• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.27-28
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• 2023

Currently, the Off-Site Construction (OSC) construction method, which emphasizes the minimization of field work, is being emphasized at construction sites due to the lack of construction skilled manpower, extreme weather, and the Severe Disaster Punishment Act. In this study, we developed a stacked PC modular, which is a method of stacking PC modules, and solved the lifting problem by reducing the weight of the unit module, which is emerging as the biggest disadvantage of PC modules, to around 20 tons. For the connection between modules, structural safety was secured through repeated history tests of the wall and slab connection. Walls and slabs satisfied all statutory fire resistance times through fire resistance tests, and residential performance was evaluated to be satisfactory through mock-up demonstration. The developed PC modular has been applied to the construction of commercial houses, detached houses, shopping malls, churches, etc., and has design results for many buildings such as dormitories, detached houses with 4 floors or more, and resorts, so it is expected that an atmosphere of revitalization of construction methods will be created.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.142-151
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• 2023

Sentiment analysis is a method used to comprehend feelings, opinions, and attitudes in text, and it is essential for evaluating consumer feedback and social media posts. However, creating sentiment dictionaries, which are necessary for this analysis, is complex and time-consuming because people express their emotions differently depending on the context and domain. In this study, we propose a new method for simplifying this procedure. We utilize syntax analysis of the Korean language to identify and extract sentiment words based on the Reason-Sentiment Pattern, which distinguishes between words expressing feelings and words explaining why those feelings are expressed, making it applicable in various contexts and domains. We also define sentiment words as those with clear polarity, even when used independently and exclude words whose polarity varies with context and domain. This approach enables the extraction of explicit sentiment expressions, enhancing the accuracy of sentiment analysis at the attribute level. Our methodology, validated using Korean cosmetics review datasets from Korean online shopping malls, demonstrates how a sentiment dictionary focused solely on clear polarity words can provide valuable insights for product planners. Understanding the polarity and reasons behind specific attributes enables improvement of product weaknesses and emphasis on strengths. This approach not only reduces dependency on extensive sentiment dictionaries but also offers high accuracy and applicability across various domains.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.1-8
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• 2023

Cross-domain recommendation is a method that shares related user information data and item data in different domains. It is mainly used in online shopping malls with many users or multimedia service contents, such as YouTube or Netflix. Through K-means clustering, embeddings are created by performing clustering based on user data and ratings. After learning the result through a transformer network, user satisfaction is predicted. Then, items suitable for the user are recommended using a transformer-based recommendation model. Through this study, it was shown through experiments that recommendations can predict cold-start problems at a lesser time cost and increase user satisfaction.

• Journal of Korean Home Economics Education Association
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• v.17 no.2
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• pp.29-47
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• 2005

In this study. we tried to provide basic materials for teachers to develop consumer's guide of internet shopping for middle and high school students through surveying their Purchase realities, clothing purchase behaviors. and clothing purchase attitudes when they use internet shopping mall. The questionaires were distributed to middle and high school students in Seoul, Daegu, Kyunggi, Chungbuk, Chungnam, Kyungbuk, and Kyungnam November, 2004. The followings are the results of this study. First, clothing items which were bought in internet shopping malls were shirts. shoes, pants, bags in order and they were below $20,000\~30,000$ won. Main payment method used was sending money to seller's account. Second, clothing purchase satisfaction degree was comparatively high but the satisfaction degree for the compensation policy was low. If they had any claims for the products. they were likely to behave more actively than passively. Third. returned items were shirts, pants, shoes in order which are the same as purchasing items and they were due to the size and the difference between the products recognised by computer screen and the real products. The $89.0\%$ of the subjects who have purchased clothing through internet expressed high intention to purchase in the future through internet. Forth the degree of attitude toward the internet shopping concerned with clothing purchase was high in the factor of 'convenience of shopping', especially they thought that the purchase through internet had the advantage of varieties and prices. The significant differences were found (1) in the experience of purchase and clothing purchase through internet according to their regions. school years, allowances per month, (2) in the purchased items through internet according to only their sexes, and (3) in the desired Purchase items through internet according to school years, their sexes. regions. The more frequently the middle and high school students use internet, the more goods they purchase through internet, especially the portion of the purchased clothing is getting bigger year by year. This suggests that we need to develope well-organized programs to teach good consumer's attitude to the middle and high school students when they purchase through internet.

• Journal of Distribution Research
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• v.10 no.2
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• pp.99-120
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• 2005

First, based on extant studies in the field, the author extracts environments, general and personalized interactions between an internet shopping mall and its customers, interactions among customers, and outcomes as 5 relevant dimensions of the service quality of an internet shopping mal She derives hypotheses on the relationships between each of the service quality dimensions and each of the three components of the relationship quality, satisfaction, trust, and commitment. She also investigates the moderating role of the relationship duration defined by the length of use in the relationships. She studies the relationships among the three relationship quality components and their effects on the future intentions of relationship maintenance, too. Through a survey on college students and adult consumers, she gathers 349 qualified questionnaires. Applying regression methods on the data, she finds out that most of the relationships between each of the service quality dimensions and each of the relationship quality dimensions are statistically significant but that the strengths of relationship are quite different dimension by dimension. The moderating effect of the relationship duration is not found except one case, the relationship between general interactions and trust. The author also finds out positive relationships between satisfaction and trust between satisfaction and commitment, and between trust and commitment. Positive relationships between trust and the future intention of relationship maintenance and between commitment and the future intention are found. But the data does not reveal any statistically significant relationship beetween satisfaction and the future intention. The author provides a few implications of the research results and future research agenda.

• Science of Emotion and Sensibility
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• v.23 no.1
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• pp.3-16
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• 2020

Recently, as the fashion e-commerce market has expanded, the proportion of online shops that are growing rapidly has increased and with them so too has competition. Most retailers operating online shops need their own competitiveness, and accordingly, the need to develop their logistics service quality components is increasing. This study investigated the quality of the logistics services, which is a factor of the logistics service quality of the internet shop. It influences customer satisfaction and repurchase intention by collecting samples from the customers using online fashion shops. Two hundred customers who shop online were surveyed to extract the data. The sample was subjected to basic statistical analysis using the SPSS 25.0 package, and factor analysis, t-test, ANOVA, and correlation analysis were performed. The results of this study showed that the information quality of proactive return, promptness of the return process, and reliability of the return cost had a positive impact on customer satisfaction, and it had a significant influence on the customer's repurchase intention to the online store. A selection of shops showed high amounts of return reasons, high customer satisfaction, and high repurchase, whereas, in general, many others scored poorly across these criteria. This suggests that a retailer operating online should consider pages for receiving information plus sales content in addition to the quality and constituent factors of its logistics services for returns that influence repurchase and satisfaction.

• Journal of Distribution Science
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• v.12 no.12
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• pp.55-63
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• 2014

Purpose - In urban regeneration projects, considerations for rejuvenating traditional public markets are becoming increasingly important. That is because the traditional market is not just a commercial space but also a living center for local people's existence. Cultural contents like these are invaluable assets in the contemporary economy. However, traditional markets are gradually declining because of changes in distribution systems and consumer lifestyles. New distribution systems such as modern distribution markets, home shopping, and online shopping malls made traditional markets less competitive. Further, traditional markets have not been able to adapt to the changing consumption styles of younger generations. Some say that it is a natural phenomenon that cannot be stopped. However, traditional markets are not just another distribution system but also a valuable resource that encapsulates the local people's tradition and history. Thus, a revitalization strategy for traditional public markets has become an urgent task in contemporary urban regeneration projects. This study aimed to find ways to activate traditional public markets by making it a community landmark based on visual merchandising perspectives. Research design and methodology - This study focused on analyzing Granville Island (Vancouver, Canada) as a role-model project for rejuvenating the traditional market. It investigated Granville Island both with walk-through evaluation and literature reviews. Results - We found that it has been developed not only to improve visual aspects, but also to promote cultural contents with high value added. For example, the developers maintained the visual elements that tell the original history of the site as an industrial factory. The renewal project had a balance between improving the outer look and creating attractive contents. The following are the merits of Granville Island that Korean traditional markets should note. First, they kept the whole area clean and hygienic. Second, merchants are well educated, business-savvy, and consumer-oriented. Third, the area's total environmental designs were done by professionals of a high caliber. Fourth, the city government and the merchants'association were collaborating well in their efforts to accommodate the changing needs of consumers. Conclusions - This study made the following suggestions as a conclusion. First, it will be a very powerful tool to rejuvenate the traditional market if we can discover unique cultural resources and develop them as cultural products, experiences, and events. Consumers of the 21st century have a strong tendency to consume not only material products, but also the experiences and memories attached to them. Second, in order to maintain the unique characteristics of traditional markets, fostering the viability of the merchants' association and local residents' society would be essential. Third, it is necessary to make the traditional market into a cultural place not only for the shopping patronage of local residents, but also for attracting tourists to increase sales. Finally, professional management and design approaches are needed in order to make the traditional market a pleasant space from a visual merchandising standpoint.

• Journal of Family Resource Management and Policy Review
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• v.9 no.2
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• pp.111-126
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• 2005

The purpose of the study was to find out some actual states qualities of consumers using of online mall users, as well as the factors that affect consumer satisfaction. A survey for this research was formed in order to find the consumer group between the ages of 20 and 30 who have experiences shopping online. From August 5th, 2002 to August 24th 2002, 424 were actually used tot this research The major results of the research were as follows. First, out of the people of the ages 20 to 30, the average age of people that actually purchase the online products was 27.7, and most were either office workers or students. Most of these people have purchased more than S products within a year, and won. Furthermore, $71.9\%$ of the payments were made using credit cards. The average days of using the Internet per week was 5.4 days, the average duration of utilization was 4 years, the average hours spent per day was 2 hours and 9 minutes, and the average time spent on searching information was 31 minutes per day. These peoples ability to put Internet to a practical use, their ability to use the information effectively, and the dangers of the Internet have received 3.66, 3.99, and 3.14 points out of the 5-point scale. In addition, the information search using the Internet received 3_44 points, and the consumer satisfaction received a fairly high score of 3.33 points. Second, the information searching factors involving the society and the Interact have showed efficiencies in people that received university education, people that purchase more than 3 products online per year, people that spend more than 100,000 won per year, and the people that make use of the Internet more often. Third, the customer satisfaction on Internet malls was greater in people that purchase more than 3 products, spend more than 100,000 won per year, make effective uses of the Internet, and Dow about the importance of the information search of the Internet. Fourth, the factors that affect customer satisfaction were the effectiveness of the Internet for searching information, the dangers of the Internet, and the hours spent on the Internet. The more uses of the Internet one makes, the less dangers one encounters, and the less one spends time on the internet, the higher ones customer satisfaction is was proven by this research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.159-166
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• 2023

This study analyzed what consumer characteristics affect the experience of using overseas direct purchase at a time when the overseas direct purchase market is rapidly increasing and consumers' interest in overseas direct purchase is increasing accordingly. For the study, personal data from the 2022 Korea Media Panel Survey were used, and data from 6,734 people who responded "yes" or "no" to whether or not to use overseas direct purchase among 9,941 total respondents were used for analysis. In addition, three variables (demographic, media utilization status, values and lifestyle) were selected among the items of the Korea Media Panel Survey. First, general characteristics were analyzed fo 6,734 people, then, Chi-square test and t-test were performed for comparative analysis between each variable according to the use of overseas direct purchase. Finally, logistic regression analysis was performed to identify the factors affecting overseas direct purchase. As a result of the analysis, 4 out of 5 demographic variables, 2 out of 3 media utilization variables, and 3 out of 7 values and lifestyle variables were derived as decisive factors for using overseas direct purchase. These results can be used to establish marketing strategies that can increase the use of consumers through domestic shopping malls, such as providing differentiated services for the sale of overseas direct shopping products on domestic shopping sites.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.