• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.169-174
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• 2002

According to the expansion of the E-Commerce based on Internet, the Interoperability between shopping malls and the expansibility of B2B has been needed. Also, Intelligent User Interface has been needed. The XML based Script Processor, the solution of the problem, is good for Interoperability and if a shopping mall is build by it, it is possible to do customer oriented display that an XML document is displayed with different looks by other style sheet according to customer's preference. In the proposed system, the TMP(Template Markup Language), an auto XML generation script, is defined by XML and the script processor is implemented to work on the shopping mall on the Web.

• Proceedings of the CALSEC Conference
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• 1999.11a
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• pp.108-116
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• 1999

최근 사이버 쇼핑몰에서 기업과 고객간의 제품 구매 활동을 도와주는 검색 에이전트 시스템에 대한 연구가 활성화되고 있다. 그러나 많은 비교 검색 에이전트 시스템들은 고객이 입력한 키워드 기반의 검색 목록만을 체공하고 있으며, 검색된 유사상품 목록 중에서 어떤 상품이 적합한지 선정해 주는 의사결정지원 기능은 충분히 제공하지 못하고 있다 본 논문에서는 인터넷 쇼핑몰 환경을 기반으로 키워드 입력에 의한 제품 검색뿐만 아니라 고객 선호도가 높은 제품 선정을 지원해 주는 의사결정지원 시스템을 제안한다. 제안한 의사결정지원 시스템은 고객이 입력한 각 속성들의 표준계수와 가중치를 점수화 하여 선호도가 높은 상품을 우선적으로 제시함으로써 고객의 상품 선정을 위한 의사결정을 지원하도록 하였으며, 또한 각 속성별 다양한 반영 비율에 따라 어느 제품이 전체적으로 적합한지를 분석하는 민감도 분석 기능을 추가하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.29-39
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• 2006

Every online shopping mall is concerned about service quality and trust issues. We analyze and compare the impacts of service quality and trust on customer satisfaction and loyalty. In addition, we investigate service quality and trust attributes and their effects on overall service quality and trust. The results unveil that, in our e-business setting, overall trust has more powerful leverage than overall service quality.

• Journal of Global Scholars of Marketing Science
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• v.17 no.1
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• pp.23-49
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• 2007

The purpose of this study is to investigate the relationships among customer satisfaction, trust, and loyalty and examine the differences and similarities between specialized and general merchandise internet shopping malls concerning the relationships of these key success factors. The structural model is tested with each of the sub-samples(i.e., specialized and general merchandise shopping customers taken separately) and the data from entire data samples(i.e., specialized and general merchandise shopping customers pooled together). The same research model was used in analysing general merchandise, specialized, and integrated internet shopping mall to reveal and compare the casual path constructs. In the analysis of path coefficients composed of separated taken sample, all research hypothesis is accepted and the model's goodness of fit also shows all high. In the basis of the previous empirical test, multiple sample method was used. Properties of the causal paths, including standardized path coefficients, the significance of difference, latent correlations and variance explained for satisfaction, trust and loyalty in the hypothesized model, have similarities in general. This means that the proper structural management concerned with customer satisfaction, trust and loyalty is very crucial for the success of all kinds of internet shopping malls. Following the model test, I conduct a test of integrated model's path coefficients. Statistical results show that all the hypothesis concerned with internet shopping malls were accepted like the separated sample test. Click and mortar companies should clearly understand and articulate the key requirements of shopping mall satisfaction, trust and loyalty and encourage to establish linkage and interactive relationship among the research variables. In addition, internet marketers are required to customize the interaction considering and adapting the patterns of internet shopping malls. Other interesting results concerning the strategies in internet shopping malls strategy are also presented.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.3 s.162
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• pp.486-494
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• 2007

Consumers' great demand for foreign apparel products created a new rapidly growing type of distribution channel that substitute traditional roles of importers. Most of the merchandise selling at this new type of e-mall are apparel and accessories. But, little study focuses on this new e-shopping mall. This study was designed to examine SISM(surrogate internet shopping mall) shopping behavior of apparel by analyzing purchase motives and consumer satisfaction and compare these variables with GISM(general internet shopping mall) shopping behavior. 166 SISM consumers and 166 GISM consumers responded for the study. Descriptive statistics, t-tests, and regression were used far statistical analysis. Results indicated that there were significant mean differences of purchase motive and consumer satisfaction between SISM and GISM consumers. Regression analysis showed that purchase motives had significant influence on consumer satisfaction for SISM and GISM consumers.

• CRM연구
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• v.4 no.2
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• pp.19-29
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• 2011

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.06a
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• pp.29-31
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• 2002

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.472-484
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• 2004

인터넷 쇼핑이 성장하면서 비교쇼핑몰의 중요성도 그만큼 증가하고 있다. 그러나 현재의 비교쇼핑몰들은 웹으로부터 제품가격정보와 같은 단순한 XML 데이터만을 수집하여 비교할 뿐, 배송비와 같이 규칙을 기반으로 한 정확한 비교는 제공하지 못하고 있다. 각 쇼핑몰은 저마다 배송비에 관한 정책을 다양하게 제시하고 있으나 비교쇼핑몰에서는 이를 반영할 구조를 가지고 있지 못하기 때문이다. 따라서, 본 연구에서는 규칙 기반의 추론을 이용해 상품가격에 배송비를 포함하여 비교를 수행할 수 있는 비교쇼핑몰을 구현하고자 한다. 이를 위해 eXtensible Rule Markup Language (XRML)를 이용하여 각 쇼핑몰의 웹페이지의 문장과 표로부터 규칙을 습득하는 방안을 제시하였다. 이 구조를 이용하면 웹페이지에서 완전에 가까운 규칙을 자동생성할 수 있을 뿐만 아니라, 각 사이트에서 변화가 발생하면 이를 반영하여 규칙을 일관성있게 수정하도록 지원할 수 있다. 본 연구에서는 인터넷 상의 대표적 서점인 Amazon.com, BarnesandNoble.com, Powells.com에 대해 XRML을 기반으로 설계한 비교쇼핑몰의 프로토타입 ConsiderD를 개발하였다. 이 과정에서 웹으로 부터 규칙을 자동생성 할 수 있는 잠재력을 검정하고, 배송비 효과의 중요성을 실험을 통해 예시하였다.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.113-127
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• 2021

This study classifies review attributes into ratings, number of comments and image information in online shopping mall to verify their impact on brand attitude and purchase decision and e-WOM intention. Use SPSS 23.0 for frequency analysis, factor analysis and regression analysis. The results showed that review attributes have a positive effect on brand attitudes, purchase decision and e-WOM intention, but the number of comments has not affect on purchase decision. Brand attitude has a positive effect on purchase decision and e-WOM intention. Brand attitude has media effect in the relationship between ratings, image information and purchase decision, and in the relationship between review attributes and e-WOM intention. As these results, consumers don't always like to have a lot of comments. and should allow to focus on high ratings and photo reviews as much as possible when writing reviews.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.21-49
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• 2008

The area of the internet shopping mall heavily relies on new emerging information technologies, and it essentially requires delicate marketing model to support consumer behavior. RSS, which is one of the representative Web 2.0 technologies, is the system that distributes digital contents without any Web browser. RSS is expected not only to be very useful in online marketing but also to become actively applied on various areas such as online newspapers and blogs. AISAS model was proposed to complement the AIDMA model that did not cover the new changing customer behaviors of online commerce environment such as search and share. In this research, we propose a marketing model which utilizes RSS based on the AISAS model to support internet shopping malls. With our marketing model, internet shopping malls are expected to provide required services to the customers at every AISAS step. Moreover, it can provide integrated services by connecting all service components of each step. We utilized RSS in our model to implement those services because RSS has many advantages on supporting search and share of product information.