• Asia pacific journal of information systems
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• v.21 no.4
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• pp.1-25
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• 2011

Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

• The Journal of Information Systems
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• v.21 no.3
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• pp.137-161
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• 2012

The increasing interest in big data analysis using various data mining techniques indicates that many commercial data mining tools now need to be equipped with fundamental text analysis modules. The most essential prerequisite for accurate analysis of text documents is an understanding of the exact semantics of each term in a document. The main difficulties in understanding the exact semantics of terms are mainly attributable to homonym and synonym problems, which is a traditional problem in the natural language processing field. Some major text mining tools provide a thesaurus to solve these problems, but a thesaurus cannot be used to resolve complex synonym problems. Furthermore, the use of a thesaurus is irrelevant to the issue of homonym problems and hence cannot solve them. In this paper, we propose a semantic text mining methodology that uses ontologies to improve the quality of text mining results by resolving the semantic ambiguity caused by homonym and synonym problems. We evaluate the practical applicability of the proposed methodology by performing a classification analysis to predict customer churn using real transactional data and Q&A articles from the "S" online shopping mall in Korea. The experiments revealed that the prediction model produced by our proposed semantic text mining method outperformed the model produced by traditional text mining in terms of prediction accuracy such as the response, captured response, and lift.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.5
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• pp.695-702
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• 2015

This study provides basic data that are helpful to prepare a sizing system for dress shirts that improves the wearer's size fitness. The 16 different parts of the dress shirts were measured for 24 pieces of dress shirts with three kinds of size (95, 100 and 105) among the eight different brands on the market. The measurement sizes of the dress shirts analyzed the accuracy of the size information, size classification by size designation, and differences of size by brand. The results of the study were: 1. The size information of dress shirts differed from customer demand. 2. The size increments between size designations differed from each other even though measurement sizes of the dress shirts increased as the size designation increase. 3. Measurement sizes of the dress shirts were different between brands even for dress shirts of the same size designation. It is necessary that manufacturers secure an accurate and standardized sizing system and provide accurate information for the measurement sizes of dress shirts on an online shopping mall.

• Proceedings of the Korea Information Assurance Society Conference
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• 2004.05a
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• pp.309-316
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• 2004

The industrial structure with Internet is changing from offline to online. By developing of network, E-commerce will be big market. It is natural to increase of E-commerce and interest of people. but, it is supported by system and technics. First of all, we need customer authentication service method. In this paper, we described about Electronic shopping mall Security by three main categories. One is general security solution of I-commerce, Second is analyzing about various threats, vulnerability and countermeasures to that. Third is security consideration of directory service in I-commerce circumstance.

• Fashion & Textile Research Journal
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• v.11 no.2
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• pp.308-314
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• 2009

In creating an avatar, consumers can find out for themselves their own sizes to be entered. Also, putting in a face creation main-page menu option enables clients to make up their faces and match them to their bodies. Through this process when purchasing clothes through the internet consumers can enter their own body sizes and create avatars that are identical to their body shape. The uniqueness of developed prototype is that it creates an avatar similar to one's body shape according to body size inputs and demonstrates visually to customers the on-line comfort test which was only available off-line traditionally. The avatar follows the movement of mouse from left to right which enables 3 dimensional visualization. Through maximizing the visual effect this research focuses on enabling consumers to feel subjective parts as if they are off-line. This study seeks to provide a type of prototype of an online shopping mall that meets the demand of the consumers using the 3D avatar.

• Fashion & Textile Research Journal
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• v.10 no.2
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• pp.147-154
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• 2008

This study was carried out to examine the actual using condition of Yogawear and consumer's preference of Yogawear with traditional pattern. Yogawear can be developed as a cultural fashion item, because Yoga is getting universal interest with "Wellbeing Trend". A survey with 34 questionnaires was made by 305 consumers who had ever experienced Yoga from July to August, 2006. The results are as follows: 1. Most of objects were female(94%). Those who are in their twenties accounted for 50%, and those who take Yoga practice time less than 1 year accounted 63%, and those who take Yoga practice time less than 1 hour in a week accounted 46%. 2. Respondents who have Yogawear accounted 32% and they bought it in a online-shopping mall(48%), department store(16%) and discount store(11%). 3. Only 31% of respondents were satisfied of their Yogawear but they weren't satisfied about Yogawear Design, fabric and color. 4. Most preferred Yogawear style was pastel colored 'shirt & Pants' style with long sleeve using cotton fabric. 5. They liked much more modern Yogawear having korean image than completely korean style Yogawear or modern style Yogawear. 6.The benefits of Yogawear were 3 dimension: appearance, easy management, physical properties.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1061-1069
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• 2011

With the development of information technology, online commercial transactions have been steadily increasing. However it is not easy to recommend the clothes in coordination with individual physical features. This paper presents a fashion coordination recommender system for women's clothes. The system includes the functionality of recommending clothes best-suited for customers in consideration of their individual physical features. It has also been designed to recommend clothes in vogue for those who are fashion-sensitive by considering the fashion trend of the times. Operated in an optional or coupling way, these functionalities of our system result in an intelligent fashion coordination system which recommends dress items to customers in various ways.

• Fashion, Industry and Education
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• v.16 no.1
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• pp.36-45
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• 2018

Recently China has become one of the major markets for luxury brands. In addition, practicing social responsibility by manufacturers of luxury brands has become ubiquitous because consumers' perception of such practices may affect their purchase decisions positively. This study explored Chinese shoppers' perception of luxury brands' social responsibility practices and their information seeking behavior. In this study, value congruence was used as a theoretical framework. Twelve participants were selected out of customers in a shopping mall in Beijing, and they were subject to in-depth interview. The interview consisted of open-ended questions about perception of luxury brands' social responsibility practices, sources to access such practices, and the degree of personal value congruence to such practices as well as demographic information. Qualitative approach was used to analyze the data. Half of the participants indicated their awareness of the social responsibility practices of luxury brands, which sets up a foundation for understanding importance of luxury brands' social responsibility practices. Approximately half of the participants preferred to learn about luxury brands' socially responsible practices online especially via social media. These findings imply that Chinese luxury shoppers' trust and preference for the companies would be enhanced by effective development and advertisement of companies' social responsibility practices, and thus provide luxury companies with useful information on marketing strategies.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.178-184
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• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• Journal of Fashion Business
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• v.18 no.3
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• pp.1-13
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• 2014

This study investigated the store switching behavior of fashion stores targeting college students. A random sample of college students completed a questionnaire that contained measurements of store property, relationship quality, switching intent of store, preference of on/offline store, purchase of brand/non-brand product and monthly clothing expenses. The factors extracted as switching behavior of on/offline fashion store are store property, relationship quality and switching intent of store. Dimensions of store switching behavior in online shopping mall is revealed to be composed of diversity/ easy to search, store reliability, home page layout, sales promotion, reliability, commitment and switching intent of store. Also those of offline store is revealed to be composed of store comfort/salespeople service, product diversity, store location, product price, reliability, commitment and switching intent of store. The significant differences were found between store switching behavior of college students by preference of on/offline store and purchase of national brand/non brand. It is expected that this results can be used as a basic material for further study and setting up the fashion retailing strategies in fashion store for selling non brand products.