• Asian Journal for Public Opinion Research
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• v.11 no.2
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• pp.163-178
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• 2023

Individuals have been under more stress since the COVID-19 pandemic began than they were before the pandemic. While social support is a known stress buffer among the general population, its impact on stress among vulnerable populations, such as immigrants and those living in rural areas, has received little attention in the context of South Korea. Accordingly, we examined the relationship between different types of social support and COVID-19 stress among young adult immigrants based on where they live (rural vs. urban). We conducted a survey of 300 young adult immigrants aged 25-34 years and analyzed the results. The dependent variable was COVID-19 stress, and the independent variables were four types of social support: emotional, appraisal, instrumental, and informational. We discovered that young adult immigrants in rural areas perceived higher-level social supportin all aspects compared with those in urban areas. Furthermore, social support was not related to COVID-19 stress in urban areas, while appraisal support was positively and informational support was negatively related to COVID-19 stress in rural areas. Our findings suggest that a contextualized understanding of social support is critical to understanding COVID-related stress during the COVID-19 pandemic.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.499-512
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• 2022

Intervention measures have been implemented worldwide to reduce the spread of the COVID-19 outbreak. The COVID-19 outbreak has occured in several waves of infection, so this paper is divided into three groups, namely those countries who have passed the pandemic period, those countries who are still experiencing a single-wave pandemic, and those countries who are experiencing a multi-wave pandemic. The purpose of this study is to develop a multi-wave Richards model with several changepoint detection methods so as to obtain more accurate prediction results, especially for the multi-wave case. We investigated epidemiological trends in different countries from January 2020 to October 2021 to determine the temporal changes during the epidemic with respect to the intervention strategy used. In this article, we adjust the daily cumulative epidemiological data for COVID-19 using the logistic growth model and the multi-wave Richards curve development model. The changepoint detection methods used include the interpolation method, the Pruned Exact Linear Time (PELT) method, and the Binary Segmentation (BS) method. The results of the analysis using 9 countries show that the Richards model development can be used to analyze multi-wave data using changepoint detection so that the initial data used for prediction on the last wave can be determined precisely. The changepoint used is the coincident changepoint generated by the PELT and BS methods. The interpolation method is only used to find out how many pandemic waves have occurred in given a country. Several waves have been identified and can better describe the data. Our results can find the peak of the pandemic and when it will end in each country, both for a single-wave pandemic and a multi-wave pandemic.

• Journal of Integrative Natural Science
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• v.13 no.4
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• pp.158-169
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• 2020

Modern people live in the age of plastics. It has been widely used due to its easy molding processing, mass production, and excellent durability. However, over-produced plastics for convenience cause plastic disasters and adversely affect the ecosystem. Since the COVID-19 outbreak, the use of single-use plastic waste due to the use of delivery services has increased. The COVID-19 pandemic has caused a plastic pandemic. Currently, domestic recycling policies depend only on recycling collection companies and market prices of recyclable resources. This paper confirms whether the outbreak of COVID-19 has affected the price of plastic waste. It also shows that the price of plastic waste is more unstable than metals with a high recycling rate. This urges businesses to share the cost of recycling on plastic waste, no longer being dependent on market prices for recyclable resources.

• Clinical and Experimental Pediatrics
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• v.65 no.4
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• pp.167-171
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• 2022

In the era of the coronavirus disease 2019 (COVID-19) pandemic, countries worldwide have implemented several nonpharmaceutical interventions (NPIs) to contain its spread before vaccines and treatments were developed. NPIs included social distancing, mask wearing, intensive contact tracing and isolation, and sanitization. In addition to their effectiveness at preventing the rapid spread of COVID-19, NPIs have caused secondary changes in the epidemiology of other infectious diseases. In Korea, various NPI stages have been implemented since the first confirmed case of COVID-19 on January 20, 2020. This review, based on a PubMed database search, shows the impact of NPIs on several infectious diseases other than severe acute respiratory syndrome coronavirus 2 in the COVID-19 pandemic era in Korea.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.31-42
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• 2024

Today, news avoidance has become an inevitable trend, particularly exacerbated since the outbreak of the COVID-19 pandemic in 2020. To delve deeper into the shifting tendencies of news consumers towards news avoidance and unveil the motivations behind this avoidance, this study recruited 500 Chinese news consumers aged between 20 and 60 years old, employing survey questionnaires as the research method. Through an indepth examination of their news consumption behavior at different stages of the COVID-19 pandemic, we discovered that individuals' risk perceptions and efficacy beliefs significantly influence their patterns of news consumption. Furthermore, we identified negative emotions, information overload, and media distrust as the primary reasons for news avoidance among Chinese news consumers during the COVID-19 crisis. These findings Not only provide crucial insights into understanding the dynamics of news consumption behavior but also offer valuable reference points for the news industry to better fulfill its role and value during crises in the future.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.49-63
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• 2024

Information behavior played a significant role in minimizing the risks of the COVID-19 pandemic. When faced with such a situation, an individual needs information for decision-making and in order to determine the best course of action relating to their health. This study aims to explore information behavior during each phase of the COVID-19 pandemic in Indonesia, which is known for its close-knit collective culture. A sensemaking approach is used, which emphasizes the process individuals go through to understand their situation and give meaning to the information they are getting from their environment. Data was collected through in-depth interviews with 10 participants to obtain a description of their information behaviors during the pandemic. Data analysis was carried out using open, axial, and selective coding. We propose a sensemaking-based information behavior strategy framework for mitigating risk and reducing ongoing health crises. Changes in information behavior strategies, including search, prevention, and restriction of information exposure, were random at the beginning of the pandemic, but became more regular in later phases. This was influenced by the "knowledge gap fulfillment" and "use of local knowledge" among the participants throughout the pandemic. In conclusion, the participants developed a sensemaking process including an understanding of the pandemic situation and the risks that they faced. They used a number of information behavior strategies to prevent transmission, and their perception of the risks changed across the course of the pandemic, up til the situation began to be considered back to normal again in Indonesia.

• The Journal of Information Systems
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• v.30 no.3
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• pp.21-45
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• 2021

Purpose This paper analyzed the impacts of domestic stock market by a global pandemic such as COVID-19. We investigated how the overall pattern of the stock market changed due to the impact of the COVID-19 pandemic. In particular, we analyzed in depth the pattern of stock price, as well, tried to find what factors affect on stock market index(KOSPI) in the healthcare industry due to the COVID-19 pandemic. Design/methodology/approach We built a data warehouse from the databases in various industrial and economic fields to analyze the changes in the KOSPI due to COVID-19, particularly, the changes in the healthcare industry centered on bio-medicine. We collected daily stock price data of the KOSPI centered on the KOSPI-200 about two years before and one year after the outbreak of COVID-19. In addition, we also collected various news related to COVID-19 from the stock market by applying text mining techniques. We designed four experimental data sets to develop decision tree-based prediction models. Findings All prediction models from the four data sets showed the significant predictive power with explainable decision tree models. In addition, we derived significant 10 to 14 decision rules for each prediction model. The experimental results showed that the decision rules were enough to explain the domestic healthcare stock market patterns for before and after COVID-19.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1027-1033
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• 2020

This study intends to improve job performance during the Covid-19 pandemic at startup companies in Indonesia. In this study, the variables tested were job satisfaction, job innovation, Indonesian culture control, and job performance. Increasing job performance is deemed necessary in facing the economic crisis caused by the Covid-19 pandemic. Job innovation, job satisfaction, and culture control are deemed necessary in improving job performance. The population of this study are managers of start-up companies in Jakarta, Banten, and West Java. This research data obtained by distributing questionnaires to startup managers. This is a quantitative study with primary data. The sample technique used was purposive sampling. Structural Equation Model using Partial Least Square statistical software was used to analyze data. The results of this study indicate a change in the pattern of work performed by startup companies in running their business. Before the Covid-19 pandemic, employees worked in offices for seven hours, but after this pandemic, they change work patterns, moving them to work from home. Working from home requires companies to exercise better control and leadership patterns so that employees can work comfortably.

• Asian Journal for Public Opinion Research
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• v.11 no.3
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• pp.201-233
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• 2023

Persons with disabilities (PwD) are believed to be a group that had a greater risk during the pandemic. While PwD are vulnerable to the spread of COVID-19 due to their high dependence on physical contact, a series of policies restricting public movement during the pandemic had the potential to place PwD in increasingly marginalized situations. This situation reinforces the urgency of crisis communication as one of the critical parts of the COVID-19 response to ensure that all levels and groups of society can accept and understand the flow of information. Using a qualitative approach, this research was conducted through in-depth interviews with PwD age 17-50 in the city of Makassar, Indonesia. The results of this study suggest that crisis communication during the pandemic should involve participatory communication, which focuses on collaboration with empowerment. The PwD communities need to be actively engaged during the communication process of a pandemic crisis to ensure that inclusiveness is always taken into account. During the distribution of information, the relevant health officers or the government at the regional level need to carry out more frequent socialization and special services for PwD based on the characteristics of their disabilities.

• Asia pacific journal of information systems
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• v.31 no.1
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• pp.76-101
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• 2021

Digitalization and digital transformations have metamorphized the face of Financial Inclusion globally, more so, in cash obsessed economies like India. The purpose of our study is to empirically analyze the users' intention to adopt digital payment systems, post Demonetisation, during the COVID-19 pandemic in India. The conceptual framework for the study is based on the Unified Theory of Acceptance and Use of Technology (UTAUT) adoption model with added operationalized constructs of Perceived Risk and Stickiness to use Cash. A total of 326 respondents were surveyed using a pre-tested questionnaire during the Nationwide Lockdown 3.0 in India. These responses were analyzed using Partial Least Squares - Structural Equation Modelling (PLS-SEM) technique. The findings of the study revealed that performance expectancy and facilitating conditions directly influence the intention of individuals to use digital payment systems, whereas the effect of perceived ease of use on digital payment systems is mediated through the attitude towards the digital payment systems during COVID-19 pandemic situation. Implications of the proposed adoption model are discussed. This will enable the other developing economies to formulate a digital ecosystem, that is here to stay even after the pandemic.