• The Korean Journal of Food & Health Convergence
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• v.8 no.3
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• pp.1-9
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• 2022

Purpose-Meat plays an important role in the Chinese daily diet, however, due to the spread of COVID-19, food supply and safety have become a major concern. The safety and health features of chilled fresh meat have attracted the attention of consumers. To study consumers' purchasing behavior and willingness to pay for chilled meat under the influence of the epidemic. Research methodology- The data were obtained by questionnaire survey, major issues include consumers' meat consumption habits in the wake of the COVID-19 and their awareness of meat product quality labels. In addition, the gender, age, family income, and other basic personal information of the interviewees were also counted. Based on the binary Logit regression method, we study consumers' purchasing behavior and willingness to pay for chilled meat under different demographic characteristics. Results-The results showed that brand and quality certification are important factors influencing purchases. In addition, the presence of children under the age of 12 in the household and the level of income and education also influence consumers' purchase intention of the chilled fresh meat. However, mart promotions and city ratings can significantly lower consumers' propensity to buy the chilled fresh meat. Apart from this, such factors as gender, age, and living conditions have no significant influence on consumers' purchase of chilled fresh meat.

• Journal of Korean Library and Information Science Society
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• v.51 no.3
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• pp.251-279
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• 2020

This study noted the recent impact of Coronavirus Disease-19 (Corona 19) on the environment surrounding the library, and investigated the libraries' response activities. In addition, related issues on news media and social media were detected based on text mining techniques to engage environmental changes surrounding the library. Key issues were derived from 1,852 news reports on the library related to the Corona 19 situation and 227,983 tweets related to the library during the Corona 19 epidemic. Through this, implications were derived: prolonged 'Untact' situations, increased e-book lending, improved expectations for online services and librarians, and re-conceptualized library space. In addition, the direction of future services was discussed by selecting representative examples of library services provided in the non-face-to-face (untact) situation and dividing them into books, services, and spaces.

• The Korea Journal of Herbology
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• v.36 no.5
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• pp.1-14
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• 2021

Objectives : From January 2020, when the first confirmed case of COVID-19 in Korea, the use of health information using the Internet is expected to increase. It is expected that there will be a significant change in the general public's interest in Korean herbal medicines for health care. Therefore, in this study, we tried to confirm the change in the search trend of Korean herbal medicines after the COVID-19 epidemic. Methods : Using the "Naver DataLab (http://datalab.naver.com)" service of a Korean portal site Naver, search volume was investigated with 606 Korean herbal medicines as keywords. The search period was from January 2020, right after the onset of COVID-19, to June 2021. The search results were sorted by the peak search volume and the total search volume. Results : 'Cheonsangap (천산갑, 穿山甲, Manitis Squama)' was the most searched Korean herbal medicine in the peak search volume and total search volume with least bias. Conclusions : The problem of supply and demand of Korean herbal medicines of high public interest was identified. Broadcasting and media exposure were the factors that had a big impact on the search volume for Korean herbal medicines. As it was confirmed that the search volume for Korean herbal medicines increased rapidly due to media exposure, it is necessary to provide correct information about Korean herbal medicines, improve public awareness, and manage stable supply and demand based on continuous search trend monitoring.

• Journal of Platform Technology
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• v.8 no.3
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• pp.22-29
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• 2020

The 4th industrial revolution is progressing by country as a mega trend that leads various technological convergence directions in the social and economic fields from the initial simple manufacturing innovation. The epidemic of infectious diseases such as COVID-19 is shifting digital-centered non-face-to-face business from economic operation, and the use of AI and big data technology for personalized services is essential to spread online. In this paper, we analyze cases focusing on the application of artificial intelligence technology, which is a key technology for the effective implementation of the digital new deal promoted by the government, as well as the major technological characteristics of the 4th industrial revolution and describe the use cases in the field of disaster response. As a disaster response use case, AI assistants suggest appropriate countermeasures according to the status of the reporter in an emergency call. To this end, AI assistants provide speech recognition data-based analysis and disaster classification of converted text for adaptive response.

• The Journal of Bigdata
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• v.5 no.2
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• pp.187-199
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• 2020

The World Health Organization declared COVID-19 a pandemic on March 11. South Korea recorded 27,000 cases of the coronavirus illness, and more than 50 million coronavirus cases were confirmed all over the world. An epidemiological investigation becomes important once again due to the spread of COVID-19 infections. However, there were a number of confirmed coronavirus cases from Deagu and Gyeongbuk. Limitations of the epidemiological investigation methods were recognized. The Korea Disease Control and Prevention Agency developed the Epidemiological Investigation Support System(EISS) to utilize the smart city data hub technology and utilized the system in the epidemiological investigation. As a part of EISS, The proposed system is big-data bsed epidemiological investigation support system processing mobile network data. The established system is the epidemiological investigation support system based on big data to process mobile carriers' big data. Processing abnormal values of mobile carriers' data which was impossible with existing staff or creating hotspot regions where more than two people were in contact with an infected person were realized. As a result, our system processes outlier of mobile network data in 30 seconds, while processes hotspot around in 10 minutes. as a first time to adapt and support bigdata system into epidemiological investigation, our system proposes the practical utilizability of big-data system into epidemiological investigation.

• Korea Journal of Hospital Management
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• v.28 no.3
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• pp.15-26
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• 2023

Purposes: Evaluate the level of mental health of administrative workers in medical institutions during the COVID-19 epidemic, and check the relationship. Methodology: It targeted 183 administrative workers at medical institutions located in Jeollabuk-do. The data survey method used a self-filled questionnaire, and the data collection period was 30 days from November 16, 2021 to December 16, 2021. A comparative analysis was conducted to find out the correlation between the subjects' biological factors, environmental factors, lifestyle factors, job related factors and depression, Post Traumatic Stress Disorder, and job stress. Findings: As an influencing factor of depression, it was found that the longer the working period, the higher the depression, and the higher the position, job satisfaction, and the total amount of smoking, the lower the depression. Due to the effect on Post Traumatic Stress Disorder, the higher the total amount of smoking, the higher the Post Traumatic Stress Disorder after effects, and the higher the organizational commitment and job satisfaction, the lower the Post Traumatic Stress Disorder aftereffects. It was found that organizational commitment had the highest influence on Post Traumatic Stress Disorder. As an influencing factor on job stress, it was found that the higher the job related factors was job satisfaction and organizational commitment, the lower the job stress. Practical Implications: Variables such as moderate physical activity, alcohol consumption, total smoking, working period, position, job satisfaction, and organizational commitment were identified as factors influencing depression, Post Traumatic Stress Disorder, and job stress during the COVID-19 pandemic.

• Journal of Distribution Science
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• v.21 no.8
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• pp.47-55
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• 2023

Purpose: Online meeting is chosen instead of face-to-face conferences as a solution that ensures both effectiveness and legality during times of strong epidemic outbreaks. In the current period, managers can have different types of meeting options for information distribution. This study has examined the effect of past behavior on the managers' intention of organizing online meetings. Research design, data and methodology: Data were collected from a survey with 475 managers and put into SmartPLS 4.0 for analysis. Partial least squares structural equation modeling (PLS-SEM) was employed to test relationships in the research model. Results: The findings indicated that past behavior plays the most critical role in explaining the organizing online meeting intention of managers, followed by attitude and subjective norms. Meanwhile, the perceived behavioral control factor has absolutely no effect on intention in the context of this study. Notably, attitude and subjective norms also remarkably mediated the impact of past behavior on managers' intention. Conclusions: This study has added to the understanding of the meeting organization behavior of managers. Even if the epidemic is under control, the administrators should still organize some meetings in the form of online because it will affect the social perceptions of future behavior and behavioral intention.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.39-52
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• 2021

This study aims to investigate the effect of the coronavirus disease 2019 (COVID-19) epidemic on negative emotions, such as anxiety, depression, fear, and stress, in Korean college students. The study recruited students from J University and conducted interviews across three time points, namely, March 2019, March 2020, and November 2020. For three time points, the participants responded to structured questions about situations they may have encountered and they were asked to summarize their responses. Repeated-measures ANOVAs were performed to examine whether differences exist in negative emotions between time points. Furthermore, polynomial trend analyses were conducted to examine resultant patterns over time. The results revealed that negative emotions displayed significant differences between time points. Moreover, trend analyses revealed a curvilinear pattern, which indicates that negative emotions increased and were then sustained. These findings suggest that negative emotions may continue to become prevalent among college students with the increased impacts of the ongoing COVID-19 pandemic. The study discussed the need for psychological support systems, such as stress management and psychological counseling, for college students.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.81-92
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• 2021

The purpose of this study is to present an approach to the "Digital Health Passport" (DHP), which will be the most important in the change of the travel industry among the sudden environmental changes brought about by COVID-19. To this end, this study reviewed a variety of empirical literature on DHP, and proposed a framework for DHP based on literature review. The framework is composed of travel intention, health information provision intention, and new technology acceptance/adoption of tourists. First, in terms of travel intention, providing information to DHP should not undermine the travel intention of the travelers. It should be possible to facilitate the travelers' enjoyment by using the information provided by the traveler. In addition, there is a need to assure that the data provided by travelers is managed in a reliable way. Second, it is necessary to understand why the travelers want to provide additional personal information (information disclosure), rather than seeing healthcare information only in terms of mandatory information provision. Finally, from the perspective of new technology, it is necessary to understand the intention of travelers to use/adopt DHP. The key implication of this work is that it proposed a DHP framework for realizing the travel bubble to predict and respond to foreign travelers' behaviors.

• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.19-29
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• 2021

To explain the interregional infections in COVID-19, we designed a multi-group compartmental model by applying the SEIQRD model, a compartmental model of a single group. The model is segmented by compartments to account for hidden infections, such as latent periods and asymptomatic cases, and is capable of comparing infection indices and test rates between regions. Through this, it estimated which region was centered during the second wave in August 2020 and the third wave in November 2020. Subgroups were set up in Seoul, Gyeonggi (including Incheon), and a non-metropolitan area. We fit the model to the Ministry of Health and Welfare's data to estimate the average infection index between regions, average rate of rT-PCR test by region, and the expected number of hidden infections by region.