• 한국의류학회지
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• 제47권4호
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• pp.646-665
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• 2023

This study attempted to examine the characteristics of fashion cross-border e-commerce(CBEC) by analyzing about 35.7 million cases of customs clearance data received from the Korea Customs Service. The demographic characteristics of consumers and the features of products purchased from 2019 to 2021 were explored. Next, the association rules between products, brands, and websites were analyzed by men and women in their 20s to 50s. The results are as follows. First, women purchased more clothing products than men, and overall, consumers tended to purchase products at low prices every year. Second, the most commonly purchased products were T-shirts, bags, and other shoes. In the list clearance, the purchase frequency of international open markets increased for three years; in general clearance, the proportion of luxury brands was high every year. Finally, in the list clearance, the relationships between bags, other shoes, pants, and overseas open markets were significant, while the relationships between wallets, bags, and luxury brands were significant in general clearance. Based on this study, domestic companies participating in or competing against the CBEC market can develop appropriate strategies for merchandising and sourcing clothing products.

• Asia pacific journal of information systems
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• 제17권4호
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• 정보처리학회논문지C
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• 제9C권3호
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• pp.351-358
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• 2002

Recently, personal business styles have been rapidly changed into e-business due to the rapid progress and deployment of Internet. As a result of the change, new and safe ways of payment such as electronic wallet, electronic money and electronic check have been developed and introduced. In this paper a secure and user-friendly payment method is addressed. One of most important reasons why newly developed safe payment methods are not widely used in e-business is lack of convenience for the users. On the other hand credit card based payment, which is traditional one, is the most prevailing due to the user-friendliness. However this payment also has some problem in sense of security. In this paper, we design and implement a secure credit card-based payment system using one-time credit information. The main features are "payment information must be new", "can use the old credit system", and "do not require client software".

• 한국패션뷰티학회지
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• 제2권1호
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• pp.75-85
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• 2004

Since, N-Generation equipped with internet seek for more reasonable consumption, they are seeking positive toward the latest vogue and having strong desires for better consumption. In such, the makeup industry produces makeup products specially made for the N-Generation. The products not only directly reflect the skin features of the N-Generation but also form different. Therefore, the purpose of this study tries to find out the distinctive consumption of the N-Generation that rises as the new consumer group of the new millennium in the makeup industry and their purchase behaviors. The investigation was done on 200 females aging from 13 to 23. Investigation method was done face-to-face interview conducted from Dec. 1st to Dec. 8th, 2003 for a week. Through the study, it can be seen that the network generation is interested in e-commerce and such trend show the possibility of makeup market in the e-commerce. Also, it is suggested that the study can be used as useful data when establishing marketing strategies in the relevant industry. The result where the N-generation demands for distinctive products just for them can be used as an alternative plan of market division policy.

• 한국IT서비스학회지
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• 제1권1호
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• pp.17-27
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• 2002

Buyer-carts to support the purchasing process in the B2B EC platform, can be categorized as s-cart, i-cart, and b-cart depending upon its residing sites : seller, intermediary, and buyer sites. In this paper, after proposing the desired features of buyer-carts in B2B EC as identification, collection, trashing, ordering, payment, tracking, recording, purchasing decision support, and transmission of records to e-procurement systems, we try to analyze each buyer-cart qualitatively from such viewpoints. Moreover, we propose an efficiency evaluation model for quantitative analysis. By setting variables from interview of employees in 30 listed companies In Korea, we try to evaluate the efficiency of buyer-carts in B2B EC. From this paper, we show that the b-cart platform is more efficient than other buyer-carts especially in B2B EC.

• 경영정보학연구
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• 제7권1호
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• pp.97-113
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• 2005

본 논문은 B2C 온라인 인터넷 쇼핑을 돕기 위한 비교쇼핑 에이전트를 설계하고 이를 구현하는데 목적을 두고 있다. 오프라인 상점에서 상품을 구매할 때 구매자가 판매원에게 제품의 제조사, 모델, 기능 또는 가격대를 설명하면 판매원이 해당 상품들을 보여주거나 카탈로그를 보여준다. 구매자는 상품의 기능이나 디자인을 비교하면서 적절한 상품군을 정한 후 가격을 비교한 다음에 가장 싼 곳에서 상품을 구입한다. 본 논문이 소개할 비교쇼핑 에이전트 ${\ulcorner}$PriceMeter${\lrcorner}$는 이러한 구매 행동에 최대한 부합 되도록 설계하였다. 구매자가 원하는 제조사, 가격, 기능 등을 선택한 후 검색하면 해당되는 상품들의 설명과 가격 정보들을 이 비교쇼핑 에이전트가 취합하여 보여준다. 마음에 드는 상품들을 카탈로그 양식으로 비교해서 볼 수도 있고, 프린트 양식으로 출력할 수도 있다. 특정 상품을 클릭하면 해당 상품을 판매하는 쇼핑몰들의 정보와 판매 가격을 함께 보여주며, 구매 아이콘을 클릭하면 쇼핑몰의 해당 상품 페이지로 이동할 수 있도록 하고 있다. B2C 전자상거래에 있어 비교쇼핑 에이전트의 구현과 확산은 구매자에게 더 많은 정보와 권한을 제공함으로써 소비자 중심의 유통경제를 한 걸음 앞당길 수 있다. 특정 상품에 대한 가격과 상세 정보를 일목요연하게 제공받는 구매자들은 보다 현명한 구매를 할 수 있으며, 거래과정에서 판매자(생산자)와 구매자의 협상력이 구매자에게로 옮겨질 수 있다. 본 논문이 제시한 비교쇼핑에이전트는 소비자 중심의 사이버 유통시대를 촉진하는데 일익을 담당하는데 그 의의가 있다.

• Asia pacific journal of information systems
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• 제14권1호
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• pp.59-77
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• 2004

Even though B2B EC is becoming popular, there have been not so much studies about performance evaluation methodology for B2B systems. In this paper, after analyzing buyer-carts systematically focusing on the buyer's interactional efforts on the typical buying processes of each buyer-cart, we propose a quantitative performance evaluation model. For this, we categorize buyer-carts in B2B EC as s-cart, i-cart, and b-cart depending upon its residing sites: seller, intermediary, and buyer sites. And after proposing the desired features of buyer-carts in B2B EC as identification, collection, trashing, ordering, payment, tracking, recording, purchasing decision support, and transmission of records to e-procurement systems, we derive a performance evaluation model by calculating detail sub-processes from the desired features' viewpoints. By setting variables from a survey on the actual condition of using buyer-carts in companies in Korea, we try to evaluate the performance of buyer-carts in B2B EC. In this paper, we suggest a new methodology of performance evaluation for B2B systems, and show that the b-cart platform is more efficient than other buyer-carts especially in B2B EC.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2004년도 추계학술발표논문집(상)
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• pp.543-546
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• 2004

Web Services are rapidity becoming the enabling technology of today's e-business and e-commerce systems, and will soon transform the Web into distributed applications. The aim of this paper is to present our approach in applying Web Services into the Internet transaction banking system. The system is integrated among backend system of banks so that each bank system can communicate with each other in order to perform transactions in transferring money from an account in one bank to an account in the partner bank and vise versa. The backend systems of banks are heterogeneous information systems; therefore it is difficult to build a common environment using existing distributed technologies. Web Services provide a means for different organizations to connect their applications with one another to conduct business across a network in a platform and language independent manner [1]. The paper will examine these benefits of Web Services and apply these features into the Internet banking transaction system regardless of platform, programming languages as well as existing backend system of banks.

• 무역상무연구
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• 제41권
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• pp.51-78
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• 2009

The ISP 98 is developed by the American Institute of International Banking Law & Practice in 1998. The ISP98 are also published as ICC Publication No. 590. A detailed commentary on the rules("The Official Commentary on the International Standby Practice") has been written by Professor James E. Byrnes. Presently there is no compelling reason to revise the rules themselves even if ten years is passed since the issuance of ISP98. Insteadthe American Institute of International Banking Law & Practice will provide Model Forms in the early 2009. Special features of the ISP 98 are as the following. Firstly, the ISP 98 is copyrighted by the Institute of International Banking Law and Practice, Inc., and published by the International Chamber of Commerce. Secondly, the ISP 98 differs from UCP in style and approach because it must receive acceptance not only from bankers and merchants, but also from a broader range of those actively involved in standby law and practice corporate treasurees and credit manager, rating agencies, government agencies and regulators, and indenture trustees as well as their counsel. Because standbys are often intended to be available in the event of disputes or applicant insovency, their texts are subject to a degree of scrutiny not encountered in the commercial letter of credit context. Thirdly, the ISP 98 supplement the UCP if the UCP dose not have the relative rule. Lastly, the ISP 98 has the official commentary. In addition, several provision of the ISP 98 would surprise the commercial parties and/or are rather peculiar, while some of them display a certain bias in favor of the banks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.