• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.109-119
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• 2024

This study aims to contribute to the initial research on on-device AI in an environment where generative AI-based services on mobile and other on-device platforms are increasing. To derive success strategies for generative AI-based chatbot services in a mobile environment, over 200,000 actual user experience review data collected from the Google Play Store were analyzed using the LDA topic modeling technique. Interpreting the derived topics based on the Information System Success Model (ISSM), the topics such as tutoring, limitation of response, and hallucination and outdated informaiton were linked to information quality; multimodal service, quality of response, and issues of device interoperability were linked to system quality; inter-device compatibility, utility of the service, quality of premium services, and challenges in account were linked to service quality; and finally, creative collaboration was linked to net benefits. Humanization of generative AI emerged as a new experience factor not explained by the existing model. By explaining specific positive and negative experience dimensions from the user's perspective based on theory, this study suggests directions for future related research and provides strategic insights for companies to improve and supplement their services for successful business operations.

• Electronics and Telecommunications Trends
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• v.37 no.6
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• pp.11-22
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• 2022

The UK is a service superpower with solid and well-developed financial and insurance services, including FinTech. Much of the UK's service industry is digital and becoming increasingly so. Primary sources constituting the UK's comparative advantage in services could be factored in business conditions driving innovation in the digital age and world-leading digital competitiveness. Therefore, this study examined the UK's digital policies. This research's focal strands were the UK's digital strategy, national artificial intelligence strategy, and digital trade objectives. As an essential insight for policymakers and other stakeholders, this study proposes that government policies in response to the digital economy are inextricably linked, leading to a critical driver for the UK's digital competitiveness.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.172-177
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• 2023

The main purpose of the research was to review the global trends of airport's smart security technologies. Moreover, using the case studies of airport using smart security, this paper tried to propose the implication how the findings through the case studies may be important for airport policy and will impact the future research of airport operation. It is expected in the future the aviation security technology with biometric information evolves from single identification to multiple identification technology which has combined application of iris, vein and others. Facing post COVID-19 era, the number of passengers traveling through airports continues increase dramatically and the risks as well, the role of AI becomes even more crucial. With AI based automated security robotics airport operators could effectively handle the growing passenger and cargo volume and address the associated issues Smart CCTV analysis with A.I. and IoT applying solutions could also provide significant support for airport security.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.175-180
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• 2020

Through case studies for insurance service marketing using artificial intelligence(AI) in the insurtech industry, it investigated how innovative technologies(artificial intelligence, machine learning etc.) are being used in the insurance ecosystems. In particular, through domestic and international case studies, it was examined by Lemonade's service of insurance contracts and getting the indemnity and AI company's service of calculating the compensation through a medical certificate image based on OCR, which brought disruptive innovations using artificial intelligence. As a result of the case analysis, these services have drastically shortened the lead time of insurance contracts and payment through machine learning using numerous customer data based on artificial intelligence. And accurate and reasonable compensation was calculated in the estimation of indemnity, which has a lot of disputes between customers and insurance companies. It was able to increase customer satisfaction and customer value.

• Informatization Policy
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• v.30 no.3
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• pp.69-91
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• 2023

The impact of technological advancements on employment is a matter of ongoing debate, with discussions on the effects of AI technology development on employment being particularly scarce. This study employs the natural language processing technique (SBERT) and patents to calculate an occupation-based AI exposure score and to analyze employment trends by group. It proposes a method for calculating the AI exposure score based on the similarity between Korean patent information and US job descriptions and linking SOC(U.S.) and KSCO(Korea). The analysis of domestic AI patent applications and regional employment data in the KOSIS Database since 2013 reveals a K-shaped polarization pattern in Korean employment trends among groups with above and below average levels of AI exposure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.21-27
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• 2020

The purpose of this study is to investigate the ecosystem structure underlying the development of artificial intelligence technology and related industries. In addition, the research on the AI business ecosystem based on AI technology and the ways to activate them was discussed. Ecosystems play a role in organically connecting producers, consumers, and decomposers. In the AI ecosystem, we classified the AI service producers, producers of AI services using the produced services, and data and related infrastructure services that are the basis of AI services. Stakeholders in the AI business ecosystem are the government and various private organizations that have a direct or indirect influence on AI service production, consumption, and operation. In Korea, in particular, the government plays a role as the most influential stakeholders. For example, the company contributes to the increase of producers, which are related to human resource development, and plays a catalyst role in the increase of services produced by R & D funding. In this study, the policy for revitalizing the AI business ecosystem includes (1) securing the environment for increasing producers, (2) spreading AI awareness among consumers, (3) securing data exchange and supply infrastructure, and (4) supporting services and related laws. Secure the system. This study is meaningful in that it contributes to and contributes to the construction of domestic AI-based environment and related research.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.325-338
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• 2022

This study was conducted to explore the acceptance behavior of undergraduate students toward telemedicine, which is temporarily allowed in the COVID-19. We applied social cognitive theory and technology acceptance model in order to reflect the convergence characteristics between medical service and digital technology of telemedicine. Based on these theoretical backgrounds, we investigated perception toward telemedicine and determinants of intention to accept telemedicine. To examine the research model and hypothesis, an online survey was conducted for college students who have not used telemedicine from September 8 to 10, 2021. A total of 184 data were collected, and multiple regression analysis was conducted using the SPSS 28.0 program. The results showed that health technology self-efficacy, usefulness and convenience benefits, social norm, and trust in telemedicine providers had positive effects on intention to accept telemedicine. This study is meaningful in that it selected undergraduate students, who are digital natives, as new targets for telemedicine, and presented the basic direction of strategies to target them.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.151-159
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• 2018

This study focused on appreciative inquiry(AI) of salespeople who have to respond to various types of emotions according to the desires of individual customers at service contact points and the effect of emotional labor on adaptive selling behavior and customer satisfaction. Dyadic questionnaires were administerd to 115 automobile salespeople and 2 customers who received service from each salesperson, and the collected data was analyzed by using structural equation modeling. The results showed that AI had positive influences on deep acting and surface acting. Only deep acting was found to have positive relationship with adaptive selling behavior, but not to surface acting. Adaptive selling behavior had a positive effect on customer satisfaction. This study will contribute to identifying the need for AI access for salespersons and for activating adaptive selling behavior through emotional labor related to AI practice.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.47-56
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• 2020

The purpose of this study is to comprehensively analyze elementary school teachers' perceptions of the use of artificial intelligence in education. Recently, interest in the use of artificial intelligence has increased in the field of education. However, there is a lack of research on the perceptions of elementary school teachers using AI in education. Using descriptive statistics, multiple linear regression analysis, and semantic differential meaning scale, 69 elementary school teachers' perceptions of using AI in education were analyzed. As a results, artificial intelligence technology was perceived as most suitable method for assisting activities in class and for problem-based learning. Factors which influence the use of AI in education were learning contents, learning materials, and AI tools. AI in education had the features of personalized learning, promoting students' participation, and provoking students' interest. Further, instructional strategies or models that enable optimized educational operation should be developed.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.177-185
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• 2019

The purpose of this study is to investigate the causes of career problems, which are the biggest problems of Korean university students, and to solve them by using case studies of domestic and global universities, I would like to suggest a career advisor system model for college students. It is most important to collect advice and learning data to solve the career problems of college students by utilizing information technology such as data analysis and AI. Research has not been actively pursued because the university has very limited internal data to advise on career problems. In this paper, we study the data types and methods of college students' career advice, and propose a career advisor counseling system for college students.