• The Journal of Information Systems
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• v.32 no.4
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• pp.69-94
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• 2023

Purpose Social networking service (SNS) platforms employ distinct networking strategies to meet the varying needs of their users, resulting in divergent sets of technological functionalities offered by each platform. Consequently, unique features on various SNSs give rise to distinct social issues. Moreover, the available technical coping mechanisms for users vary significantly across platforms. Design/methodology/approach Therefore, this study analyzes the factors affecting technical coping intention based on technical functions of SNSs for users exposed to cybercrime, such as sexual harassment. We divide coping intention into active and passive coping intention. Furthermore, this research focuses on trust as an antecedent of coping intention and verifies how human and system-like trust affects two coping intentions in different directions. Findings Findings reveal that system-like trust significantly affects both active and passive coping intention as a belief in whether the technology will work properly. However, in the case of human-like trust, trust in the platform provider was found to negatively affect passive coping, which is considered unsocialized behavior on SNS platforms. Therefore, both human-like and system-like trust for the platform must be appropriately applied to cope with the problem while activating the platform.

• Journal of Korea Game Society
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• v.13 no.1
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• pp.49-60
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• 2013

The government enacted shutdown system in the fall of 2011. It was to secure a right to sleep for the youth and prevent them from being addicted to game. The opinion on the system was dichotomized: gamers were against it for the reason that shutdown system was not effective while non-gamers like parents thought that it was a measure to prevent game addiction. The trust of the public on the government is influenced by the factors of moral and competence. That is, if the policy chosen by the government is effective, the public come to trust their government more. Focusing on the factors of the government competence, this study examined to know how the effectiveness and efficiency of governmental policies have impact on the public trust on the government. Particularly this study looked carefully into what factors of political effectiveness have impact on the trust by group (group with and against the shutdown system). Through this study some implication could be obtained for the difference in trust between two groups.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.941-946
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• 2006

It followed in system development and SMRT(Seoul Metropolitan Rapid Transit Co)System reached to an automatic train operation(ATO) and driverless operation(DLM) from the manual operation due to the train driver. The train like the general bus or the car vehicle was not serial riding in a car and the Parallel concept which the numerous passenger rides in a car simultaneously occur frequently the charge of the train driver unmanned bitterly from existing manual handling was a possibility of doing, train open door control(ODM) which bites also ATO, it handles it minimized. Like this ATO/DLM, the control system which bites being a Wayside to Train communication for immediacy, it is a system of the Vital concept the immediacy of the citizen Data evil the radio information transmission and the train of the interface which is accurate from unmanned operation and, will decipher, will accomplish it will guarantee. It respects the passenger accident prevention and an air question environment improvement from subway platform and phul leys the screen door of Platform(PSD) with the fire tube frost it refers and part it treats and to sleep it does, ODM which bites is accuracy and immediacy of altitude and when seeing from the viewpoint which demands the trust of altitude, ODM system the trust of car incest interface in the equipment construction which is safe and the comparative analysis back of the system analysis against the control which bites and case study and other subway system it leads from the research which it sees and signal - train in base grudge to sleep it contributes it does.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.63-68
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• 2010

Mobile devices like iphone, ipad, kindle, and PDA are used as everyday tool. In the mobile environment, smart phones and other mobile units are also used as a tool for protection or infringement of personal information. Therefore, smart monitoring technology is required to protect personal information and privacy. On the other hand, with smart phones and the mobile environment, diverse application technologies are realized on hardware and software platforms. Therefore, this paper designs the network structure that forms privacy trust zone, and based on this, deals with the monitoring and monitoring prevention system with a focus on CCTV, through which this paper proposes a system that provides privacy trust zone information and its utilization which is capable of smart monitoring.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.808-815
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• 2003

Fieldbus technology is having a massive impact on the development of faster, smarter and less expensive industrial networking systems. However, there have been a few of practically applied cases and channels for obtaining technical advices. Moreover, the users in the industry don't trust the Fieldbus technology like they didn't trust PLC control system in 1970s. Therefore, in this paper, Air flow control system is constructed by Fieldbus technologies, Profibus and Inverter that controls the motor speed. With the features of the motor control, the amount of electric power consumption by the speed control of motor is measured by the constructed control system. From this measured result, the effectiveness of the airflow control system and Feasibility to the practical industry field is demonstrated To improve the confidence of Fieldbus technology, practically embodied cases and technical methods are presented.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.9-18
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• 2021

Blockchain and its infrastructure technology have expanded rapidly in the last decade and are in high demand, but there is a lack of comprehensive studies on those platforms. Blockchain is a new technology based on the distributed digital ledger system. Decentralized trust is one of the key factors behind the blockchain-based system. Transparency of such a system is better than a conventional centralized ledger system. By using a blockchain-based transaction system, any business organization can harness key benefits like data integrity, confidentiality, and anonymity without involving any third party in control of the transactions. Since the blockchain is used in numerous applications and the horizon is expanding at an unprecedented pace. So, there is a need for an introducing and reviewing of blockchain platforms. In this paper, we have reported a review on existing contemporary blockchain platforms. In particular, From the existing studies, we have identified eighty blockchain platforms and the majority of them have a lack of technical details. To provide the researchers a comprehensive introducing on blockchain platforms to perform a broad guideline for future research and investment in the blockchain domain.

• The Journal of Industrial Distribution & Business
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• v.8 no.5
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• pp.95-109
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• 2017

Purpose - The purpose of this study is to classify the quality factors of coffee shop customers with the service quality based on the SERVQUAL, selection attributes, and service qualities used in previous studies. The path structure of coffee shops' quality factors → customer satisfaction → trust → behavioral intention was analyzed in order to confirm the system of coffee shops' quality factors. Research design, data, and methodology - The survey of was conducted with college students of Kangwon University. A total of 250 questionnaires were distributed, with 232 collected. Of them, Excluding 36 respondents' because of incomplete answers and missing values, 196 responses were used in the final analysis. Empirical analysis was made through factor analysis, correlation analysis, multiple regression analysis, simple regression analysis and mediating regression analysis by using Statistics Package SPSS 19.0. Results - The results are as follows: Firstly, coffee shops' quality factors were classified into seven categories like service encounter quality, product quality, cleanliness, overall interior, purchase quality, convenience, and aesthetics. Secondly, service encounter quality, product quality, purchase quality, and aesthetics had a positive effect on customer satisfaction, respectively. Thirdly, it showed that service encounter quality, product quality, overall interior, purchase quality, and aesthetics had a positive effect on trust, respectively. Fourthly, customer satisfaction had a positive effect on behavioral intention. Lastly, after verifying the effect relations of trust between customer satisfaction about coffee shop and behavioral intention, customer satisfaction has a positive effect on trust and trust has a positive effect on behavioral intention. On the other hand, trust did not have a mediating effect between customer satisfaction and behavioral intention. But, cleanliness, convenience, and overall interior did not have a positive effect on customer satisfaction. Conclusions - Coffee shop consumers put importance on price, discount systems, taste, and freshness, but more on courteous and kind services of coffee shop staff or comfortable and calming atmosphere of inner space. Thereby, coffee shop marketers need to take factors like service encounter quality and aesthetics into more consideration. In addition, customer satisfaction has an effect on trust, while trust on behavioral intention, even though trust is not mediated between customer satisfaction and behavior intention.

• Journal of Information Technology Applications and Management
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• v.17 no.4
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• pp.1-17
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• 2010

As web technologies evolve and so-called Web 2.0 technologies appear, collective intelligence is being applied in widespread areas. In general, mass collective intelligence like Wikipedia is created, revised, and managed by anonymous participants in an uncontrolled system. Thus, the knowledge provided by mass collective intelligence may be distorted, and may not be true, which may affect the user acceptance behavior. However, there have been few academic studies that analyzed the factors that affect user acceptance of mass collective intelligence, and their relationships. Under this academic background, we develop a model to examine how mass collective intelligence is accepted by users. The theoretical model is validated through an online survey of the Wikipedia users from three universities in Korea. The results reveal that the users will have positive attitude towards adopting mass collective knowledge when they perceive that the knowledge from mass collective intelligence is useful. We also find that the perceived usefulness of the knowledge is affected by perceived knowledge quality and trust in knowledge contributors. The results also suggest that perceived knowledge quality is determined by perceived level of collaboration, perceived objectivity, and recipient expertise, whereas trust in knowledge contributors is determined by natural propensity to trust and perceived objectivity. Theoretical and practical implications about mass collective knowledge are discussed.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.5
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• pp.871-883
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• 2018

This study tests consumer responses to online product recommendation service offered by a website. A product recommendation service refers to a filtering system that predicts and shows items that consumers would like to purchase based on their searches or pre-purchase information. The survey is conducted on 300 people in an age group between 20 and 40 years in a panel of an online survey firm. Data are analyzed using confirmatory factor analysis and structural equation modeling by AMOS 20.0. The results show that personalization quality does not have a significant effect on trust, but relationship quality and technology quality have a positive effect on trust. Three types of quality of recommendation service also have a positive effect on commitment. Trust and commitment are factors that increase service usage intentions. In addition, this study reveals the moderating effect of light users vs heavy users based on online shopping time. Light users show a negative effect of personalization quality on trust, indicating that they are likely to be uncomfortable to the service using personal information, compared to heavy users. This study also finds that trust vs commitment is an important factor increasing service usage intentions for heavy users vs light users.