• The Journal of Information Systems
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• v.28 no.4
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• pp.199-221
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• 2019

Purpose The research investigated on what motivates the consumers to use the SNS, what qualities of images are preferred and how the pleasure and arousal derived from looking at the images have moderating effects on sharing images, following accounts, clicking profile links of accounts and accessing the link on profiles to purchase products. Design A survey was conducted by using actual images published on the Instagram profiles of an online shopping mall. Findings As a result, their emotional responses such as pleasure or arousal on the four of behavioral intentions changed the impact of SNS use motivation on the behavioral intentions. When one felt pleasure, the behavioral intentions of sharing activities and clicking links is further triggered.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.1
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• pp.47-56
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• 2012

The main goal of this study is to investigate the importance of trust as a mediator between shopping experience and shopping value. Previous studies on utilitarian shopping value and hedonic shopping value have focused on the antecedents and outcomes of those shopping values. Also, although the role of trust has been studied a lot in the series of studies on online shopping mall, most of them focus on the relationship with intention to shop or use and there are few studies on the mechanism in which consumers get to have shopping value. This study tries to see how trust can boost utilitarian shopping value and hedonic shopping value which can lead to consumer's loyalty to the shopping mall. A structural equation model is proposed and examined through a survey research to investigate the role of trust in forming perceived shopping value. One model included the trust variable as a mediator and the other excluded it. The comparison of R2 verified that the first model had a better fit. The results of the study show that the level of experience has a significant impact on both utilitarian and hedonic shopping values in the case of the model without the mediator. But experience has an insignificant or a partially significant effect on utilitarian and hedonic shopping values when trust mediates experience and shopping values. Finally, the implications and limitations are further discussed.

• Asia pacific journal of information systems
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• v.12 no.3
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• pp.71-88
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• 2002

In this paper, intelligent marketing and merchandising methods utilizing data mining and Web mining techniques are proposed for online retailers to survive and succeed in gaining competitive advantage in a highly competitive environment. The first part of this paper explains the procedures of one-to-one marketing based on customer relationship management(CRM) techniques and personalized recommendation lists generation. The second part illustrates Web merchandising methods utilizing data mining techniques, such as association and sequential pattern mining. We expect that our Web marketing and merchandising methods will both provide a currently operating Internet shopping mall with more selling opportunities and give more useful product information to customers.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• The Journal of Industrial Distribution & Business
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• v.11 no.2
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• pp.17-23
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• 2020

Purpose: The purpose of this study is to understand the effect of the unique product recommendation system on customer satisfaction. Research design, data and methodology: The survey method used the self-recording way in which the respondents selected for the study and distributed 300 questionnaires, and with due personal care, researchers collected all the distributed questionnaires. Results: The result implies that the characteristics of the product recommendation system should be more secure and developed. Conclusions: The aspects of the product recommendation system were selected as factors of price fairness, accuracy, and quality through previous studies, and the empirical analysis of the effect of the characteristics of the product recommendation system on customer satisfaction was summarized as follows. Among the attributes of the product recommendation system, the attributes of price fairness, accuracy, and quality affect customer satisfaction. Among them, the beta value of quality was the highest, and the effect of quality was the largest among the three factors. Based on the results of the study, the implications for the characteristics of the product recommendation system are summarized as follows. The aspects of the product recommendation system have a positive effect on customer satisfaction, so it is necessary to fill the needs of consumers based on the survey focused on quality

• The Journal of Bigdata
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• v.4 no.1
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• pp.29-38
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• 2019

In this paper, we propose a sales forecasting model that forecasts the sales volume of short sleeves and outerwear according to the temperature change by utilizing accumulated big data from the online shopping mall 'A' over the past five years to increase sales volume and efficient inventory management. The proposed model predicts sales of short sleeves and outerwear according to temperature changes in 2018 by analyzing sales volume of short sleeves and outerwear from 2014 to 2017. Using the proposed sales forecasting model, we compared the sales forecasts of 2018 with the actual sales volume and found that the error rates are ±1.5% and ±8% for short sleeve and outerwear respectively.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.47-54
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• 2022

The development of the Internet of Things led to new services that did not exist before. This required a change to the existing network. This study aims to verify the service quality, satisfaction, repurchase intention relationship, and the moderating effect of online reviews of Chinese consumers using fashion shopping malls. The results of the study showed that from the perspective of consumers in their 20s and 30s in China, the type, reliability, convenience, and interaction of service quality had a positive effect on customer satisfaction and repurchase intention. In addition, negative reviews among online reviews had a great influence on repurchase intention. Based on the results of the study, it will help improve the effect on online product reviews and in-depth understanding of the acceptance of online product reviews for online fashion shopping malls, and establish strategies for fashion companies to effectively manage online product reviews information.

• 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 Internet of Things and Convergence
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• v.5 no.2
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• pp.7-13
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• 2019

As online shopping is activated by the development of the Internet, consumers' purchase form is changing from the traditional face-to-face purchase method to online purchase method. Many sellers have flowed into shopping malls, and competition among sellers is very intense. Therefore, sellers in shopping malls need to establish rational marketing strategies by analyzing consumer purchase patterns and product sales trends. In this paper, we analyzed the purchase price of consumers by analyzing the product price, rating, and sales quantity of competitors who sell the same product in open shopping malls by time zone. In addition, the collected information was visualized in a chart so that the company's and competitors' sales trends could be easily compared. Using the above system, it is possible to predict the sales volume through the analyzed purchasing pattern and to select the reasonable price of the product by grasping the sales trend.

• The Research Journal of the Costume Culture
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• v.18 no.1
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• pp.118-132
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• 2010

The purpose of this study is to understand factors of risk perception and purchase obstruction by consumer characteristics and purchase experience of clothing in online. The collection of the research materials was progressed by online and offline. Out of 374 usable questionnaires used for examining this study, 278 questionnaires were collected from offline and 107 questionnaires were collected from online. Frequency analysis, factor analysis, reliability analysis, t-test, One-way ANOVA and multiple regression analysis using SPSS WIN 12.0 were conducted. Three factors of perceived risk were extracted: harmonic/image, quality/shopping process, payments. Based on these dimensions, ANOVA was conducted. The results indicated that the more purchasing experience people had, the less the extent of perceived risk they got, and quality/shopping process risk mostly among them. As the factors which obstruct purchasing decision, a security obstruction, a reliability obstruction, a convenient obstruction and an information insufficient obstruction are extracted. Also, the factors have got the result of same aspects as the perceived risk recognized by the Internet shopping experience. Meaningful differences between groups appear at security obstruction, reliability obstruction, and convenient obstruction. Perceived risk almost influenced on purchase obstruction when purchasing clothes in Internet shopping mall. When consumers perceiving harmony/image risk highly make decisions, they usually hesitate or abandon due to reliability obstruction, convenient obstruction. All the factors: including security obstruction, reliability obstruction, convenient obstruction and information insufficient obstruction made consumers perceiving quality/shopping process risk highly obstruct purchase decision.