• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.83-91
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• 2006

Internet shopping mall has become a huge distribution channel with dramatic growth in recent years. The number of consumers has exponentially increased as the scale of shopping mall has been large so that shopping malls with thousands or millions of consumers become a general case. However, it is essential to evaluate whether current assortment of consumers is proper or not in the strategic aspect in order to operate Internet shopping mall effectively and gain profits. That is, it is important to evaluate whether consumer strategy of corporation is proper or not from the corporation. Despite this business importance, consumer assortment has not been evaluated well and related study is not sufficient. This study supposes a framework for consumer assortment evaluation, which evaluates whether consumer assortment of Internet shopping mall is proper or not. In the framework for consumer assortment evaluation, analysis data based on order data and consumer data in database is made. Then, four factors, consumer maintenance rate, consumer profitability, consumer securing rate and consumer conversion are setup, and 22 measurement indexes are drawn. Finally, a consumer assortment evaluation score card is made by integrating them. This study has applied a supposed framework to a domestic typical community based shopping mall, and it is expected that the evaluation result will be used as informant strategic information to operate the shopping mall effectively.

• Journal of Information Technology Applications and Management
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• v.10 no.4
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• pp.51-63
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• 2003

This study designs and implements a new approach to the classification of e-mail requests from customer based on machine learning techniques. The work on building an electronic mall classifier can be cast into the framework of text classification, since an e-mail is a viewed as a document, and judgement of interest is viewed as a class level given to the e-mail document. It is also implemented an e-mall based automated response system that integrate with Call Center in a practical use.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.153-177
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• 2001

Nowadays, product recommendation is one of the important issues regarding both CRM and Internet shopping mall. Generally, a recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly and thereby automatic recommendation methodologies have got great attentions. But the researches and commercial tools for product recommendation so far, still have many aspects that merit further considerations. To supplement those aspects, we devise a recommendation methodology by which we can get further recommendation effectiveness when applied to Internet shopping mall. The suggested methodology is based on web log information, product taxonomy, association rule mining, and decision tree learning. To implement this we also design and intelligent Internet shopping mall support system based on agent technology and develop it as a prototype system. We applied this methodology and the prototype system to a leading Korean Internet shopping mall and provide some experimental results. Through the experiment, we found that the suggested methodology can perform recommendation tasks both effectively and efficiently in real world problems. Its systematic validity issues are also discussed.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.213-222
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• 2017

This paper proposes a new service design which is deep learning-based image retrieval system for product search on O2O shopping mall platform. We have implemented deep learning technology that provides more convenient retrieval service for diverse images of many products that are sold in the internet shopping malls. In order to implement this retrieval system, real data used by shopping mall companies were used as experimental data. However, result from several experiments have confirmed deterioration of retrieval performance due to data components. In order to improve the performance, the learning data that interferes with the retrieval is revised several times, and then the values of experimental result are quantified with the verification data. Using the numerical values of these experiments, we have applied them to the new service design in this system.

• Journal of the Korea Safety Management & Science
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• v.17 no.1
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• pp.203-213
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• 2015

Recently, online grocery shopping has been increasing with the development of internet, mobile, and IT technology due to the proportion of consumers changes like increasing single households and double-income couples. Therefore, online sales from distributors with offline stores have also increased, and the offline retailers are facing their limits in dealing with store-based online channel they have carried out. Domestic offline retailers benchmarked overseas advanced retailers to solve this problem by reviewing about developing the online-only distribution center. However, much investment is needed in order to operate the distribution center with the new concept from abroad. In this study, we have reviewed the current online grocery market trend and the theory related to developing distribution system of the online mall. For offline retailers, we have reviewed the case which developed the distribution center applied to the nation's first online-only distribution center. The purpose of this study is reducing trial and error for local retailers in developing online-only distribution centers and suggesting ways to improve investment effect.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.700-702
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• 2001

As computers and networks become popular, distributing information on the Interment is common in our daily life. Also, the explosion of the Internet, of wireless digital communication and data exchange on Internet has rapidly changed the way we connect with other people. But secure mall is gamins popularity abroad and domestically because of their nature of prodding security. That is. it has been used a variety of fields such as general mail and e-mail for advertisement But, As the data transmitted on network can be easily opened or forged with simple operations. Most of existing e-mall system don't have any security on the transmitted information. Thus, security mail system need to provide security including message encryption, content integrity, message origin authentication, and non-repudiation. In this paper, we design implement secure mall system with non-repudiation service and encryption capability to provide services for certification of delivery and certification of content as well as the basic security services.

• Proceedings of the Korean DIstribution Association Conference
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• 2006.02a
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• pp.187-227
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• 2006

To attain competitiveness in the severe competition of retailing, retailing firm like Aekyung department store composites multiplex entertainment shopping mall with other firms as key tenants like LG supermarket, Books Libro, and CGV. But in multiplex entertainment shopping mall customers who have experienced a service failure in key tenant's shops usually ask a compensation of service failure to the lessor like department store. Even though customers of multiplex entertainment shopping mall know that key tenants use different service strategy, personnel management system and operation system and so on, they do not rare of it. Why they do that? How can we explain this situation? This study explains customer's complaining behaviors in multiplex entertainment shopping mall using attribution theory and justice theory. The study presents a comprehensive model about the effects of the perceived attribution and fairness on customer satisfaction and suggests practical implications for retailing firms composing multiplex entertainment shopping mall.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.7
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• pp.1184-1196
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• 2010

Several applications of body scanning technology have been commercialized or are currently under development. The virtual fit from 3D scans is most advanced form of virtual try-on. This article is an analysis of the comparison of user preferences for domestic versus foreign 3D virtual try-on systems. For this study, domestic i-Fashion Mall (www.ifashionmall.co.kr) and a Canadian company, My Virtual Model (www.mvm.com) were selected as the most representative online retailers that offer a virtual try-on system. The respondents were comprised of 70 Korean female college students in the age group 20-29. A five point Likert scale was used to evaluate the degree of the preference of virtual avatar and try-on images. T-test, cross table, and a chi-square independence test were conducted for data analysis. The results are as follow. 1. The representation about current looks according to each virtual fit image indicates that MVM is more accurate than i-Fashion Mall. 2. About decision confidence, respondents have decision confidence in i-Fashion Mall in the case of the avatar image; however, respondents have confidence in MVM or the fit image. 3. There were no significant differences in among waist size groups in accuracy, trust of each avatar image, while there were significant differences among waist size groups in the accuracy and trust of each virtual fit image. 4. About ease of use, respondents answered that i-Fashion Mall is superior to MVM. 5. The respondents prioritized the ‘fitting report’ of i-Fashion Mall and ‘Weight loss’ of MVM over other functionalities.

• Journal of the Korea Fashion and Costume Design Association
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• v.8 no.3
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• pp.87-100
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• 2006

The objectives of this research were to investigate the relationship between purchase behavior and consumer dissatisfaction of cosmetics at internet shopping malls, and to examine how the purchase behavior and consumer values influence the consumer dissatisfaction. Subjects were 212 females in Seoul who had experiences of cosmetic shopping at internet shopping malls. Consumers showed highest dissatisfaction when the purchased cosmetics were different from the products showed at internet shopping malls. The dissatisfaction with consuming system was higher than buying system or transporting system. The higher the expense and frequency of cosmetic purchase, the lower the consumer dissatisfaction of buying system. Females of 18 to 24 years old purchased color cosmetics more than females of 25 to 39 years old did. Females of 25 to 39 years old purchased functional skincare products more than females of 18 to 24 years old did. The cosmetic purchase expense of older groups was higher than that of younger one. The more consumers spent time on the internet, the more frequent they bought the cosmetics at internet showing mall. Consumers were most willing to buy basic skincare products at the internet shopping mall (42.9%). The consumer dissatisfaction with cosmetics at internet shopping malls was influenced the most by the happiness value(-) and the next by the responsible value, the frequency of cosmetic purchase at internet shopping malls(-) in order.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.227-234
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• 2017

In this paper, we propose a system whereby one can automatically classifies categories based on image data of the products for a shopping mall platform. Many products sold within internet shopping malls are classified their category defined by the same use of product names and products. However, it is difficult to search by category classification when the classification of the product is uncertain and the product classified by the shopping mall seller judgment is different from the purchasing user judgment. We proposes classification and retrieval method by Deep Learning technique solely using product image. The system can categorize products by using their images and its speed and accuracy are quantified using test data. The performance is evaluated with the test data. In addition, its usability is tested with the participants.