• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.1
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• pp.43-59
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• 2012

The purpose of this study was to compare knitwear design preferences and purchase behaviors of university students by sex. The subjects were 493 university students in Daejeon and Gongju provinces. The research method was a survey and measurement instruments were 16 stimuli which were manipulated of knitwear shape and self-administrated questionnaire (knitwear design preference items, knitwear favorite image items, purchase behavior items and subject' demographic attributions). Data were analyzed by factor analysis, frequency analysis, t-test, Cronbach' ${\alpha}$ using SPSS program. The results of the study were as follows. First, as for pullover designs according to pullover shape factors, male preferred classic design with normal round neck, set-in sleeves and normal length, whereas female preferred various designs with normal round, normal V or deep V neck, set-in sleeves and normal or long length. Second, there was significant difference by sex in knitwear patterns and materials. Male preferred geometric patterns and 100% cotton, whereas female preferred natural patterns and blended cotton. Third, 4 factors were emerged on knitwear favorite images(casual image, modem classic image, active image and characteristic image). Especially, there was significant difference by sex in active image. Male preferred active image, whereas female did not. Fourth, as for knitwear purchases, male considered fitting as important purchase criteria, whereas female considered design or style. Male used department stores for purchasing, whereas female used Bosejeom for independent fashion. Male preferred high quality knitwear to female.

• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.71-84
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• 2007

The architecture for RFID-based home network and an intelligent agent for efficiently managing home network are proposed in this paper. The agent consists of six modules-Agent Manager, Data Collector, Execution Controller, Data Storage, Data Queue and User Interface. Agent Manager manages the tasks of modules, and Data Collector collects the data from home appliances through the RFID readersm Execution Controller determines the operations home appliances according to the conditions of the home environment and transfers the operations to the appliances through the RFID readers. Moreover, Data Storage keeps the data which is necessary for the operations of the agent, and Data Queue temporarily stores the data which is collected from home appliances. Lastly, User Interface provides the graphical user interface in which an individual can directly control and monitor the home network. The proposed intelligent agent autonomously learns the circumstances of a home network by analyzing the data about the state of home appliances, and controls home appliances according to the preference of the user. Therefore, the user can live in the best-suited home environment without direct appliance control if he/she performs home networking through the agent.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.85-94
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• 2006

This study was conducted to suggest new development model for national & public parks by applying fascinating theme to the existing standardized development of those park. For this purpose, YeonIn Mountain Provincial Park was chosen as object of this research, which is located in GaPyeong, Kyonggi Province. The results from analysis of demand for tourism trend and development were as follows. Most of visitors(87%) come from the metropolitan area and their age are between the ages of 20 and 30. And the visitors' preference for accommodation is the independent villa style. For commercial facility, the strong expansion for food and beverage facilities and stores was needed. The future facilities and activities which they want to experience and e are health-recreation facility and ecological experience based on nature. From these results, It might conclude that we have to develop the qualified nature park with various theme focused on experience and recreation, and that we do preserve the environment.

• The Research Journal of the Costume Culture
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• v.13 no.1
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• pp.34-46
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• 2005

The purpose of this study was to research buying behavior and home fashion preferences based on housing size. The target consumers were Korean women, aged 20~40s who reside in the Seoul & Kyunggido areas. We distributed questionnaires to 650 women. However, only 600 questionnaires were used for the statistical analysis. Data analyses were conducted with SPSS program on the frequency, Chi-square test, cluster analysis, t-test and ANOVA. The results of this study are as follows: 1. The considering factors for purchasing such as brand, trends coordinating existing furnishings with new products and functionality were significantly associated with housing size. The buyers who reside in bigger size homes. over 40 pyung place higher value on brand name, trends. or coordinating existing furnishing with new products than residents in smaller units. However, women who live in smaller units place higher value on functionality when purchasing home fashion products. Considering factors such as brand, trend, and materials were also significantly associated with segmented age group; 40~49 age group considered brand, trend, and materials more than 20~29 age group. The group who are highly interested in home fashion considered design/color, rand, coordination, and functionality than the group who are low interested in home fashion. 2. Residents in over 40 pyung homes buy home fashion products at department stores, while residents in less than 39 pyung homes buy them at discounted store. 3. Respondents preferred solid colors more than patterns. However, they favored character pattern for textile bedding products for their children. 4. there is also a statistical difference in preferences for types of window treatments between large ad small housing sizes. Residents living in over 40 pyung preferred tie-back/cottage curtain, while residents living in less than 29 pyung preferred Roman shade style.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.1
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• pp.105-116
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• 2017

Murals in villages revitalize communities and spaces, and are economically efficient. Central and local governments are therefore actively undertaking Mural Village Projects but there are some issues and concerns about the projects for the provision of uniformed landscapes for the regions that are the result of a short-term completion of projects, and instead of cohesion, cause destruction of place identities. In addition, the problem of sustainable landscape management that is the result of low community involvement can be pointed out because the murals are products of government-led projects. The study covered the context of landscape and space change processes from a critical perspective, and focused on Ihwa-dong Mural Village, which is considered the first mural village in Korea and has begun to undergo drastic changes due to attention received from media. The purposes of this study are as follows. First, the study provides data about difference of place identity perception and landscape preference between residents and tourists in Ihwa-dong Mural Village. Second, this paper evaluates the current Mural Village Projects and finds alternative directions to improve the projects by using these data. This paper analyzed tourist hot spots in Ihwa-dong Mural Village by using SNS analysis, a field study and focus group interviews. The difference of place identity perception and landscape preference was examined among three groups: residents, new residents who are invited by Mural Village Projects, and tourists. This study showed that many tourists are focused on landscape areas that were not intentionally constructed projects. In addition, the locations of preferred landscapes and stores overlapped. Meanwhile, using qualitative data analysis, it was found that residents perceived the area as being an under-privileged location, while the murals, a non-daily landscape, largely affected place identity perception of new residents and tourists. For landscape preference, tourists preferred outdoor rest areas, while new residents and residents preferred less. Additionally, new residents and tourists preferred an area's night view while residents made no mention of this. Related to the direction of the projects, three groups showed their dependence on the government. This empirical study is significant from a participatory design perspective and in analyzing the issues for mural villages' landscapes, which are spreading across the nation and proceeding without criticism in urban regeneration. Implications for urban planners and suggestions for the future projects are given.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.53-67
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• 2009

For the last decades, service quality has been studied as one of the most important tools for a service company to compete with the other companies. Based on these past researches, it has been agreed that the service quality is a basic and powerful tool to create the competitive advantage. Due to similar reason, many service marketing practitioners have been also focused on the service quality to retain the existing consumers and collect the new consumers. However, service quality is subjectively perceived by individual consumers. Consumer evaluation of service quality can be different from each other. Especially consumers with one life-style may evaluate the service quality differently from the consumers with the other life-styles. Therefore we need to know whether there are differences in service quality perception on the categories of life-style. Life-style refers to a distinctive mode of living in its aggregate and broadest sense. It embodies the patterns that were developed and emerged from the dynamics of living in a society. Since the concept of life-style and its relationship to marketing was introduced in 1963 by William Lazer, methods of measuring the life-style and their application have been developed. Life-style has been usually used to segment the marketplace because it offers marketers a unique and important view of the market. When Life-style is combined with clustering methods, life-style segmentation can generate identifiable whole persons rather than isolated fragment. Life-style segmentation begins with people instead of products and classifies them into different life-style types, each characterized by a unique style of living based on a wide range of activities, interests, and opinions(Plummer, 1974). In this study we applies the life-style segmentation based on the AIO(Activities, Interests, and Opinions) to the consumers of the large discount stores. In Korea, the large discount store market has entered into maturity stage so that the market differentiation strategy is becoming a more critical issue to the marketing practitioners. One of the most important tools to differentiate from the competitors in large discount store market is continuously to provide service of better quality than competitors. This study tries to find answers about the following questions: 1) How can we categorize the consumer life-styles in the large discount store? 2) What are the characteristics of the categorized groups? 3) Are there any differences in service quality perception among the consumers with different life-styles 4) Are there any differences in consumer behavior among them in the large discount store? For the purpose, we collected survey data from consumers and analyzed the data with the SPSS package where we had $X^2$-test, factor analysis, ANOVA, MANOVA, and cluster analysis. The survey was made during one month in the April of 2008. Among the collected 306 copies of questionnaires, 281 copies were chosen as the effective samples for empirical analysis except 25 copies with wrong responses. To identify the life-style patterns, we used the measures employed by Kim and Kwon(1999), where 44 items on a seven-point scale were used to measure factors of the life-style patterns. The Principal Component Method was used for factor extraction, and the VARIMAX orthogonal factor rotation was employed. The 7 items showing low factor loading were eliminated. The results of the factor analysis suggested that nine factors of the life-style patterns were identified as follows: 1) the equality-of-sexes and pursuit-of-independence tendency 2) self-management tendency 3) sociable tendency 4) self-display tendency 5) degree of a dilettante life 6) pursuit-of-information tendency 7) bargain hunter tendency 8) TV preference tendency 9) pursuit-of-leisure tendency. Next, after the K-means cluster analysis was performed with nine factors of the life-style patterns, the life-styles of the respondents were classified into four groups which are named as the 'progressive practicality-oriented group', 'positive success-oriented group', 'sociable ostentation-oriented group', 'stable conservation-oriented group'. The analysis results for usage behavior between the market segments showed statistically significant differences in the frequency of usage, duration time in the store, consumer satisfaction, and loyalty. Also, we tried to investigate whether the large discount store consumers differently perceive the quality of service based upon the types of life-style. To measure the service quality of large discount store, we adapted several measurement models measuring the service quality such as SERVPERF, BCP, R-SERVPERF, R-BCP. MANOVA and One-Way ANOVA were performed to confirm the difference in service quality perception based on the market segments. The results have also shown significant differences between life-style types in service quality perception. These findings show that the large discount store marketers should consider consumer life-style as one of the most important market segments for marketing and understand the difference in service quality perception between life-style types. Our findings give important implications to marketers of large discount stores as well as life-style researchers. First, this study showed there were significant differences in consumer's service quality perception and usage behavior between the types of life-style. It provides evidence that the life-style approach can be a important basis in segmenting the large discount store market and will make consumers perceive the service quality high. Second, most previous researches on service quality have been in aggregate level. However, our results imply that the future research on service quality have to focus on segment level.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• The Korean Journal of Food And Nutrition
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• v.28 no.1
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• pp.47-59
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• 2015

In this study, we investigated the dietary habits, snacks, and self-purchasing snacks (SPS) intake behaviors of 519 elementary school students (boys=239, girls=280). Obesity was significantly higher (p<0.05) in boys (24.8%) than in girls (14.7%) and the proportion of underweight subjects was higher compared to normal or other weight groups for both the boys and the girls. There were 7.5% of the subjects in the group that always skipped breakfast, and the main reason of skipping breakfast was insufficient time (51.9%). The snack intake frequency was once or twice per week for 23.1% of the subjects and three or four times per week for 25.1%. The SPS intake frequency was the subjects zero for 35.6% of the highest level of the responders, while 6.8% of the respondents took more than once SPS per day. 59.6% of the respondents consumed SPS due to hunger while 15.0% consumed SPS out of boredom. The SPS was purchased from supermarkets in 34.5% of the cases, from convenience stores in 24.1% and from snack corners in 20.0% of cases or from a store near school in 14.5% of the cases. Analysis of SPS behaviors according to obesity index showed that parent's opinion of 'permission to buy SPS as needed' had a significant effect in 64.5% over weight subjects compared to only 53.7% in underweight groups. The subjects who used more than 3/4 of their pocket money to buy SPS was higher in the overweight groups (16.4%) than in the underweight groups (7.0%) and normal weight groups (9.8%). The favorite snacks and SPS were milk and yogurt for 45.7% of the subjects, fruits for 42.7%, ice cream for 26.4%, fruit juices for 23.8%, sweet stuff for 16.4%, frozen dessert for 8.9%, and chocolate or candy for 8.1% in descending order. The intake frequency of milk, yogurt, and fruit juices was higher in the underweight groups, but the intake frequency of sweet stuff, frozen dessert, and chocolate or candy was higher in over weight groups. The intake of frozen dessert was more than four times higher in the overweight groups than in the underweight groups. In conclusion, dietary habits, snacks, and SPS intake behaviors were similar between the boys and the girls and obesity groups, but most students appeared to have a high preference for intake snacks and SPS. Therefore, education for appropriate snacks intake habits will be beneficial for improving their dietary habits and health.

• Korean Journal of Community Nutrition
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• v.13 no.3
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• pp.374-385
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• 2008

A study has been performed to provide the basic information about the current dietary habits, health related behaviors, and body indices and to bring forward the importance of this information to the people's attention based upon the relation between employee's life patterns and health conditions in their daily lives. Three hundred and five department store workers were examined from August 2006 to September 2006. With the average BMI values $23.9{\pm}2.2$ for males and $20.0{\pm}1.9$ for females, both gender groups were in normal, but 62.2% of the males were overweight and 15.4% of the females were under-weight. Regarding dietary and health related factors on how they perceive themselves, as normal were 204 (66.9%) the most and bad and very bad were respectively 43 (14.1%) and 5 (1.6%). Half of the subjects (43.2%) perceived sleeping hours to be insufficient, and 64.4% of them need to exercise regularly. As problems related to eating habits, they reported irregular meal times, overeating, preference of hot and spicy food, skipping meal, unbalanced meals. Regarding weight control they have attempted were the most (73.0%), after weight reduction, 51.2% of the subjects had side effects, such as gastrointestinal troubles, anemia, dizziness, sense of fatigue, constipation, physiological disorder, and diarrhea, etc. In the food habit score, it was shown that overall average score of the subjects was $62.63{\pm}9.86$ which is lower than other studies. Female ($62.76{\pm}10.15$) had better score than male ($61.67{\pm}8.06$). While the item with the highest point was eat all three meals of the day, that was the lowest point, exercise every day. The food habit score of the younger group had lower than older group, and also they preferred sweet foods to other group. The results suggest that nutrition education for workers at specific working fields needs to be more focused on the improvement of dietary habits and health status of workers.