• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.70-79
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• 2010

There has been some research conducted that addressed immoral consumer behaviors in Korea; however, most of this research focused on purchasing counterfeits or shoplifting. High return rates of apparel and used apparel returns have been acknowledged as problem areas within the fashion industry. However, very few researchers have addressed this issue. Therefore, the goal of this research was to explore consumer's retail borrowing experience using a mixed methods approach. In study 1 Korean consumer's retail borrowing experiences was explored through focus group interviews. Findings informed study 2 an examination of apparel consumers' attitudes toward retail borrowing behavior via an online survey. Findings assist both researchers' and practitioners' understanding of retail borrowing behaviors and provide insight into retail borrowing issues in the apparel retail industry. For study 1, five focus-group interviews were conducted with seven panels of individuals that had retail borrowing experience within the past year. Thirty-five Korean consumers who lived in a metropolitan area participated in the focus group interviews. Most of consumers were in their 20's (n=21) and were women (n=24). Most participants purchased apparel items from a retail store and returned the worn items for either a full refund or exchanged the worn item for another item. Motives underlying retail borrowing behavior included social needs, job-related needs, fashion needs, and "smart shopping." Similar to existing research findings from other countries, social needs were the most frequently mentioned cause of retail borrowing in fashion stores. Consumers' moral values, attitude toward large corporations, and prior retail borrowing experience were mentioned as possible factors affecting consumers' retail borrowing behavior. For study 2, the questionnaire used to gather the data was developed based on the findings of part I and existing research. Questions concerning consumers' moral beliefs, sensation seeking tendencies, self-worth, past retail job experience, retail borrowing experience, and some demographic characteristics were included in the questionnaire. The data were collected via an online survey using an online panel provided by a commercial online research company located in Seoul, Korea. In order to obtain various consumers, a quota sample was (male: female=1:1, 20's:30's:40's=1:1:1, retail experience: no retail experience=1:3) obtained from the company. A total of 401 consumers who had shopped for apparel items during the prior 6 months participated in the online survey. The results indicated that 19.7% of the respondents reported they had experience borrowing fashion merchandise. Among these individuals, male borrowers (57%) outnumbered female borrowers. In terms of age distribution, x2 revealed that there was a statistical difference between respondents with and without retail borrowing experiences: 41.8% of the respondents with retail borrowing experience were in their 40's, while respondents without retail borrowing experience were evenly distributed between their 20's to 40's. There was also a significant difference between respondents with and without retail borrowing experience in terms of income: respondents with retail borrowing experience tended to have higher incomes than those without retail borrowing experience. T-tests were performed to compare respondents' fashion shopping behavior, moral beliefs, sensation-seeking tendencies, and attitudes toward retail borrowing behavior between participants with and without retail borrowing experience. As compared to those with no borrowing experience, respondents with experience tended to shop for fashion items more frequently and spent more on shopping for fashion items. Consumers with experience borrowing tended to have higher sensation-seeking tendencies than consumers without retail borrowing experience. A regression analysis revealed that attitudes toward fashion retail borrowing were negatively related to consumers' moral beliefs, but positively related to monthly fashion shopping frequency, sensation-seeking tendencies, and past fashion retail borrowing experience. Among these variables, past retail borrowing experience was the most significant predictor, followed by moral beliefs. This research serves as an initial attempt to address the motives that underlie retail borrowing behaviors and the factors affecting those behaviors. The findings of this study may facilitate an understanding of the consumer's retail borrowing, which will provide a basis for approaches that may help decrease retail borrowing and inappropriate returns at fashion retail stores. The findings may also provide materials for consumer education over the long term. In order to better understand fashion retail borrowing behavior, more research is needed in the future.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Distribution Science
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• v.14 no.1
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• pp.67-74
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• 2016

Purpose - In this paper, the degree of similarity and dissimilarity between pairs of 50 major cities in China can be shown on the basis of three evaluation variables(internet businessman index, internet shopping index and e-commerce development index). Dissimilarity distance matrix is used to analyze both similarity and dissimilarity between each fifty city in China by calculating dissimilarity as distance. Higher value signifies higher degree of dissimilarity between two cities. Cluster analysis is exploited to classify 50 cities into a number of different groups such that similar cities are placed in the same group. In addition, multidimensional scaling(MDS) technique can obtain visual representation for exploring the pattern of proximities among 50 major cities in China based on three development performance attributes. Research design, data, and methodology - This research is performed by the 2013 report provided with AliResearch in China(1/1/2013~11/30/2013) and utilized multivariate methods such as dissimilarity distance matrix, cluster analysis and MDS by using CLUSTER, KMEANS, PROXIMITIES and ALSCAL procedures in SPSS 21.0. Results - This research applies two types of cluster analysis and MDS on three development performances based on the 2013 report of Aliresearch. As a result, it is confirmed that grouping is possible by categorizing the types into four clusters which share similar characteristics. MDS is exploited to carry out positioning of both grouped locations of cluster and 50 major cities belonging to each cluster. Since all the values corresponding to Shenzhen, Guangzhou and Hangzhou(which belong to cluster 1 among 50 major cities) are very large, these cities are superior to other cities in all three evaluation attributes. Twelve cities(Beijing, ShangHai, Jinghua, ZhuHai, XiaMen, SuZhou, NanJing, DongWan, ZhangShan, JiaXing, NingBo and FoShan), which belong to cluster 3, are inferior to those of cluster 1 in terms of all three attributes, but they can be expected to be the next e-commerce revolution. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three attributes, so that this automatically evokes creative innovation, which leads to e-commerce development as a whole in China. In terms of internet businessman index, on the other hand, Tainan, Taizhong, and Gaoxiong(which belong to cluster 2) are situated superior to others. However, these three cities are inferior to others in an internet shopping index sense. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three evaluation attributes, so that this automatically evokes innovation and entrepreneurship, which leads to e-commerce development as a whole in China. Conclusions - This study suggests the implications to help e-governmental officers and companies make strategies in both Korea and China. This is expected to give some useful information in understanding the recent situation of e-commerce in China, by looking over development performances of 50 major cities. Therefore, we should develop marketing, branding and communication relevant to online Chinese consumers. One of these efforts will be incentives like loyalty points and coupons that can encourage consumers and building in-house logistics networks.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.5
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• pp.16-26
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• 2004

As the importance of outdoor lighting become more widely recognized, outdoor lighting has been installed in many buildings, plazas, landscape, and historical monuments in Korea, Outdoor lighting on showing complex, in particular, express its values as local landmarks. However, the excessive outdoor lighting in the large-scale shopping complex tends to cause light pollution. Many advanced countries are trying to create a comfortable lighting environment by the guidlines and regulations on outdoor lighting to prevent light pollution. For this research backgrounds, the light pollution of three showing complexes in Seoul have been investigated. For the purpose, luminance of building facade, horizontal illuminance, and vertical illuminance were measured with proper measurement instruments and compared the results with the CIE recommendations. The results of the study are as follows. As no cut-off luminaries are currently installed on pedestrian walks, some glare were occured partially. It also shows that the luminance of building facades are high to improve the degree of public awareness of buildings and advertisements. In other words, the luminance of the building facade, when compared with that of the CIE recommendations, is twice as high and the vatical illuminance of pedestrian walks is far higher than that of the CIE recommendations, which proves the existence of light pollution. As Korea has not yet provided proper regulations or guidelines for the control of light pollution, it is necessary to make appropriate codes for it.

• Culinary science and hospitality research
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• v.23 no.2
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• pp.104-116
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• 2017

The purpose of this study was to conduct an empirical survey on consumer perception and consumption behavior in relation to local food and eco-friendly food. The survey was conducted using 266 consumers who have heard about or purchased local foods and eco-friendly foods centering on Seoul and Gyeonggi-do, and statistical analysis was carried out using SPSS (Version 23.0) to generate descriptive statistical values such as frequency and percentage and implement a Chi-square test. The results showed that consumers purchased local food in large shopping malls, supermarkets, and local food stores, whereas eco-friendly food were usually bought in large shopping malls, supermarkets, and eco-friendly food specialty stores. For local food, consumers bought fruits the most, followed by vegetables, whereas for eco-friendly food, consumers purchased vegetables the most, followed by fruits. The top reason for purchasing local food was its "fresh and high quality," whereas the top reason for buying eco-friendly food was "safety from pesticides and additives." According to results of the Chi-square test, women, unmarried people and younger people turned out to have more experiences in purchasing local foods and eco-friendly foods compared to men, married people and older people, respectively. Although local and eco-friendly food were completely different concepts, results of the study show that consumers were not able to make a clear distinction between the two. Consumer education, therefore, should involve defining the two types of food and spreading awareness on local and organic food to help them made the right choices when buying food.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.293-303
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• 2018

This paper aimed to research the brand personality, brand equity, and brand value of Taobao and Jindong (JD) as well as the difference between the two brands. Chinese consumers receive the questionnaire survey in groups. A total of 321 questionnaires were distributed, of which, 162 for Taobao and 159 for JD. The findings, first, determine the brand personalities of Taobao(sincerity, sophistication, competence and excitement) and JD(competence, sophistication, and excitement). Second, find the influential relationship between brand personality and brand equity. For Taobao, the sincerity of personality has a positive impact on brand loyalty, image and perceived quality. The competence impact on brand loyalty, awareness, and image. The sophistication impact on brand image and perceived quality. Competence and sophistication of the JD personality impact on the brand equity. Excitement of JD impact on the perceived quality. Third, the brand loyalty and perceived quality of Taobao have a positive influence on the brand value; and brand loyalty, image, and perceived quality of JD have a positive influence on the brand value. In the future research, the findings of the research provide a theory basis for the brand management, and can take more consideration into the relations among other variables in the context of online shopping environment.

• Journal of Navigation and Port Research
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• v.28 no.10 s.96
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• pp.869-874
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• 2004

Digital TV broadcasting's resolution or tone quality is very excellent than analog broadcasting and has many advantages including various multimedia functions such as home shopping, home banking, internet search, telecommuting, VOD, etc. In this study, it is essential to analyze the regional electromagnetic environment before Digital TV broadcasting, and therefore we analyzed Busan area's limitation using ETRI propagation model. For maintaining high-quality Digital TV signals, we measure electric field intensity wide and far in Busan including mountains area and high-rise buildings. Generally, it has lower value by a standard ETRI propagation model than simulated value about standard model, but distribution pattern are similar with it. Compared theoretical values with the measured results, they have similar values for flat area but very different values for crowded city area and mountains area So we conclude that ETRI propagation model and theoretical model are not suitable for Busan in a free space.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.103-112
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• 2012

This research introduces a trip generation model reflecting time-series effects derived from a panel analysis with the data collected from the national household trip surveys conducted in 1996, 2002 and 2006. The existing methods are unable to reflect time-series effects from the change of socioeconomic conditions because the parameters applied to the model were basically from the base year of study - the parameter values were unchanged. This study proposes a new trip generation model developed through a panel analysis performed with the data collected from the last three national household trip surveys. From the results, it was found that the number of school trips increases and that the number of shopping trips decreases as time passes. The results showed that there are time-series effects affecting in trip generation.

• Fashion & Textile Research Journal
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• v.20 no.1
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• pp.50-62
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• 2018

The global volume of luxury fashion industries has continuously grown with the influx of young consumers in 20s and 30s, yet little research explores luxury consumption patterns of the young consumers. Given the crucial importance of socio-psychological shopping values in luxury, the current study explores the effects of self-congruity and functional congruity on purchase intentions of luxury fashion brands, and the moderation of self-construal in the mechanisms. An online study was conducted through Google Forms with a total of 227 Korean respondents of actual luxury consumption experiences. The data was analyzed using SPSS 18.0 program. The results of the study reveal the following: (i) Among the three factors of self-congruity, ideal and social self-congruity factors have significant positive effects on purchase intentions; (ii) actual self-congruity has no statistical effect on purchase intnetions of luxury fashion brands; (iii) functional congruity has a significant positive effect on purchase intentions of luxury fashion brands; (iv) no moderation effect of self-construal was found in the relationships between the three factors of self-congruity and purchase intentions; (v) the moderation effect of independent self-construal is significant but negative in the relationship between functional congruity and purchase intentions; (vi) the effect of intdependent self-construal is not found to be significant in the relationship between functional congruity and purchase intentions. Managerial and theoretical implications are discussed.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.1-10
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• 2018

This study investigates Chinese consumers who have recently purchased products through internet personal broadcasting of Wang Hong and explores how factors related to Wang Hong, broadcasting contents, and products affect purchasing satisfaction of consumers. The present study also examines whether this satisfaction affects the consumer loyalty to the shopping through the Wang Hong in the future. The results indicated that consumers' perception of the informational level rather than entertainment level of broadcasting contents had significant effects on the product satisfaction. The perceived uniqueness and credibility of Wang Hong were found to have positive impacts. In terms of products, the more consumers perceived the product to fit their images or values, and the higher the fit between the images of Wang Hong and the endorsed product, the higher the satisfaction with the product. Product satisfaction increased the customer loyalty, including the intention of repurchasing products endorsed by the Wang Hong.