• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.777-787
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• 2020

With the development of the Internet and the spread of mobile devices, the online market is growing rapidly. As the number of customers using online shopping malls explodes, research is being conducted on the analysis of usage behavior from customer data, personalized product recommendations, and service development. Thus, this paper seeks to analyze the overall process of online shopping malls through process mining, and to identify the factors that influence users' purchases. The data used are from a large online shopping mall, and R was the analysis tool. The results show that customer activity was most prominent in categories with event elements, such as unconventional discounts and monthly giveaway events. On the other hand, searches, logins, and campaign activity were found to be less relevant than their importance. Those are very important, because they can provide clues to a customer's information and needs. Therefore, it is necessary to refine the recommendations from related search words, and to manage activity, such as coupons provided when customers log in. In addition to the previous discussion, this paper proposes various business strategies to enhance the competitiveness of online shopping malls and to increase profits.

• Korean Journal of Human Ecology
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• v.21 no.6
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• pp.1185-1198
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• 2012

The purposes of this study were to investigate the relationships between e-loyalty formation process and satisfaction for apparel products by testing the research model developing upon prior researches, and to analyze the differences of the structural model between two groups (high satisfaction group and low satisfaction group). A total of 356 respondents participated through a convenience sampling at universities in Busan. Data were analyzed by a structural equation model analysis. The results were as followings: First, for the structural model, the attributes of shopping malls (e.g., e-store attributes and product attributes) affected consumer satisfaction which influenced the e-loyalty of shopping malls, mediated by value perception. Second, high-satisfaction group evaluated more importantly the attributes of shopping malls, higher perceived the value of products and web sites, more satisfied the mall, and had greater loyalty of online shopping malls than low-satisfaction group. Third, there were significant differences between high-satisfaction group and low-satisfaction group in the e-loyalty model for apparels. Specifically, for high-satisfaction group, the e-store attributes were more likely to influence the value perception of products and web sites than low-satisfaction group, while low-satisfaction group was the higher perceived the value of products, the more they satisfied and then the greater e-loyalty respectively. According to the findings, the implications and future suggestions related to e-loyalty of shopping malls for apparels are provided.

• Journal of the Korea Fashion and Costume Design Association
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• v.20 no.4
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• pp.57-71
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• 2018

Since consumers have become more comfortable with providing and receiving information online, 'online word of mouth' has been gaining consideration as one of the major information sources. Also, the shopping orientation of consumers has been proven to be an important determinant of consumer behavior. Therefore, the study investigated the differences in online WOM behavior based on shopping orientation. Hedonic, loyal, and syntonic styles were the types of shopping orientation considered, and the study focused on information retrieval tendencies, the motivation of online WOM search, searching online WOM sources, and the contents for the online WOM behavior. The research conducted an off-line survey targeting females in their twenties. The total number of data sets used in the empirical study was 125, and these were analyzed by SPSS 20.0: factors analysis, Cronbach's ${\alpha}$, k-means cluster, ANOVA, Duncan's multiple range test, Kruskal-Wallis, Mann-Whitney, and Bonferroni correction. The participants were divided into 3 kinds of shopping orientation groups named 'trend-pursuit', 'passive', and 'loyal'. As a result, there were significant differences in online WOM behavior discovered between the groups. Firstly, the 'trend-pursuit' group had the highest number of ongoing searches while the 'loyal' group had the highest number of pre-purchase search. Secondly, the 'trend-pursuit' and 'loyal' groups both had the motivations of online WOM search, hedonic and utility, whereas the 'passive' group had the lowest motivations for both motivations. Thirdly, the 'loyal' group frequently referred to reviews on shopping malls as online WOM sources. The research provided a better understanding of the online WOM behavior of present consumers and suggests that fashion related corporations map out marketing strategies with the understanding of these behaviors.

• Journal of Distribution Science
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• v.22 no.5
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• pp.93-104
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• 2024

Purpose: This study used the SORmodel (or cue utilization theory) to examine the impact of expanded quality factorsincluding product quality on customer satisfaction, attitude, and behavioral loyalty. This study examined the moderating effect of gender on the customer satisfaction-attitudinal and behavioral loyalty relationship. Research design, data, and methodology: 364 respondents were collected through an online survey and analyzed using the SmartPLS 4.0 program. Results: The findings show that product quality, along with system quality and service quality, are key determinants of customer satisfaction. In addition, this study shows that the relationship between customer satisfaction and attitudinal loyalty (repurchase and word-of-mouth intention) does not differ depending on gender, but the relationship between customer satisfaction and behavioral loyalty (share-of-visit and share-of-wallet) is stronger for women than for men. Conclusions: This research integrates concepts from environmental psychology and marketing focusing on website quality (information, system, service, and product), as well as satisfaction, attitudinal and behavioral loyalty. Online shopping mall practitioners must systematically analyze and assess the quality of online shopping, a pivotal factor driving customer satisfaction, attitude, and behavioral loyalty. Acknowledging the influence of gender on consumers' online purchasing behavior can aid online retailers in devising tailored e-commerce marketing strategies aimed at attracting and retaining customers.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.1
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• pp.14-26
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• 2010

This study investigates the effectiveness of fashion coordination presentation formats when people buy apparel products online. This study conducted an online survey with 595 females who shopped online at the simulated website by a single apparel plan picture (n=189), coordination plane picture (n=187), and 3-D coordination image (n=216). For data analysis, factor analysis, Cronbach's alpha, MANCOVA, ANOVA, Duncan test, correlation analysis, and chi-square are used. The results of this study are: First, the hedonic shopping value was significantly the highest when respondents shopped at a 3-D coordination image shopping mall, the next highest-scored presentation type was the coordination plane picture, and the case of presenting only the single apparel picture was significantly the lowest. The utilitarian shopping value and information shopping value were higher in the coordination plane picture and the 3-D coordination image shopping mall than the single apparel picture. Second, transactions satisfaction was high when respondents shopped at a 3-D coordination image, coordination plane image, and single apparel image in decreasing order.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.56-64
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• 2022

Many studies have suggested that e-commerce value creation potential depends on four interdependent factors Lock-In, Complementarity, Efficiency, and Novelty. In order to survive in the recent fierce competition, companies have also secured e-Trust that strengthens long-term business relationships by reducing consumer uncertainty. This study, while analyzing the value creation factors (Lock-in, Complementarity, Efficiency, Novelty, e-Trust) of recent e-commerce (online shopping mall) companies from the point of view of purchase intention, customer value (Functional value, Emotional value, Social value) We present an academic proposition that can also examine the mediating effect of value). First, through previous studies on value-based strategy and value creation in e-commerce, various discussions on the theoretical background necessary for effective value-based strategy establishment and strategy execution of e-commerce (online shopping mall) companies were reviewed. Second, it provides academic discussion and practical implications by presenting academic propositions on the value creation factors of e-commerce (online shopping mall) companies, purchase intentions, and customer value, and confirming the basis through empirical analysis.

• The Journal of Information Systems
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• v.14 no.2
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• pp.55-74
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• 2005

In order to purchase a product cheaper, a lot of customers have been trying to search one or more marketplaces. Ever since the commercial use of the Internet, several types of marketplaces have been operating successfully on the Internet. Some of them are online shopping malls, auction markets, and group-buying markets. They have the price settlement mechanisms of their own. Online shopping malls where many stores are located support a customer to purchase the product that matches his/her requests such as price, function, design, and so forth. In online auction market, a customer can buy the product by making bids sequentially and competitively until a final price is reached. In online group-buying market, a customer can purchase the product by aggregating the orders from several buyers so that cheaper prices can be negotiated. The cheaper customers could purchase the same product item, the more satisfied they would be. However, it is very difficult for the customer to determine the marketplace to purchase, considering different kinds of marketplaces at the same time. Even though the purchasing price is cheapest in one marketplace, it is very difficult for customers to convince it the cheapest for all marketplaces. Therefore, rules and methods have been developed for purchase decision making in multiple marketplaces to reach the optimal purchase decision as a whole. They can maximize customer's utility and resolve the conflicts with other marketplaces through multi-agent negotiation.

• The Journal of Information Systems
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• v.15 no.4
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• pp.55-72
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• 2006

The total market capacities of our domestic on-line shopping malls had reached over one billion wons in 2005. They are also estimated to reach 1.8 billion wons in 2008. In order to reveal some relationships between six antecedent variables and intention-to-use of online shooing malls, this study has extended the original TAM2 model using these variables obtained from (1) perceived usefulness and perceived ease of use from TAM2 model, (2) compatibility from IDT theory, (3) perceived enjoyment from Flow theory, and (4) others (perceived risk and self efficacy). Two statistical packages such as SPSS 12.0 and Lirel 8.70 were used for data analyses. Among these seven proposed hypotheses, six hypotheses were accepted while one hypothesis regarding perceived risk was rejected. As perceived risk hypothesis concerning the intention-to-use was rejected, the perceived risk did not show the support of the intention-to-use.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.6
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• pp.621-634
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• 2011

This study analyzed the influencing factors on consumer purchase deferrals for internet clothing shopping. In addition, based on consumer demographics, it compared the differences of purchase deferrals with respect to clothing items, prices, and types of shopping malls. For an empirical study, 405 questionnaires were answered by respondents in their 20s and 30s with internet clothing purchase deferral experience. Data were analyzed using: SPSS for Windows 12.0 and descriptive statistics, reliability analysis, factor analysis, $X^2$-test, and regression analysis. The results of this study were as follows. First, the order of items with many purchase deferrals in internet clothing shopping were casual T-shirt>casual skirts>pants, one-piece>suits>sportswear>blouse/shirts and 58.3% of purchase deferrals happened when the price was below \50,000. Second, the significant differences in products, prices, and shopping malls for purchase deferrals were identified according to consumer demographics. There were significant differences in clothing items according to gender, age, marriage, and education; however, there were significant differences only according to gender in terms of price. There were significant differences according to gender, age, marriage, education, and income in terms of the used shopping malls. Third, for the analysis of the influence of diverse factors that can affect purchase deferrals for internet clothing shopping, the more information search, purchase deferral habits, perceived risks, and deficiency in shopping mall supply conditions were when higher purchase deferrals occurred. For a strong competitive online market, this study can help internet clothing shopping mall entrepreneurs manage products and customers by analyzing the lists of purchase deferrals indicated in "cart" and by administrating the influential factors for purchase deferral.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.295-303
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• 2008

With universality of e-commerce through internet, smaller online shopping malls are increased. A Smaller online shopping mall by nature lacks an extra space to load many inventory quantities. Therefore, it is difficult to response immediately with client request with traditional inventory management method. VMI has a character that supplier can control volume of inventory according to sales of seller. This paper proposes SOHO-VMI that is applied VMI into smaller online shopping mall. Proposed SOHO-VMI supports M $\times$ N structure can interact with multiple suppliers and sellers. And it uses XML/EDI for interaction with EDI documents use to legacy system. Also, This paper proposes logistics statistic prediction algorithm can adjust production and distribution volumes to supplier considering seller's product distribution information and seasonal factor.