• The Journal of Economics, Marketing and Management
• /
• v.12 no.3
• /
• pp.23-33
• /
• 2024

This study aims to enhance the accuracy of effective demand analysis for publicly supported private rental housing by integrating the RIR into the traditional Mankiw-Weil (MW) model. Traditional models like the M-W model, which account for household income, housing costs, and household size, often fall short in estimating demand driven by large-scale development projects. By integrating the RIR factor, this study introduces a more accurate and practical approach to analyzing effective housing demand. Findings show that the modified M-W model incorporating RIR predicts effective demand with greater precision than traditional methods. This advancement allows developers to plan projects more efficiently and aids governments and local authorities in implementing more effective housing policies. Furthermore, the study assesses the real housing cost burden on households, elucidating their capacity to pay housing costs based on household size and income quintile. This information enables policymakers to design targeted housing support policies for specific demographic groups. Additionally, the research provides comprehensive policy recommendations tailored to various regions and housing types. Overall, this study lays a vital groundwork for the long-term analysis of the effects of economic changes and housing market trends on effective demand.

• Journal of Korean Society for Quality Management
• /
• v.52 no.1
• /
• pp.115-133
• /
• 2024

Purpose: The purpose of research is to explore the factors influencing the intention to adopt altcoin investments, based on the Unified Theory of Acceptance and Use of Technology. Through this, it seeks to elucidate the key factors impacting altcoin investment adoption, and provide a comprehensive understanding of the crypto-currency market and investor behavior. Methods: This study analyzed factors affecting altcoin investment intentions using frequency and descriptive analyses, and verified socio-demographic differences with t-tests and ANOVA. Exploratory factor and correlation analyses were conducted for research tool validity and relationship assessment among variables. Hypotheses were tested through regression analysis, integrating control, independent, and moderating variables, along with interaction terms, to establish the model and examine moderating effects. Results: As a result, it is revealed that higher age and experience in crypto-currency investment are associated with intention to invest. Among the independent variables, performance expectancy, social influence, facilitating conditions, and personal innovativeness have positive effects to investment intention to invest, while effort expectancy had a negative effect. The moderating variable, perceived risk, also negatively affected the intention to invest. Notably, significant moderating effects of perceived risk were observed in the relationships between investment intention and both performance expectancy and personal innovativeness. Conclusion: This study provides empirical verification into consumers' intentions to invest in altcoins, offering insights into investors' behavior and decision-making processes based on a practical understanding of altcoin investment acceptance.

• Asia-Pacific Journal of Business
• /
• v.15 no.1
• /
• pp.113-129
• /
• 2024

Purpose - This study aims to empirically identify the quantitative effects of work from home (WFH) on employee productivity using field data. Design/methodology/approach - Based on large-scale field data from a South Korean company which introduced the WFH arrangement in 2020, we conducted fixed effect and moderating effect analyses using individual-level panel data over sixty-three weeks. Findings - The empirical analysis generated several findings. It was found that overall, WFH has a positive effect on productivity. However, the productivity impact of WFH was found to vary depending on task characteristics. Specifically, WFH led to over 20% increase in productivity for simple and repetitive tasks. On the other hand, no significant productivity impact was observed for professional and knowledge-based tasks. Research implications or Originality - As the first study based on field data from South Korea, this study offers convincing causal evidence of the moderating impact of task characteristics on the relationship between WFH and productivity. Further, the above findings provide managers with practical insights concerning their work arrangement decisions.

• Korea Journal of Hospital Management
• /
• v.29 no.1
• /
• pp.64-75
• /
• 2024

Purposes: This study aims to identify the characteristics of the study subjects by age, including non-elderly people aged 19 to 65, pre-elderly people aged 65 to 75, and elderly people aged 75 and over, and to identify factors affecting health literacy based on an investigation of the health literacy level of each study group. This study would like to find out the differences in health literacy factors by age group. Methodology: The HLS-EU-Q16, developed by the World Health Organization Regional Office for Europe for the Health literacy Survey of Europeans, will be applied in this study. Findings: We found that scores decreased in order of nonelderly, pre-elderly, and late-elderly in health care, disease prevention, and health promotion. In addition, health literacy was lower in the older age group, and higher health literacy was associated with being unmarried, higher education, and higher income. In terms of influencing factors, marital status was significantly different in the non-elderly group, and higher education level was associated with higher health literacy. Practical Implications: The results of this study show that health literacy levels are low in all age groups, and efforts to improve health literacy in younger, older, and non-elderly groups are needed. It is expected that age-specific health literacy strategies can help improve the level of understanding and utilization of health information, improve health, and lead a healthy life.

• Korea Journal of Hospital Management
• /
• v.29 no.1
• /
• pp.56-63
• /
• 2024

Purposes: This study aims to analyze the correlation with the current status of the medical resident application rate, physician's income, and non-benefit rates of majors in each specialty subject and to suggest implications. Methodology: First, it analyzes the correlation between the medical resident application rate by specialty subject and the income of physicians. Second, it analyzes the correlation between the income of specialists and the non-benefit rate for each specialty subject at the clinic level. Findings: First, a significant positive correlation was found between the medical resident application rate and the average physician's income for each specialty subject (r=.718, p<.01). Second, a significant positive correlation was observed between physician income at the practitioner level by medical specialty and the non-benefit rate (r=.726, p<.01). Practical Implications: In this study, the correlation between medical resident application rate by specialty subject and physician's income, non-payment and physician's income was confirmed. Choosing a department that is less risky and can earn higher income is a natural phenomenon, but it is necessary to adjust the physicians crowding phenomenon to a specific specialty subject at the government level to maintain the medical system.

• Journal of Information Technology Applications and Management
• /
• v.31 no.1
• /
• pp.1-9
• /
• 2024

Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.20 no.2
• /
• pp.159-174
• /
• 2024

Recently, as demand for delivery services has increased rapidly due to COVID-19, the food service O2O(Online to Offline) platform has also grown significantly. This study aimed to verify the influencing factors on continuance use intention of O2O platform using the Information Service Success Model and Post Acceptance Model. An online survey was conducted on 379 consumers who used the food service O2O platform in the past six months, and the collected survey was analyzed using SPSS 26.0 and AMOS 24.0. As a result of the verification, in the influence relationship between the Information Service Success Model and Post Acceptance Model, system quality was found to have an effect on perceived usefulness, but information quality and service quality were rejected for perceived usefulness and were partially adopted, The rest were all found to have a significant effect. In the moderating effect according to the amount used, the intention to continue using was stronger when the group who spent more than 30,000 won was satisfied. These results support previous research on O2O platforms and provide academic implications as well as practical implications for practitioners in the food service industry.

• Journal of Practical Engineering Education
• /
• v.16 no.3_spc
• /
• pp.297-308
• /
• 2024

This study explored the application of the NFT-based Learn-and-Earn model in metaverse vocational education and training. Through expert interviews, Delphi analysis, and AHP analysis, the study evaluated considerations and importance of L&E model operation, NFT technology application, course history and certification management, teaching media copyright management, and platform-related issues. Based on the results, the study suggested the need for performance measurement, infrastructure establishment, institutional arrangement, and ethical issue response when utilizing the L&E model.

• Journal of Forest and Environmental Science
• /
• v.40 no.1
• /
• pp.35-42
• /
• 2024

The Japanese larch (Larix kaempferi [Lamb.] Carriere) is a major timber species in Korea. However, studies on bucking rates and merchantable logs of this species are insufficient in South Korea. To bridge these gaps, in this study, the bucking rate of Japanese larch (Larix kaempferi [Lamb.] Carriere) was computed and the number of long logs and merchantable log volumes were analyzed. Sample trees were bucked according to the log grade for trading, and collected from a forest field in Gangwon Province. The bucking rate of all Japanese larch logs was >89%. The highly profitable 2-4 logs of 3.6 m length from trees with ≤30 cm diameter at breast height (DBH) and 5-6 logs with ≥34 cm DBH were produced. The bucking rate of long logs was >84%; thus, Japanese larch was found to be suitable for the supply of high-grade timber. Additionally, to follow reasonable wood supply plans, merchantable volume tables were offered based on 3.6 m-long number of logs and small-end diameter classes. Understanding the proportion of merchantable log volumes, bucking rates, and the number of long and short logs has large-scale applications in practical forestry.

• International Journal of Computer Science & Network Security
• /
• v.24 no.9
• /
• pp.77-84
• /
• 2024

Emotional health is important for overall health, and those who are experiencing difficulties should seek professional help. However, the social stigma associated with emotional health, as well as the influence of cultural beliefs, prevent many people from seeking help. This makes early detection difficult, which is critical for such health issues. It would be extremely beneficial if they could assess their emotional state and express their thoughts without prejudices. On the market, there are emotional health apps. However, there was little to no evidence-based information on their quality. Hence, this study was conducted in order to provide evidence-based quality in emotional health mobile apps. Eleven functionality task scenarios were used to assess functional quality, while a System Usability Scale test (n=20) was used to assess usability, customer acceptability, learnability, and satisfaction. The findings show that the app for emotional health management is highly efficient and effective, with a high level of user satisfaction. This contributes to the creation of an app that will be useful and practical for people experiencing early-stage emotional health issues, as well as related stakeholders, in order to manage early-stage emotional health issues.