• Journal of the Korea Society of Computer and Information
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• v.6 no.3
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• pp.1-10
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• 2001

Recently, way of Electronic Commerce is changing with increment of Internet users. In the previous way of commerce, users used to search for information by themselves. However, for user's convience, it can be done for users from one site. Mobile in order to provide users with such service. By the mobile agent-based Electronic Commerce system, users can get information from one site, and service companies can provide various and useful information to users. This is very important for construction of reliable Electronic Commerce environment, However, in generally used mobile agent-based platforms, the user should know URL information. and it is based on search engines. And as user's requirement levels become higher, they want to be provided with integrated and summarized service. In this paper, we implement product-trading system by applying mobile agent concept in order to satisfy user's requirement of getting required information from one site with minimal mouse click. For implementing the product trading system, E-speak, which is a platform for E-Service, is used And contents are saved as XML documents and data are shared based on these documents.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.

• Asia Marketing Journal
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• v.9 no.2
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• pp.97-129
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• 2007

The critical link between consumer-based internet ordering and the delivery of the product to the consumer is a key success factor in online shopping. Market areas of online shopping company implies the range of space where products ordered from online shopping can be physically delivered to customers distributed over space with reasonable shipping cost and lead time through the physical distribution network. The average rate of growth in online shopping is 36% per year in Korea for the last 5 years. But there are no maps available that describe sales/delivery density of online shopping, few researches are focused on the short-term/long-term adaptation to demand increase by online shopping. In this paper (1) Maps of trade area are described indicating the sales/delivery density around the nation. (2) Empirical researches suggested that short-term adaptation to demand increase resulted in price reduction and service in enhancement of service quality in local transportation. But the long-term adaptation on the parts of parcel delivery industry are to be investigated in future researches.

• Information Systems Review
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• v.20 no.1
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• pp.61-80
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• 2018

Individuals often receive smishing campaigns (mobile phishing messages), which they treat as spam. Thus, firms should understand how their customers distinguish their promotion messages from smishing. However, only a few studies examined this important issue. The present study employs the elaboration likelihood model to develop research hypotheses on the relationship between message cue and message credibility. The message cue in this study is classified as content cue, which is found in the content of promotion messages, and as leakage cue, which is found in peripheral information in the message. Leakage cue includes orthography (inclusion of special characters)and an abbreviated link sent by a faithless sender. We also propose that contextualization has a moderating effect on the relationship between content cue and credibility. We conducted a survey experiment to examine the effect of message cues on message credibility in the context of respondents receiving discount coupons through mobile messages. The result of data analysis based on 166 responses suggests that leakage cue had a negative effect on message credibility. A message with defective content cue has a marginally negative effect on message credibility. In particular, defective content cue in a high-contextual message has a strong negative impact on message credibility. This effect was not observed in low-contextual messages. Moreover, message credibility is significantly low regardless of the degree of contextualization if there is a leakage cue in the message. Our findings suggest that mobile promotion messages should be customized for message receivers and should have no leakage cues.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.1
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• pp.1-7
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• 2010

Purpose: To plan and improve consumers' satisfaction by analyzing consumers' purchasing behavior of spectacles. Also this will show the need of improvement in reliance of an optician. Methods: A total of 307 people (10 to 60 years) participated in individual questionnaires. Questionnaires comprised of general characteristic of surveyed people, purchasing spectacles behavior, satisfaction after purchasing spectacles, reliability of optician, and improvement points of optician. Results: Most important points in selecting the product were the design and the price of the spectacles. 142 people (46.3%) replied "average" and 140 people (45.6%) replied "satisfying" out of maximum point of satisfaction level which was 5 points. 72.3% of people have regularly visiting optical shop due to the high accessibility, after-sales care, and courteous optician. On the contrary, 27.7% replied "never visit same optician shop again" because of the low accessibility, minimal range of products, and high price. Data showed that people had high re liability about the opticians' knowledge of product, and their technique of eye refraction. Data revealed that people did not show high satisfaction about opticians' knowledge of ophthalmology, and price of products. Most important improvement points were accurate spectacle prescription by Opticians rating 42% of reply. Factors most considered during spectacle selection among the 10 to 20 age group were design by 34.8% and price by 10.1%. Among the 40 to 50 age group, most considered factors were design by 14% and spectacle frame material by 10.1%. Conclusions: Satisfaction rate of purchasing spectacles for the total participant group was 4.2 average grades. Reliability of opticians' eye refraction result and prescription was 50.5%. However consumers wanted to obtain more accurate eye refraction result and prescription with more comprehensive explanations. Also, consumers wanted opticians to be sensitive and have appreciative eye in select spectacles for customers, and to offer precise spectacle dispensing services and courteous after-sales care.

• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1535-1544
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• 2018

This study surveyed purchase behavior of users who purchased goods within the last year to analyze the relationship of search intention to purchase behavior according to SNS channel attributes. Based on these findings, it is analyzed that the information provision and interrelationships in SNS channel attributes affect search intent. In order to enhance the purchase behavior through the users of NS Channel, reliability and information availability are also cited as major issues, but more importantly, SNS channel search index is more important. It is also important to increase search indexes by simply increasing the attributes of SNS channels by improving the reliability of information and information availability, and by enhancing information delivery performance and interaction.

• 지역과문화
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• v.7 no.2
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• pp.155-172
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• 2020

This study analyzed the factors to customer attitude on the goods and service introduced in UGC(User Generated Contents) and explored the difference between Korean and Chinese customers. For the first research question, the hypothetical factors were selected through literature review, the area of which are media consumption, social media and effect of advertising. In this study examined 4 independent variables: information, reliability, BJ attractiveness and customer innovation. Methodologies are confirmatory factor analysis, correlation analysis and multi regression. Result showed that reliability, BJ attractiveness and customer innovation are statistically significant. According to the β value, the biggest one is customer innovation, the second one is BJ attractiveness and the third one is reliability. The influence of information on customer attitude is not statistically significant. The result is well-aligned with the prior studies. The information factor's influence, however, is disputable because some prior studies shows that it is not significant when the research samples are recently developed channel such as mobile or social media commerce platforms. It is necessary to identify the root causes why the information factor is not significant in some research cases. For the second research question, this study used independent t-test between Korean and Chinese customers. The result shows that the difference in reliability, BJ attractiveness and attitude are stastically significant, and the ratings of Chinese customers are higher. This result caused by the difference of media commerce environment between Korea and China. Information and customer innovation didn't show significant difference.

• Journal of Service Research and Studies
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• v.8 no.4
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• pp.77-88
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• 2018

Collaboration works on R&D project have many characteristics in interoranizational relationships. There are many variables on explaining the their relationships. In the previous study, I chose some relevant variables and some hypotheses. Base on service marketing theories and relationship marketing perspective I suggest 5 hypotheses. Independent variables are fairness and quality, and dependent variable is loyalty. And trust are treated as the intervening variable between the independent variables and dependent variable. To test the research model and some hypothesis empirically, I collected the data using the questionnaire. Sample size was 448, it was enough to analyze statistically. Data were analysed using the SPSS and AMOS. In the previous study, H1($fairness{\rightarrow}trust$), H2($quality{\rightarrow}trust$), H5($trust{\rightarrow}loyalty$) were accepted, but H3 and H4 were rejected. The reason H3($fairness{\rightarrow}loyalty$) and H4($quality{\rightarrow}loyalty$) were not accepted might be attributed to the fact that trust was the mediating variable between fairness and loyalty, quality and loyalty. Specific research methodologies and statistical findings from AMOS were referred in the previous study(Jeong 2018). In this study, I suggested some hypotheses on the mediating role trust between fairness and loyalty and service quality and loyalty. Using the PROCESS-macro, I found that trust was the mediating variable between fairness and loyalty as well as service quality and loyalty. This research is the complementary and extended study from previous research.

• Journal of Venture Innovation
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• v.5 no.2
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• pp.1-14
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• 2022

Mobile shopping goes beyond the level of a tool that simply supports consumers' shopping in-store and creates a new level of experience for consumers through offline connection. It is important to acquire new customers in order to gain a competitive advantage through mobile shopping, but it is more important to maintain a continuous transaction relationship with the secured customers. Existing mobile shopping-related studies can be largely classified into three categories such as a study on the characteristics of mobile consumers, a study on the characteristics of a mobile shopping mall, and a study on the characteristics of mobile shopping itself. Therefore, this study aimed to analyze the impact of perceived value, perceived risk, and innovativeness on trust in mobile shopping. In order to investigate the impact of perceived value, perceived risk, consumer innovativeness on the trust in mobile shopping, consumers who have experience in purchasing products through mobile were investigated. The data collected in this study were verified the reliability and validity of the measurement items based on the measurement validation process. In this study, regression analysis was performed by selecting perceived value, perceived risk, innovativeness as independent variables, and trust as dependent variables. As a result of the analysis, perceived value, innovativeness had a positive impact on trust and perceived risk had a negative impact on trust. As a result of analysis, three hypotheses were supported. Finally, implications of the research are presented, and limitations and directions for future research are described.