• Journal of Digital Convergence
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• v.17 no.4
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• pp.355-364
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• 2019

The purpose of this study is to present the implications of analyzing users' market segmentation and characteristics based on the tourism SNS lovemarks experience. The results are as follows. First as a result of conducting factor analysis of tourism SNS lovemarks experience, five factors explained namely, mystery, sensuality, intimacy, trust, reputation. Second, as a result of conducting cluster analysis, four cluster groups were identified (reputation/sensuality centered experience group, high lovemarks experience group, intimacy centered experience group, low lovemarks experience group) and each characteristics were profiled. Third, as a result of Chi-square analysis and correspondence analysis, there was a difference in the characteristics of tourism SNS usage by cluster. Fourth, higher tourism SNS lovemarks experience segmented groups were more likely to recognize the degree of experiential value, satisfaction, behavioral intention.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.75-86
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• 2020

With the advent of the 4.0 era of logistics due to the Fourth Industrial Revolution, infrastructures have been built to receive the same services online and offline. Logistics services affected by logistics 4.0 and IT technology are rapidly changing. Logistics services are developing using technologies such as big data, artificial intelligence, blockchain, Internet of things, and augmented reality. The convergence of logistics services and various IT new technologies is accelerating, and the development of data management solution technology has led to the emergence of electronic cargo waybill to replace paper cargo waybill. The electronic waybill was developed to supplement paper waybill that lack economical and safety. However, the electronic waybill that appeared to complement the paper waybill are also in need of complementation in terms of efficiency and reliability. New research is needed to ensure that electronic cargo waybill gain the trust of users and are actively utilized. To solve this problem, electronic cargo waybill that combine blockchain technology are being developed. This study aims to improve the reliability, operational efficiency and safety of blockchain electronic cargo waybill. The purpose of this study is to analyze the blockchain-based electronic cargo waybill system and to derive evaluation indicators for system supplementation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.567-575
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• 2020

As online social networks are used as a critical medium for modern people's information sharing and relationship, their users are increasing rapidly every year. This not only increases usage but also surpasses the existing media in terms of information credibility. Therefore, emerging marketing strategies are deliberately attacking social networks. As a result, public opinion, which should be formed naturally, is artificially formed by online attacks, and many people trust it. Therefore, many studies have been conducted to detect agents attacking online social networks. In this paper, we analyze the trends of researches attempting to detect such online social network attackers, focusing on researches using social network graph characteristics. While the existing content-based techniques may represent classification errors due to privacy infringement and changes in attack strategies, the graph-based method proposes a more robust detection method using attacker patterns.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.

• Journal of Information Technology Services
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• v.21 no.1
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• pp.1-19
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• 2022

With the revision of the Credit Information Use and Protection Act in August 2020, the MyData service based on open banking policy will take effect in January 2022. Nonetheless, the previous studies focused on the legal system or security-related issues of such service. Therefore, this paper conducted an empirical study on financial consumers aged 20 or older nationwide to analyze the factors which influence the intention to use MyData services based on open banking. Five characteristics representing open banking-based MyData service were derived through prior research, and a research model that combined value-based adoption model and privacy calculus theory was presented. The proposed research model and the relationship of its variables was analyzed using a sample of 400 users that is randomly selected. The results of empirical analysis showed that personalization had the greatest influence on benefits and reliability on sacrifice among service characteristics. They also suggested that MyData operators should devote themselves to providing customized services optimized for customers and establishing trust relationships. It was confirmed that both usefulness and enjoyment had a great influence on perceived value, and in terms of sacrifice, the burden of financial costs had a greater influence than privacy concerns. This study is meaningful in that it explored the psychological propensity of financial consumers to identify service utilization factors and presented a new approach that can contribute to the successful settlement of the domestic MyData industry.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.43-61
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• 2022

Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI understanding as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the intention to use AI. It was also found that AI knowledge of users differently influence the intention to use through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness have positive causation to the intention to use in AI financial service. On the facilitating conditions, unlike other variables, it was found that the user's intention to use was different by the level of AI understanding. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the intention to use AI.

• Information Systems Review
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• v.22 no.1
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• pp.1-16
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• 2020

Blockchain is emerging as a technology that can build trust between users participating in the system. As interest of Blockchain has increased, previous studies have mainly focused on cryptocurrency and application methods related to Blockchain technology. On the other hand, the studies on the stable implementation of Blockchain were rarely conducted. Typically, uncle block in the Blockchain plays an important role in the stable implementation of the Blockhain system, but no study was conducted on this. Drawing on this recognition, this study attempts to predict the uncle block of Blockchain using machine learning method, Blockchain information, and macro-economic factors. The results of artificial neural network and support vector machine analysis, Blockchain information and macro-economic factors contributed to the prediction of uncle block of Blockchain. In addition, artificial neural network using only Blockchain information provided the best performance for predicting the occurrence of uncle block. This study suggests ways to lead and contribute to Blockchain research in information systems filed.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.85-105
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• 2024

Augmented Reality (AR) is a mix of the real world that is enhanced by virtual objects from computer-generated information. AR is currently used in a variety of information systems and library services. AR technologies are also being developed for today's children, who are digital natives and are exposed to various technologies even earlier. To assist librarians who need to accurately understand users' information needs and perceptions of the technology being used in their libraries, we conducted a study of AR perceptions among children. We conducted two online co-design sessions using "Would you rather?", a co-design technique that facilitates research into children's opinions. Through the co-design sessions, we found that children were psychologically wary about AR technology due to a lack of trust in the technology, and realism had a significant impact on these judgments. We also identified that children considered AR technology environments as an extension of the real world. Their real-world values directly influenced their perceptions of AR. This research provides insights into the wariness that libraries need to be aware of when developing AR content for children in the future, and how libraries can use AR as an educational tool.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.653-665
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• 2020

As the use of recommended agents has become more active, the "Explain Facilities" is drawing attention as a way to solve the black-box problem that could not explain internal logic to users. This study wants to look at how the description Method and Detail affects to user experience. The Explanation method was divided into 'why the agent did a particular action' and 'why not do a particular action' and the detail condition were divided into 'high or low'. Studies have found that 'why method' have a positive effect on users' transparency, trust, satisfaction, and behavioral intention to use, and 'high detail condition' higher the user' Psychological reactance. In addition, it was found that the explanation methods and detail influenced the 'Explanation' perception through interaction and tended to affect satisfaction and intention to adopt recommendation. This study suggested that careful attention is needed to determine the method and detail of the Explanation facilities in the context of the recommended agent, based on the research findings that it affects the user experience through the interaction of the method and detail.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.2
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• pp.151-157
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• 2005

The purpose of this study is to get related appropriate data for correct awareness and education of the university students who are using contact lens by investigating university students' awareness, present status, using habits and complication of contact lens. The method of survey was made by questionnaires which were spread to the group of 408 university students. The result indicated some characteristics including using daily wear soft lens of 55.7%, the major motive of using them is for cosmetics of 45.6%. Among them, 54.9% experienced complication, and the xerophthalmia was the most conspicuous case in the aspect of the kinds of the complication. In the aspect of the place where they purchased the contact lens, 93% of the users bought them at eye glasses stores. But when they experienced inconveniences of the contact lens, only 18.8% consulted the Stores. In the fact, I think, the users don't seem to trust the stores fully. Furthermore, 43.5% endure the inconveniences when they get them without any treatment. The fact indicates that they don't realize the seriousness of the complication due to contact lens. Reviewing above-stated facts, information and education for correct awareness and managing methods of contact lens, the complication seem 10 be required. In addition, optician specialized knowledge on contact lens and the sense of duty on national eye health improvement seem to be required.