• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.52-54
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• 2023

최근 인공지능 기술의 발전에 따라서 다양한 서비스에서 음성 인식을 활용한 서비스를 제공하면서 음성 인식에 대한 중요성이 증가하고 있다. 이 논문에서는 국내에서 많이 사용되고 있는 대표적인 인공지능 서비스 API 를 제공하는 구글, ETRI, 네이버에 대해서 감정 음성 관점에서 그 차이를 평가하였다. AI Hub 에서 제공하는 감성 대화 말뭉치 데이터 셋의 일부인 음성 테스트 데이터를 사용하여 평가한 결과 ETRI API 가 문자 오류율 (1.29%)과 단어 오류율(10.1%)의 성능 지표에 대해서 가장 우수한 음성 인식 성능을 보임을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.818-819
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• 2023

본 연구는 ICT 기술의 발전과 온라인 정보량 증가에 따른 개인화된 통번역 수요를 충족시키기 위한 새로운 AI 번역 서비스를 제안한다. ChatGPT 의 생성 기능을 활용하여 사용자의 요구사항을 반영한 맞춤형 번역을 제공하며, 사용자와 실시간 피드백을 주고받는 것이 가능하다. 이로써 번역 과정의 자동화와 사용자 맞춤형 번역 경험을 실현할 수 있다. 더불어 AI 기술이 2 차적인 서비스 모델 개발을 촉진하고, 다양한 사용자 니즈를 충족하는 신규 시장을 개척할 수 있음을 시사한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1375-1380
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• 2021

Korea's security response to application service app is still insufficient due to the initial opening of the public safety network. Therefore, preemptive security measures are essential. In this study, we proposed to establish a 'public safety network app security system' to prevent potential vulnerabilities to the app store that distributes app in public safety network and android operating system that operate app on dedicated terminal devices. In order for an application service app to be listed on the public safety network mobile app store, a dataset of malicious and normal app is first established to extract characteristics and select the most effective AI model to perform static and dynamic analysis. According to the analysis results, 'Safety App Certificate' is certified for non-malicious app to secure reliability for listed apps. Ultimately, it minimizes the security blind spots of public safety network app. In addition, the safety of the network can be secured by supporting public safety application service of certified apps.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.754-768
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• 2022

Purpose: The purpose of this study is to derive improvements through user satisfaction analysis for the smart traffic safety system being applied to improve traffic safety. Method: A survey-based IPA analysis was used to derive system and service improvements for groups of drivers and pedestrians. Result: As a result of the analysis, both drivers and pedestrian groups showed that Quadrant 1(Keep up the Good Work) was 'Perception of risk information', and Quadrant 3(Low Priority) was 'Reliability of warning information'. On the other hand, 'AI display suitability', which was analyzed as Quadrant 1(Keep up the Good Work) in the driver group, was found to be Quadrant 3(Low priority) in the pedestrian group. Conclusion: Satisfaction factors for smart pedestrian safety systems may vary depending on users, and it is judged that user-centered system construction and service provision are necessary.

• Journal of Korea Technology Innovation Society
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• v.22 no.2
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• pp.242-264
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• 2019

This study focuses on considering the factors affecting the user intention to adopt an intelligent service - A.I. speaker services. Currently there can be a considerable difference between the expectation and the realized diffusion of IT-based intelligent services. This study aims to find out this gap based on the idea of diver previous researches including TAM and UTAUT studies and to identify the direct and indirect effects of diverse factors such as security issues, perceived time pressure, service innovativeness, and the experience of these IT-based intelligent services. And this study considers the expected impact of perceived time pressure factor on the user acceptance of A.I. speaker services. In analysis results, not only the traditional factors such as the perceived usefulness and the hedonic/utilitarian motives but also the perceived time pressure, the perceived security issues, and the experience of the services should be considered as meaningful factors to affect the users adopting A.I. speaker services.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.117-126
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• 2017

This Study Focuses on the Customer Experience Story of Bandi&Luni's Centum City branch which Offers the Different Service Concept on the Competitive Book Selling Market. Bandi&Luni's Stands as one of the Largest Bookstore Chains that has 14 Offline Bookstores and an Online Bookstore Shop. The Purpose of this Study takes Lessons from the Unique Practices and Efforts of Bandi&Lunis's Online-to-Offline(O2O) Service and Service Design. In Order to Achieve this Propose, we Investigated the History, Service Concept, Value, and Performance of Bandi&Luni's from a Variety of sources and Reviewed the Previous Literatures of O2O Service and Service Design. In order to Offer Better Customer Experience the Service should be Designed from Customer's View and be Delivered through the Lifecycle of Customers. In a era of Big Data, IOT(internet of things), AI(artificial intelligence), The Service Design Innovation using Information and Communication Technology will be needed in order to Break down the Boundaries Between Online and Offline.

• Review of KIISC
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• v.30 no.5
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• pp.121-126
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• 2020

초연결사회인 4차 산업혁명 시대가 들어서면서 AI, IoT, 블록체인 등 새로운 기술들에 대한 개발과 서비스 수요가 늘어나고 있다. 4차 산업혁명 시대에 데이터는 미래 산업의 원유이고 정부는 데이터 경제 활성화를 위한 투자를 아끼지 않고 있다. 반면 데이터를 활용한 서비스의 증가로 개인정보 침해 위험성이 증가한다는 우려도 있다. 본 논문에서는 4차 산업혁명 시대에 데이터를 활용하는 신기술과 서비스를 분류하고 분야별 서비스에서의 개인정보 처리 실태 및 침해가능 요소와 개선방향에 대하여 제시한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.127-130
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• 2024

본 연구는 기존 포털형 정보 서비스의 한계를 극복하고자, 이전 연구에서 제안된 연구자의 R&D 프로세스 과정에서의 협업을 지원하는 개방형 협업 지원 서비스 플랫폼을 기반으로 하여, 본 연구에서는 R&D 프로세스 중 '사전 단계'에 대한 설계와 구현을 소개한다. 우리는 R&D 프로세스를 문헌 리뷰와 연구 가설 설정 등을 수행하는 '사전 단계,' 실험과 데이터 분석 등을 수행하는 '실행 단계', 논문 작성 및 출판 등을 수행하는 '성과화 단계'로 구분하고, 이 중 '사전 단계'에 대해 프로젝트 뷰, 그룹 뷰, 문헌 뷰, 관계 뷰를 설계하고 구현하였다. 연구자는 이 플랫폼을 통해 문헌 내용 및 문헌 간 복잡한 연관성을 신속하게 파악할 수 있으며, 플랫폼은 연구자에 의해 자연스럽게 생성되는 사용자 정의 관계를 통해 향후 심층적인 문헌 네트워크 구축 및 분석이 가능해질 것으로 기대한다.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.327-351
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• 2023

This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.