• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.322-333
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• 2019

After the launch of smart phones, various miniaturized smart devices such as wearable and IOT devices have deeply embedded in human life, and have created a technology-oriented society. In this technology-oriented society, technology development itself is important, however it seems more important to utilize existing technology appropriately and deliver effectively to human life. As the computer became personalized after the appearance of PC, human-centered computing such as HCI and UCD had begun to appear. However, most of the researches focused on technology that made human being convenient to interact with computer such as computer systems design and UX development. In the technology-oriented society, it seems more urgent to apply existing technology to human life. In this paper, we propose a methodology, 'Digital Leveraging' which guides how to effectively apply technology to human life. Digital Leveraging is the way of convergence between technology and humanities.

• Management Science and Financial Engineering
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• v.16 no.2
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• pp.1-15
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• 2010

Digital convergence which means the convergence of industry areas related to digital technologies is an important phenomenon in business, which will decide the fates of firms in the near future. The only firms which can create synergy effects from digital convergence are expected to be the winners in the fierce competition of digital convergence era. In our analysis, we examine the strategy of an integrated firm which has businesses in two different industry areas which are related to each other. By using a game theoretical model, we show how the integrated firm can win over two single separated firms which have business in only one industry area each by leveraging the two businesses the integrated firm has. In our welfare analysis, we also show that this convergence may be even beneficial to consumers, which seems counter-intuitive to social concerns about anti-competitive behaviors by integrated firms. Additionally, we study comparison between industry convergence and product convergence.

• The Journal of Economics, Marketing and Management
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• v.12 no.4
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• pp.87-99
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• 2024

Purpose: This research examines the elements that affect Chinese tourists' trip experiences and behaviors in Japan and South Korea, focusing on destination image, digital engagement, and sustainability practices awareness. Research design, data and methodology: Data were collected from 414 Chinese tourists through an online survey and analyzed conduct confirmatory factor analysis and structural equation modeling. Findings indicate a positive destination image significantly influences revisit intention but not travel satisfaction. Travel satisfaction positively affects revisit intention, while digital engagement and sustainability practices awareness both enhance travel satisfaction. Results: The results highlight the importance of leveraging digital engagement and promoting sustainability practices to boost satisfaction and repeat visits. Conclusions: The study provides practical insights for tourism stakeholders to develop targeted strategies, emphasizing customer service, sustainable practices.

• Journal of Information Science Theory and Practice
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• v.12 no.3
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• pp.63-74
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• 2024

This study aimed to develop a digital thesaurus dedicated to cataloging the traditional common culture of the Greater Mekong Subregion. The process followed a meticulous seven-step methodology, including scoping, vocabulary collection, knowledge structure analysis, relationship delineation, related word adjustments, list validation, and evaluation. Leveraging principles from knowledge organization, thesaurus construction, and digital platform development, the TemaTres web application emerged as the primary tool for constructing this thesaurus. The study's results showed that 2,042 principal words related to the traditional common culture of the Greater Mekong Subregion were compiled and classified into terms for each of the seven deep levels. Each term was accompanied by essential metadata, including broader and narrower terms, related terms, cross-references, and scope notes. This rich dataset empowered semantic search capabilities across diverse applications and web services, providing access to knowledge pertaining to the traditional common culture of the Greater Mekong Subregion and contributing to a deeper understanding of this cultural domain.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.273-278
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• 2024

The meta-universe, as an innovative medium of digital technology that integrates the virtual and real worlds, is revolutionizing the traditional K-POP industry by leveraging advanced technologies such as artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and motion capture. This transformation is gradually reshaping the entire entertainment sector. As K-POP continues its global expansion, the industry is actively exploring the application of virtual technologies, presenting viewers with a more diverse range of entertainment content. This thesis reviews the development history of virtual technology in K-POP, analyzes the practical applications of VR, AR, AI, and motion capture within the industry, and examines how these technologies enhance artist-fan interactions and immersion. The study demonstrates that the incorporation of virtual technology not only overcomes the limitations of traditional entertainment modes but also provides new directions for the future development of the K-POP industry.

• Journal of Venture Innovation
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• v.1 no.2
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• pp.1-12
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• 2018

The applications of psychology principles in marketing areas were pervasived. As the importance of digital marketing has increased, the cases of applications of psychology principles in digital marketing areas also has increased. This study analnyzed digital marketing cases based on the psychology principles of social proof, scarcity and loss aversion, reciprocity, commitment and consistency, anchoring. Cases were analnyzed amomg USA and Korea in digital marketing areas. This attempt will facilitating interdisciplinary research. It also will improve customer engagement, increase customer life value, and develope virtuous circle of customer journey through optimal user interface and message strategies.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.33-39
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• 2020

The paper is to build recommendation systems leveraging Deep Learning and Big Data platform, Spark to predict item ratings of the Amazon e-commerce site. Recommendation system in e-commerce has become extremely popular in recent years and it is very important for both customers and sellers in daily life. It means providing the users with products and services they are interested in. Therecommendation systems need users' previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. We developed the recommendation models in Amazon AWS Cloud services to predict the users' ratings for the items with the massive data set of Amazon customer reviews. We also present Big Data architecture to afford the large scale data set for storing and computation. And, we adopted deep learning for machine learning community as it is known that it has higher accuracy for the massive data set. In the end, a comparative conclusion in terms of the accuracy as well as the performance is illustrated with the Deep Learning architecture with Spark ML and the traditional Big Data architecture, Spark ML alone.

• The Korean Journal of Food & Health Convergence
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• v.10 no.4
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• pp.9-19
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• 2024

This qualitative study explores the impact of online food delivery platform attributes on customer satisfaction and repurchase intentions. Employing a phenomenological approach, we conducted in-depth interviews and focus group discussions with 15 participants to gain rich insights into user experiences. Thematic analysis revealed key factors influencing satisfaction and loyalty: service quality dimensions (efficiency, reliability, fulfillment, privacy), expectation disconfirmation, perceived usefulness and ease of use, multi-level customer value, relationship quality, electronic word-of-mouth, value co-creation, and phased loyalty formation. Our findings extend customer behavior theory in digital platforms, offering a comprehensive framework for understanding the complex mechanisms underlying user satisfaction and repurchase decisions. The study provides valuable implications for platform operators, highlighting the importance of exceeding customer expectations, enhancing user experience, building trust, leveraging user-generated content, and fostering co-creation processes. Methodologically, we demonstrate the efficacy of qualitative approaches in uncovering nuanced insights in digital service contexts. While acknowledging limitations in generalizability, this research establishes a solid foundation for future investigations into the rapidly evolving domain of online food delivery services. The integrated theoretical approach offers a robust model for analyzing customer behavior in emerging digital service environments, contributing significantly to both academic understanding and practical application in the field of digital service provision and platform management.

• Journal of KIBIM
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• v.13 no.4
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• pp.36-44
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• 2023

Recently in Korea, efforts are underway to enhance smart construction by implementing Building Information Modeling (BIM) comprehensively across all sectors of the construction industry. This study focused on the adoption of BIM for prefab bridges currently executed in the industry and It examined the process of creating a BIM-based prefab bridge model that can support production. Additionally, it explored how prefab products made by manufacturers can be integrated with road alignments using BIM technology and how the DfMA (Design for Manufacturing and Assembly) approach, which supports production based on designed information, can be adopted. The process of creating the prefab bridge model aims to shorten production time, reduce costs, and enhance quality by leveraging digital information related to design and manufacturing within the BIM framework

• Annual Conference of KIPS
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• 2024.05a
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• pp.692-695
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• 2024

With the recent advancements in artificial intelligence (AI), the performance of deep learning-based audio deepfake technology has significantly improved. This technology has been exploited for criminal activities, leading to various cases of victimization. To prevent such illicit outcomes, this paper proposes a deep learning-based audio deepfake detection model. In this study, we propose CoNSIST, an improved audio deepfake detection model, which incorporates three additional components into the graph-based end-to-end model AASIST: (i) Squeeze and Excitation, (ii) Positional Encoding, and (iii) Reformulated HS-GAL, This incorporation is expected to enable more effective feature extraction, elimination of unnecessary operations, and consideration of more diverse information, thereby improving the performance of the original AASIST. The results of multiple experiments indicate that CoNSIST has enhanced the performance of audio deepfake detection compared to existing models.