• Smart Media Journal
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• v.12 no.1
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• pp.77-91
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• 2023

Interaction methods and technologies for mutual exploration based on user behavior are evolving variously. Especially, in recent years, with the development of a wide range of sensors, they have developed from contact to non-contact methods. However, developers' senseless definitions of the interaction methods have made the exploration process quite complicated, which rather creates the hassle of users needing to learn the interaction guide defined by the developers before experiencing the exhibition contents. In this context, in order to make visitors smoothly communicate with exhibition contents, a preliminary study on easy interaction for users of various ages is needed, and in particular, research on improving the usability of user interaction is also essential when developing non-contact exhibition contents. So, in this study, a method to reduce the confusion between developers and users was sought by researching non-contact interaction that could be universally interacted with in the field of exhibition contents and proposing behavior designs. First, based on the narrative structure of cultural resources, existing studies were reviewed and the points of interactions as cultural contents were derived. Then the most efficient search process was selected among non-contact behaviors based on hand gestures that allow users to naturally guess and learn interaction methods. Furthermore, on the basis of the meaning of non-linear narrative-based interaction and the analysis results of spatial behavior elements, affordance behavior with high learning effect and efficiency was derived. Through this research process, an action that helps users to understand non-contact interaction naturally in the process of exploring exhibition-type cultural contents and to utilize non-contact interaction in the process of immersion in exhibition contents is proposed as a final model.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.769-777
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• 2023

Globalization has brought about rapid economic, technological, and cultural changes. In order for countries around the world to communicate, recognize and understand globalization, creativity or planning ability can be used to code. In this paper, we would like to present and prove a data analysis that can solve world problems. In the global market, the value of goods or services increases with connectivity. This connection is becoming one of the factors that increase the value of culture. Changes taking this into account promoted cultural spread and innovative growth, and increased productivity and competitiveness in each region of the world. This paper compares the income of the middle class in the United States on the impact of globalization and anti-globalization on cultural spread and innovative growth. Globalization has created an environment in which various elements of K-culture can interact and spread. Through the Internet, social media, and international travel, globalization has had a positive impact on Korea's innovative growth. In areas such as economic activity, technological innovation, and creative industries, globalization has facilitated new tech and approaches, Through this, it changed the existing economic model and contributed to exports K-culture with a new middle class model. However, globalization in the cultural industry can result in the loss of regional characteristics & individuality, which can lead to the middle class cultural unification and alienation(chasm). As a result of the empirical analysis of K-exports for the middle income in the United States, cultural diffusion and innovation must be developed even in anti-globalization. With these industrial changes the soft power value of the Korean Wave proves that it can create value for use for the middle class of major exporting countries.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.416-434
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• 2022

This study, for learners using online and offline tools, understood the structural relationship of user experience of smart learning app on continuous use intention through the technology acceptance model, and classified the learning type characteristics. In addition, based on the experience of using the smart learning app, we explored ways to improve the design of the user experience design for learning tools and contents. For this purpose, the usage perception of 84 middle and high school students of the developed smart learning learning app was investigated after using it for 2 months, and the data were analyzed using the PLS structural equation technique. The main results of this study are as follows. First, system and content user experience had a significant effect on perceived usability and perceived ease of use, and the effect on continued use intention through attitude was significant. Second, there was a significant difference in the effect of system user experience on perceived usefulness in multi-group comparative analysis and gender group. In the preferred learning group, it was the path from perceived ease of use and perceived usefulness to attitude and intention to continue using that showed a significant path difference. Third, as a result of classifying the most commonly used learning types by the multidimensional scale method, the types separated into low dimensions were found to be four types: offline sync type, online sync type, ubiquitous learning type, and self-direct learning type.

• Knowledge Management Research
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• v.24 no.3
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• pp.95-125
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• 2023

As the aviation industry has rapidly been grown, there are more factors for customers to consider when choosing an airline. In response, airlines are trying to increase customer value by providing high-quality services and differentiated experiential value. While early customer value research centered on utilitarian value, which is the trade-off between cost and benefit in terms of utility for products and services, the importance of experiential value has recently been emphasized. However, experiential value needs to be studied in a specific context that fully represents customer preferences because what constitutes customer value changes depending on the product or service context. In addition, customer value has an important influence on customers' decision-making, so it is necessary for airlines to accurately understand what constitutes customer value. In this study, we collected customer reviews and ratings from Skytrax, a website specializing in airlines, and utilized the BERTopic technique to derive factors of customer value. The results revealed nine factors that constitute customer value in airlines, and six of them are related to customer satisfaction. This study proposes a new methodology that enables a granular understanding of customer value and provides airlines with specific directions for improving service quality.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.750-759
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• 2023

The Korean government and industry practitioners have rapidly increased their interest in marine healing programs after the COVID-19 pandemic. However, research related to understanding the perceived usefulness, participant satisfaction, and benefits of marine healing experience from a consumer-oriented perspective is still lacking. This study used the post acceptance model to continuously examine the relationship between the perceived usefulness, expectancy confirmation, participant satisfaction, and intention to participate in a marine healing program. A survey was conducted by trained interviewers every weekend from September to October 2022 on the participants of marine healing programs in Busan city, and 203 samples were used for the analysis. The results showed that expectancy confirmation for the marine healing program positively affected satisfaction with the program and the perceived usefulness of the program. Moreover, satisfaction of the participants with the marine healing program positively affected their intention to continue participating. Additionally, the perceived usefulness of the healing program positively affected program satisfaction and continuous participation intention.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.99-114
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• 2024

Objective : This study aimed to develop an information and communication technology (ICT)-based, non-face-to-face lifestyle program for older adults and assess its applicability. Methods : The program was developed on the basis of the ADDIE model which comprises 5 stages: analysis, design, development, implementation, and evaluation. In this study, a step-by-step identification was performed in 8 stages. Results : The results of the program analysis showed a significant decrease in depressive symptoms and loneliness scores, and an increased quality of life scores. Conclusion : The findings suggest that the ICT-based non-face-to-face lifestyle program developed in this study can motivate older adults to better understand their lifestyles for successful aging, while helping senior citizen centers resume stagnant projects.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.50 no.2
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• pp.119-129
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• 2024

The cutaneous lymphatic system in humans plays a crucial role in draining interstitial fluid and activating the immune system. Environmental factors, such as ultraviolet light and natural aging, often affect structural changes of such lymphatic vessels, causing skin dysfunction. However, some limitations still exist because of no alternatives to animal testing. To better understand the skin lymphatic system, a biomimetic microfluidic platform, skin-lymph-on-a-chip, was fabricated to develop a novel in vitro skin lymphatic model of humans and to investigate the molecular and physiological changes involved in lymphangiogenesis, the formation of lymphatic vessels. Briefly, the platform involved co-culturing differentiated primary normal human epidermal keratinocytes (NHEKs) and dermal lymphatic endothelial cells (HDLECs) in vitro. Based on our system, Lymphanax^TM, which is a condensed Panax ginseng root extract obtained through thermal conversion for 21 days, was applied to evaluate the lymphangiogenic effect, and the changes in molecular factors were analyzed using a deep-learning-based algorithm. Lymphanax^TM promoted healthy lymphangiogenesis in skin-lymphon-a-chip and indirectly affected HDELCs as its components rarely penetrated differentiated NHEKs in the chip. Overall, this study provides a new perspective on Lymphanax^TM and its effects using an innovative in vitro system.

• Information Systems Review
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• v.25 no.3
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• pp.99-120
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• 2023

Courier services users' experience of violating privacy affects psychology and behavior of protecting personal privacy. Depending on what privacy infringement experience (PIE) of courier services users, learning about perceived privacy infringement incidents is made, recognition is formed, affection is formed, and behavior is appeared. This paradigm of changing in privacy psychologies of courier services users has an important impact on predicting responses of privacy protective action (PPA). In this study, a theoretical research framework are developed to explain the privacy protective action (PPA) of courier services users by applying attitude theory. Based on this framework, the relationships among past privacy infringement experience (PIE), perceived privacy risk (PPR), privacy concerns (i.e., concerns in unlicensed secondary use (CIUSU), concerns in information error (CIE), concerns in improper access (CIA), and concern in information collection (CIC), and privacy protective action (PPA) are analyzed. In this study, the proposed research model was surveyed by people with experience in using courier services and was analyzed for finding relationships among research variables using structured an equation modeling software, SMART-PLS. The empirical results show the causal relationships among PIE, PPR, privacy concerns (CIUSU, CIE, CIA, and CIC), and PPA. The results of this study provide useful theoretical implications for privacy management research in courier services, and practical implications for the development of courier services business model.