• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Journal of Korea Game Society
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• v.14 no.1
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• pp.7-18
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• 2014

For the rapid growth of Chinese on-line game market in this decade, it became more necessary to study Chinese on-line game industry, business strategy, and, especially the behavioral characteristics of on-line game users. In spite of these necessities, there were a few studies on these research fields in China. The current study investigated the relationships among perceived price, perceived quality, the flow, perceived value, and loyalty of Chinese on-line game user. In addition, we tested the influence factors on perceived value and game user loyalty of on-line game user through AMOS method. Results showed that perceived value and game loyalty are positively related perceived price and the flow, the flow and perceived value respectively.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.348-359
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• 2013

The core of contents monetization is the consumer's willingness to pay. In the past, the terrestrial contents can be used through the frequency for free. As the terrestrial contents use via online services has been increased, the importance of willingness to pay for the broadcasting contents is getting bigger. To find critical factors which can influence on the willingness to pay for the terrestrial contents, independent factors are categorized into three. The independent factors are users' awareness for copyright protection, contents characteristics, and platform characteristics. The results show that attitude for paying, subjective norms for copyright protection, rapid providing of contents, quality of service, social critical point, and expected service value are found out as significant factors. This result implies that it is necessary to enhance platform competitiveness to survive in convergence environment and customer relationships should be reinforced to maintain them as loyal customers.

• Informatization Policy
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• v.21 no.4
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• pp.40-58
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• 2014

This study investigated how online information affected consumers' purchases at social commerce websites. In the online purchase process, consumers use two types of online information: user generated content(UGC) and vendor generated content(VGC). These information types may influence consumers'purchase intention differently because each information builds entity trust and content trust, which play mediation roles between online information and purchase intention. According to the analysis results, general transactional information and safe transaction information of VGC and reputation information of UGC significantly affected entity trust. But content trust was affected only from general transactional information of VGC. And entity trust significantly affected content trust as well as purchase intention. These findings imply that social commerce vendors should focus mainly on entity trust for enhancing consumers' purchase intention. To achieve this objective, in the short term perspective, they should endeavor how to enhance general transaction information and safe transaction information qualities because these information types are easily controlled and improved by vendors. In the long term perspective, they should focus on reputation formation because reputation takes long time.

• Journal of the HCI Society of Korea
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• v.6 no.2
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• pp.11-20
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• 2011

The mass collaboration, one of the newest solutions for web-related tasks, has been recognized to be an effective tool for the R&D sectors of the corporates, since the key advantages of crowdsourcing is that the industrial challenges can be shared with the public entities to find proper solutions. This research approaches to the possibility of the design adoption with participation thorough the Internet will positively effect to its process. This research tried to look around the current trend of web 2.0 based services which support the Mass Collaboration method and results of paper related to the Crowdsourcing and design integration. Following to the analysis of web research, we meet the conclusion as just a small number of users' opinion has helped designing new product and service. And we compared it to the conventional design process detail functions, less number of websites support it. However, the result of paper research shows optimistic results of collective design activity. Several cases emphasize that participants were very active to support their thoughts, memories and novel design idea, therefore designer and researchers got enormous help from them and it was better than conventional participatory design in some perspective.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.124-132
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• 2019

Scheduling problems can be classified into offline and online ones. This paper considers an online scheduling problem to minimize makespan on the identical parallel machines. For dynamically arrived jobs with their ready times, we show that the sequencing order according to the ERD (Earliest Ready Date) rule is optimal to minimize makespan. This paper suggests an algorithm by using the MIP(Mixed Integer Programming) formulation periodically to find a good periodic schedule and evaluates the required computational time and resulted makespan of the algorithm. The comparition with an offline scheduling shows our algorithm makes the schedule very fast and the makespan can be reduced as the period time reduction, so we can conclude that our algorithm is useful for scheduling the jobs under online environment even though the number of jobs and machines is large. We expect that the algorithm is invaluable one to find good schedules for the smart factory and online scheduler using the blockchain mechanism.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.171-182
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• 2019

As online shopping malls continue to grow in popularity, various chances of consumption are provided to customers. Customers decide the purchase by exploiting information provided by shopping malls such as the reviews of actual purchasing users, the detailed information of items, and so on. It is required to provide objective and reliable information because customers have to decide on their own whether the massive information is credible. In this paper, we propose a personalized recommendation method considering an item confidence to recommend reliable items. The proposed method determines user preferences based on various behaviors for personalized recommendation. We also propose an user preference measurement that considers time weights to apply the latest propensity to consume. Finally, we predict the preference score of items that have not been used or purchased before, and we recommend items that have highest scores in terms of both the predicted preference score and the item confidence score.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.448-462
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• 2021

Only a few studies investigated the relationship between exchange structure and solidarity in online communities and even reported conflicting results. This study attempts to shed lights on this relationship by introducing a moderating variable, i.e., exchange benefits, based on the social exchange theory. Also, distributed knowledge is considered as a determinant of exchange structure. The results of a field study from 380 online communities show that both direct and generalized exchange structures have positive effects on community solidarity, but their effects vary depending on the level of exchange benefits. When exchange benefits are high, generalized exchange influences community solidarity more than direct exchange does, whereas at a low level of benefits there are no significant differences between the two exchange structures. Also distributed knowledge turns out to be a significant influencer of generalized exchange.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.119-138
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• 2016

Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.

• Journal of Service Research and Studies
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• v.7 no.4
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• pp.51-68
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• 2017

Financial technology (FinTech) is an emerging financial service sector include innovations in financial literacy and investment, retail banking, education, and crypto-currencies like bitcoin. One of the crucial branch of financial technology-third-party payment (TPP) is undergoing rapid growth, with online/mobile systems replacing offline financial systems. System quality and user attitudes are key perceptions driving third-party payment usage, the importance of these perceptions, however, may be different with countries as users' thinking varies from country to country. Thus, the purpose of this study is to elaborate how factors differ from China to Korea by drawing on the unified theory of acceptance and use of technology (UTAUT2). Additionally, this study also aims to propose a multi-attribute evaluation of the third-party online payment system based on analytic hierarchy process (AHP), fuzzy sets and technique for order performance by similarity to ideal solution (TOPSIS), to examine the relative importance of the perceptions influencing new technology adoption intention. The results showed that the price value has the most significant influence on Chinese perceptions, while the perceived credibility has the most significant effect on Korean perceptions. Sub-criteria also performs different results to Chinese and Korean third-party online payment system.