• The Research Journal of the Costume Culture
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• v.24 no.6
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• pp.709-724
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• 2016

The purpose of this study is to develop a multi-dimensional scale measuring consumers' perceived challenge in shopping fashion products online, and to verify its validity and reliability. Relevant literature is first reviewed to identify possible dimensions of perceived challenge. Next, Study 1 is conducted in order to explore the dimensions empirically and to see whether the dimensions that emerged were consistent with prior findings. A total of 190 responses to an open-ended question was qualitatively analyzed by using content analysis. The findings of Study 1 generate 26 items reflecting four dimensions (i.e., product knowledge, previous experience, website functionality, and product availability), which correspond to the dimensions suggested in literature review. Study 2 is subsequently conducted to refine the items so that the perceived challenge scale establishes cross-validation, convergent validity, discriminant validity, reliability, and predictive validity. A total of 238 responses is quantitatively analyzed by using exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. In the results of Study 2, the perceived challenge scale is found to consist of a total of 16 items reflecting three dimensions: E-commerce Challenge (corresponding to Previous Experience reported in Study 1), Retailer Challenge (corresponding to Website Functionality), and Product Challenge (corresponding to Product Knowledge); all Product Availability items have been eliminated through the item refinement process. Specifically, E-commerce Challenge and Retailer Challenge are found to predict flow, supporting flow theory, while Product Challenge fails to lead to flow significantly. Implications, limitations, and suggestions for future studies are also discussed.

• Proceedings of the Korean Institute of Interior Design Conference
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• 1999.04a
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• pp.37-44
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• 1999

A number of the retail and traditional market customer is decrease, whereas that of the supermarket in department-store customers in is increase. This case suggests that customers have a preference for much more comfortable and pleasant shopping places And making a resonable purchase in the supermarkets where we can find various goods and price zone, is now garden variety. It is a current course that once the manager ask an architect for multi-functional space design in department-store and then the architect compose a team and start to design. Of course, the team of planner thinking manage give the design team the basic material data such as commerce analysis and the use of each layer in the department store but, the design team solve the assignment by architectural form, functional space plan and the limited architecture law. After establishing general design for architecture, we can ask shopping-mall distribution, products display and interior design of the interior design general design for architecture, we can ask shopping-mall distribution, products display and interior design of the interior design team. so it is inevitable that the interior design team concerning M·D can find lots of complementary factors with architecture design. The purpose of this study is analyzing the differences of architecture design, which has to accept the limited law and interior design concerning M·D, satisfying the structure and the law in the future design for the department-store. Also the purpose of this thesis is suggestion the items architects and interior designers research into together to make the inner space ideally.

• Journal of Fashion Business
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• v.5 no.2
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• pp.87-104
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• 2001

The purpose of this study is to understand the distributions of fashion market and it's characteristics by investigating the attributes and changes of three representative fashion markets i. e. Chungjang Street Market, Underground Shopping arcades, Department Stores in Kwangju Metropolitan city. This study might contribute to the construction of more attractive fashion markets and also to consumer convenience by providing information about fashion. The method of investigation is by direct market visiting and interview from 2000. 7. 11 until 7. 30. The result is as follows; 1. Chungjang Street: This is the most famous and fashionable area, situated mainly on Chungjang street and Hwangkum-dong. The various kind of designer's boutiques, national brands, wedding shops, multi-shops etc. take place. Teenagers and people in their early twenties are the main customers. This point should be born in mind in a strategy of marketing. 2. Underground Shopping arcades: This market is open to customers of all ages and to the passengers crossing the streets and the purposeful visitors, even in rainy or snow days. However it is hard for novices to find it. 3. Department Stores: There are three department stores which are very competitive with each other by granting not only spacious and comfortable shopping areas but also places for children and cultural activities. The strategy of exhibiting unique items unparalleled in it's quality, might be needed with providing a comfortable parking lot, high quality commodes, appropriate sales program and more effective sales managements.

• The Research Journal of the Costume Culture
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• v.27 no.5
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• pp.496-511
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• 2019

The purpose of this study was to create a theoretical structure for the concept of purchasing risks by identifying the structure of purchasing risks that lead to obstacles in the purchasing decisions of consumers in fashion consumption via online channels. This was a secondary research using books, articles, prior researches, and academic journals on the five topics of "characteristics of fashion consumption," "the concept of purchasing risks," "purchasing risks by product types," "purchasing risks by channel types," and "purchasing risks of fashion consumption on online shopping channels." According to the arguments of prior researches, the study divided the purchasing risks of fashion consumption through online shopping into four categories : (1) fundamental purchasing risks including financial risk and time loss risk pertaining to any product or channel, (2) online channel purchase risks, which include risks in payment, Information leaks, and delivery and return/exchange risk, (3) fashion product risk related to product quality or experience of other people, which includes social risks and risks associated with quality, and (4) the online channel${\times}$fashion product risks, which include the aesthetic and psychological hazards especially amplified in online channels. The four risk factors were then described with a concept map to systemize the multi-dimensional and stereoscopic psychological structure of purchasing risks. Of the four risk factors, consumers placed the most emphasis on the online channel${\times}$fashion product risks, hence, reducing this risk factor is of utmost priority for marketing of online shopping channels.

• 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.

• Fashion & Textile Research Journal
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• v.15 no.1
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• pp.35-45
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• 2013

The purposes of this study were to segment the women's plus-size market by the types of store patronage, profile the segments, and examine the differences in satisfaction with clothing attributes and variety of plus-size apparels according to different segments. The questionnaires included the 7-point likert scales on store patronage, satisfaction, clothing involvement and body cathexis. Five body measurements were recorded by sales people, and the respondents also provided information on their weight, height and garment size in addition to demographic characteristics. Questionnaires were collected from 7 franchise stores in Seoul, Anyang, Daegu, and Cheonan during the months of February, 2011 to April, 2011. 210 questionnaires were distributed and 160 were returned. Excluding incomplete questionnaires, a total of 149 questionnaires were used in the final analysis. The cluster analysis based on store patronage identified four segments- major patrons of specialty stores, multi-channel users, regular store users, and internet shopping mall users. Significant differences were found among the four segments of women's plus-size consumers in terms of clothing involvement, age, occupation, education and clothing expenditures. Internet shopping mall user group were in overall less satisfied with several clothing attributes and variety compared to other groups.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.2
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• pp.138-151
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• 2012

This study determines a consumer retail store choice by applying the Analytic Hierarchy Process (AHP) method for multi-criteria decision-making in the fashion retail industry. The study provides detailed and relevant information for management, marketers of fashion retail stores, and to improve competition between suppliers. Data was collected in February 2011 from questionnaires completed by 319 university students in Busan, South Korea. One of the major findings of this study was that consumer store preference was affected by the following factors in order of importance: product, image, service quality, and purchase facilitation. Brand image was assessed to be the most important of the evaluation elements, followed by individuality, style, and price. The results of rating the relative importance and priority of fashion retailers showed that department stores ranked most highly, followed by outlet malls, Internet shopping malls, brand malls, and discount stores.

• Journal of the Korean Institute of Landscape Architecture
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• v.32 no.3
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• pp.91-105
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• 2004

Recently the function of a department store has changed to the concept of a multi-functional center because of the alternative stores such as discount stores, home shopping, and internet shopping. This means that the front plaza of a department store is not a personal or private space any more, but a public space. This study focuses on the special character of public space through the classification and preference types of department store front plazas. The major results of this study can be summarized as follows: (1) Components of front plaza of department store are classified by three factors. The first factor, named "space limit", has 14 elements ; the second, named "space decoration" has 16 elements ; third, named "activity", has 2 elements. The first preferred element is easily- used and easily- serviced wide space. The second preferred element is the equipment that is placed linearly along the street. The third preferred element is cultural events. (2) The comparison between the frequency and preference shows that the plazas could not satisfy the user-needs. (3) Preference factors of front plazas were examined to three characters such as familiarity, peculiarity, and openness. Familiarity, peculiarity, openness have a positive correlation in all types. Peculiarity especially influences the other two space - preference factors.

• Journal of the Korean Society of Costume
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• v.67 no.1
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• pp.40-55
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• 2017

The current new distribution environment provides the consumers to shop at anytime and any places by using mobile appliances. So, the companies which run the offline-store increase the contact point with the consumer by launching not only online-store but also the mobile application (app). Moreover, they are trying to operate the Omni-channel shopping environment. In order for this research to draw the direction of 'the Omni-Channel Strategy', which is about the changed distribution environment of the domestic fashion enterprise, the following steps were performed. First of all, the term related to 'Omni-Channel' is defined. And then, Example of the 'Omni-Channel' strategy and 'O2O' business in the domestic distributior were researched. Lastly, present condition of the 'Omni-Channel' strategy case of the domestic fashion industry was researched. At the result, the online-stores usually have several brands which can not represent their identities. It is suggested that each online-store according to each brand has their own characteristic identity. And The Omni-Channel strategy of the domestic fashion enterprise that is needed the connection point connecting the on-line and off-line. It is able to allure the customer to the off-line-store.

• Journal of Information Technology Applications and Management
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• v.13 no.2
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• pp.127-143
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• 2006

As the number of Internet users increases, online shopping malls are gradually flourishing and sales are continuously growing. However, since consumers are not able to check what they purchase when buying products on the Internet, they are bound to have higher risk perception than buying directly from off-line stores. Especially, sporting goods require a special attention because a preliminary test is important. Therefore, the risk perception is much higher when people purchase sporting goods online. This study first identifies the multi-dimensionality of risk perception. Then, it investigates whether online purchasing experience of sporting goods makes differences in the level of risk perception. In addition, it examines whether the risk perception by those who had an experience in purchasing sporting goods online affects the customer satisfaction. This study has identified five dimensions in the concept of risk perception, such as financial risk, performance risk, security risk, delivery risk, and psychological/physical risk. A statistical analysis shows that people without an experience in purchasing sporting goods online have perceived significantly higher performance risk, security risk, and psychological/physical risk than those with online purchasing experiences. Finally, this study has found that delivery risk, financial risk, and psychological/physical risk have significant negative influences on the customer satisfaction.