• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.2
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• pp.23-29
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• 2024

Purpose: This study aims to investigate consumer attitudes towards healthy foods, focusing on low-calorie options, and their impact on purchasing behavior. Methods: The study utilizes structural equation modeling, which incorporates statistical tools such as SPSS and AMOS for thorough analysis. This involves collecting data over a period of time and then inferring patterns and relationships through correlation and trend analysis. Results: The study found that attributes such as quality, price, functional value, and emotional value have a significant impact on customer satisfaction and repurchase intentions, but not on nutrition and brand. The study provides a comprehensive understanding of the factors that influence consumer attitudes and purchase behavior toward healthy indulgences in the context of low-calorie foods, and has important implications for both academic research and practical marketing strategies. Conclusions and Implications: This study provides new insights into consumer behavior theory by validating the impact of the perceived value of low-calorie products on attitudes and purchase behavior, which is of great academic value. It is also expected to provide useful information for the formulation of effective marketing strategies for low-calorie products and the development of products that meet consumer needs.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.2
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• pp.19-28
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• 2024

Purpose: In the era of global economic integration, China's doors of openness have widened, leading to increasingly frequent economic and trade exchanges between countries. Exchange rates, as a crucial economic lever for regulating foreign markets, play a vital role in the balanced development of a nation's international trade. Therefore, the relationship between exchange rate fluctuations and foreign trade has garnered widespread attention. Research design, data and methodology: This study utilizes import and export trade data between China and five ASEAN countries from 1998 to 2019. It employs regression analysis to examine the specific impact of the real effective exchange rate of the Renminbi on China's import and export trade with these ASEAN nations. Results: The empirical analysis yields the following conclusions: Firstly, the real effective exchange rate of the Renminbi exhibits a long-term stable relationship with China's import and export trade with the five ASEAN countries. Renminbi appreciation contributes to an increase in export trade volume but is detrimental to import trade. While this conclusion may deviate from classical trade theories, it aligns with the practical realities of China's foreign trade. Secondly, the coefficients before Gross Domestic Product (GDP) all display positive values, indicating that the growth of total economic demand has a stimulating effect on China's import and export trade.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.817-837
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• 2019

The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.571-590
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• 2019

Despite the growing amount of mobile peer-to-peer (P2P) payment applications available on mobile app stores, these applications are still in their infancy and have yet to see mass adoption. This study aims to explore the factors that influence the adoption of such mobile P2P payment applications by using a large-scale data set based on the tracking of users' actual mobile application usage behavior. Our main findings reveal that the duration of each session that users use of traditional bank application has a significant relationship with their adoption of mobile P2P payment applications. In addition, we explore the social aspect of such mobile P2P payment applications by analyzing their social network applications usage and found that the amount of social network service applications used and usage duration positively impacted one's adoption of mobile P2P payment applications. These findings have important theoretical and practical implications for stakeholders of mobile P2P payment solution providers as well as intermediaries/banks who provide their own payment applications to their customers.

• Asia pacific journal of information systems
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• v.28 no.1
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• pp.1-18
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• 2018

Despite the increasing interest in the positive effects of smart-work, the introduction rate of domestic firms in Korea is lower than that of other developed countries. A gap also exists between the introduction of smart-work program and the actual use by workers. Thus, even if the smart-work program was introduced to firms, the actual usage rate of the program would still be lower than the introduction rate. Moreover, even if the program was initially used, evidence suggests that the usage rate tends to decrease rather than being used continuously. In this study, we intend to find out the mechanism by which the continuance intention of smart-work is formed. To achieve this objective, we established a research model based on literature on Information System (IS) continuance model and Information & Communication Technology (ICT) support. We also hypothesize that concerns about career disadvantage in the mechanism plays a negative role in the satisfaction of smart-work. To analyze the hypothesis empirically, we surveyed domestic workers who used smart-work. Our data analysis was based on 333 responses. We found that all paths were statistically significant, except for the direct effect of ICT support on perceived usefulness and the direct effect of perceived usefulness on smart-work continuance intention. The results of this study extend existing IS continuance model and suggest implications for practical smart-work implementation and improvement.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.141-158
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• 2023

In the field of animation, as technology advances, production technology, production methods, and production culture are also steadily developing. The demand for content is increasing rapidly around the OTT platform, and the demand for animation content and diversity is increasing. With these market changes, animation creation ability is becoming a more important animation education goal. There is also a need to innovate educational methods to provide students with the skills and knowledge required in the modern animation business. This paper investigated the composition of the educational curriculum of domestic and foreign animation universities education. It examines artificial intelligence (AI) technology that can be used in animation creation and explores the design and direction of the university animation curriculum using it. AI technology has already proven its potential in various areas, and it is integrated into the animation curriculum to present various development potentials. Using AI technology, students can focus on practical and essential animation education by preventing technical difficulties in animation creation, increase their experience in animation production, and experiment with planning and producing various contents. It is proposed to design an educational curriculum that further strengthens animation creation and production capabilities by forming smart animation classes to foster talents who can lead the future animation industry in a new direction.

• The Research Journal of the Costume Culture
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• v.32 no.1
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• pp.1-16
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• 2024

In response to the global trend of making sustainable development an urgent task, luxury fashion brands actively embrace it in their corporate philosophies and management policies. However, despite the widespread consensus in the related industry and the strong will of companies for the sustainable development of luxury brands, there are still few cases of luxury fashion brands successfully implementing sustainable development. This study examined the impact of the types of message framing on the sustainability marketing of luxury fashion brands, focusing on their effects on perceived message effectiveness, sustainable brand image, and brand attitudes. An online survey was administered to 464 Korean consumers in their 20s to 40s to test the hypotheses. The results showed that perceived effectiveness was higher for negatively framed messages (loss) than for their positive counterparts (gain). The types of message framing did not significantly affect sustainable brand messages, and no significant difference in perceived brand image was found, regardless of message type. Perceived message effectiveness exerted a significant positive effect on sustainable brand image, and such an image had a significant positive effect on brand attitudes. The results provide implications for related research and practical implications for the development of competitive sustainability marketing strategies for luxury fashion-an industry still in its infancy.

• Mass Spectrometry Letters
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• v.15 no.2
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• pp.69 -78
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• 2024

The advancement of high-throughput omics technologies and systems biology is essential for understanding complex biological mechanisms and diseases. The integration of proteomics and metabolomics provides comprehensive insights into cellular functions and disease pathology, driven by developments in mass spectrometry (MS) technologies, including electrospray ionization (ESI). These advancements are crucial for interpreting biological systems effectively. However, integrating these technologies poses challenges. Compared to genomic, proteomics and metabolomics have limitations in throughput, and data integration. This review examines developments in MS equipped electrospray ionization (ESI), and their importance in the effective interpretation of biological mechanisms. The review also discusses developments in sample preparation, such as Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX), analytical techniques, and data analysis, highlighting the application of these technologies in the study of cancer or Huntington's disease, underscoring the potential for personalized medicine and diagnostic accuracy. Efforts by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and integrative data analysis methods such as O2PLS and OnPLS extract statistical similarities between metabolomic and proteomic data. System modeling techniques that mathematically explain and predict system responses are also covered. This practical application also shows significant improvements in cancer research, diagnostic accuracy and therapeutic targeting for diseases like pancreatic ductal adenocarcinoma, non-small cell lung cancer, and Huntington's disease. These approaches enable researchers to develop standardized protocols, and interoperable software and databases, expanding multi-omics research application in clinical practice.

• Journal of Industrial Convergence
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• v.22 no.7
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• pp.61-68
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• 2024

This paper explores strategies to enhance internal customer orientation from the perspectives of both disabled clients and people without disabilities (social workers) within vocational rehabilitation facilities. It proposes efficient operational strategies for these facilities through a literature review on the relationship between internal customer orientation and performance. In this process, it examines how satisfying internal customer needs and focusing on job satisfaction in service provision impacts the overall economic and social performance of the organization. The study also identifies practical strategies that can help vocational rehabilitation facilities overcome challenges and achieve sustainable development.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.212-220
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• 2024

A recently the advancement of society, AI technology has made significant strides, especially in the fields of computer vision and voice recognition. This study introduces a system that leverages these technologies to recognize users through a camera and relay commands within a vehicle based on voice commands. The system uses the YOLO (You Only Look Once) machine learning algorithm, widely used for object and entity recognition, to identify specific users. For voice command recognition, a machine learning model based on spectrogram voice analysis is employed to identify specific commands. This design aims to enhance security and convenience by preventing unauthorized access to vehicles and IoT devices by anyone other than registered users. We converts camera input data into YOLO system inputs to determine if it is a person, Additionally, it collects voice data through a microphone embedded in the device or computer, converting it into time-domain spectrogram data to be used as input for the voice recognition machine learning system. The input camera image data and voice data undergo inference tasks through pre-trained models, enabling the recognition of simple commands within a limited space based on the inference results. This study demonstrates the feasibility of constructing a device management system within a confined space that enhances security and user convenience through a simple real-time system model. Finally our work aims to provide practical solutions in various application fields, such as smart homes and autonomous vehicles.