the students consumed bread as a snack, while 24.8% consumed bread with other foods 1~2 times a week. In the case of purchasing bread as a snack, females had more purchases than males (p<0.05). Students who lived in their own home (p<0.001) with a commute time to school greater than 30 minutes (p<0.001) had the highest number of bread purchases as a snack. The most important point for bread purchase was hygiene (4.60). Overall, for the development of bakeries in the Gyeongju area it seems imperative to address the bakery shop environment, including such aspects as hygiene, price, and new bread product development for students.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• Knowledge Management Research
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• v.24 no.4
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• pp.63-85
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• 2023

This study aims to identify the primary user group in the growing metaverse space based on the increased interest during the COVID-19 era. It also aims to explore the predictive factors for metaverse adoption. To predict online activities, the study examined user purposes, motivations, and relevant demographic factors as predictive variables through model analysis. The data from the Korean Media Panel Survey were used, and a two-stage analysis with the Heckman two-stage sample selection model was conducted to predict metaverse users. The analysis revealed that the key factors influencing metaverse adoption were offline activities, openness, OTT usage, and purchasing of paid content. Moreover, in the second stage model, openness, gender, and paid content purchases were identified as significant variables for increasing metaverse usage time. These results indicate that understanding metaverse users is essential in the context of the rising interest in online activities during the COVID-19 era and can provide valuable insights for metaverse platform-related companies and developers.