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This study analysed the social situation in Korea caused by the Corona pandemic, as shown in YouTube videos between January 2020 when the Corona pandemic began in Korea and December 2021, about two years later, along with its characteristics. The aim of the study was to derive lessons for future quarantine policies. First, the two-year period was divided into three phases in consideration of trends in the number of Corona patients. Then, for each period, YouTube videos created during this period were analysed using text network analysis and the system dynamics analysis method, both of which represent a kind of big data analysis method. This analysis method is new, and is highly significant in terms of research methodology. In addition, the analysis results provide important policy implications. One important policy meaning is the derivation of the reinforcing loop and balancing loop that policymakers should consider for each period.

The aim of this study is to analyse the roles played by medical personnel such as doctors and nurses in Korea in the context of Covid, and to suggest directions for responding to possible pandemics in the future from the perspective of the roles of medical personnel. For this analysis, Korean YouTube video contents were analysed; the analysis methods employed were text-mining and ego network analysis. The analysis target period was 2020, the year in which the Corona pandemic was declared, and 2021, one year after the declaration of the pandemic. As a result of the analysis six themes, derived from the perspective of the role of medical professionals, were selected in respect of each year. In the future, the Korean medical policy decision-making process should aim to reflect these topics.

This study was conducted in order to ascertain what role government and individuals should play in the event of a pandemic such as Coronavirus occurring in Korea in the future, using information deriving from news articles available at the Bigkinds news portal site in Korea. The analysis period ran from 11 March 2020, when the pandemic was declared by the World Health Organization, to 31 January 2023, almost three years later. Text mining analysis was conducted on all the articles, as a result of which six important roles that individuals should play, and ten roles that government should play, in a pandemic situation were suggested.

The aim of this study is to increase the effectiveness of Korean aid provision for countries in the Middle East and North Africa (MENA) region, which are important ODA recipient countries from a Korean perspective, but have not been studied extensively in Korea. Although there are twenty countries in the MENA region, in this study five countries, Egypt, Algeria, Libya, Iran and Iraq, which are considered important from a Korean perspective, are targeted. The analysis includes an examination of the regional characteristics and the long-term development plans of these five countries, and the size and contents of aid projects provided by Korea to these countries. It is expected that as a result of this analysis Korea will be able to carry out aid projects involving these countries more effectively in the future.

This study aims to evaluate the status of the partnerships with important international organizations that Korea employs in operating its foreign aid projects from a humanitarian point of view. On the basis of this information, Korea intends to seek ways of effectively supporting underdeveloped countries through future co-operation with these organizations. The main international organizations analyzed are the World Food Programmer (WFP), the United Nations Children’s Fund (UNICEF), the United Nations High Commissioner for Refugees (UNHCR), the World Health Organization (WHO), the United Nations Development Program (UNDP), the (United Nations) Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), the Food and Agriculture Organization (FAO), the International Committee of the Red Cross (ICRC) and the Office for the Coordination of Humanitarian Affairs (OCHA). These international organizations support underdeveloped countries through co-operative relationships not only with Korea but also with important donor countries of the OECD. This study focuses on establishing the factors that Korea needs to consider when providing humanitarian aid in the future to underdeveloped countries via such international organizations.

This study is based on a social network analysis of newspaper articles relating to the Corona pandemic contained in the African daily newspaper African News. The aim of the study is to analyse what life-changes have been brought about in Africa as a result of the Corona pandemic, so that this information can be used in official development assistance policies for Africa. For this purpose, a text network analysis method was used. As a result of the analysis, the life-changes experienced by African residents as a consequence of the Corona pandemic are summarized into five broad categories. The five topics are: the Government’s countermeasures against the virus; recovery measures in African countries; measures relating to personal health; Government measures relating to schools; and an increase in the number of deaths from Coronavirus. After the Coronavirus pandemic, the ​​aid that should be provided most urgently to Africa is in the fields of health and education. It is hoped that aid donors will refer to the points found in this analysis and reflect them in their aid policy.

Korea is one of the leading countries across the world to have promoted education through ICT using smart school practices. Using the Analytical Hierarchy Process (AHP) method, this paper aims to identify the determinants affecting the success of the smart schooling system in Korea; prioritise the indicators necessary for the success of the smart schooling system in terms of weight; and provide policy implications for policymakers and practitioners involved in smart school and education policy. The indicator teacher dedication has the greatest weight score, followed by attitudes toward e-learning and IT, meaning that the individual involved in the smart schooling system's activities should be viewed as more significant than any other indication.

The purpose of this study is to investigate the causal relationships among the key educational factors that affect adolescent happiness and to propose policy implications for OECD countries to increase their levels of adolescent happiness. The HSBC score of adolescent happiness in OECD countries was chosen as an indicator, and a number of independent variables such as per capita GDP and per capita educational expenditure amount were included in the subject of analysis. For the analysis, the QCA (Qualitative Comparative Analysis) method was used. The use of QCA has been rarely reported in adolescents’ happiness studies, and are likely to be conceptual and paradigmatic challenges to its adoption in some settings. According to the findings, there are three key factors that contribute to adolescents' high levels of happiness in OECD nations: TEPC*GDP*PUPTEA, tee*GDP*PRIVATEXP, and tee*tepc*gdp*privatexp. In other words, while a number of further steps are required to produce a more parsimonious formulation, the solution in this study suggests six configurations and three prime implicants. The first prime implicant is TEPC(high total per capita expenditure on education)*GDP(high per capita gdp)*PUPTEA(high ratio of students to teaching staff). The second implicant is tee(low total expenditure on education)*GDP(high per capita gdp)*PRIVATEXP(high ratio of private source expenditure on education to gdp). Finally, the third implicant is tee(low total expenditure on education)*tepc(low total per capita expenditure on education)*gdp(low per capita gdp)*privatexp(low ratio of private source expenditure on education to gdp). It is crucial to emphasise that the data reported in this research are simply illustrative and should be examined in a broader context.Alternative causal configurations are acceptable for the complexity of adolescents' happiness, rather than being a limitation of QCA.

This paper aims to discover the characteristics of the ODA donor countries which conduct ODA projects effectively and to induce the less effective ODA donor countries to benchmark them so that all ODA donor countries can implement ODA projects effectively and also help all the recipient countries eventually to end their poverties. As time goes on, the size of ODA increases across the glove and however, there has little studies on how to effectively implement ODA projects, in particular. What should be noted in the field of ODA studies is that each ODA donor country has its own political, social and policy-related system, resulting in that only one model for benchmarking the effective ODA donor countries is not easy to be constructed. In other words, there should be more than one model to be benchmarked on the part of less effective countries. Against this background, this study attempts to analyse 23 ODA donor countries to find the configurations of the factors affecting the effectiveness of ODA projects. The analysis shows that two combinations of the factors associated with the effectiveness of the ODA projects were found. The first type combination, in which Canada is included, is that the capacity for innovation of government is high, the willingness to delegate power to lower tier is high, the size of the assistance per recipient country is relatively big, the size of the assistance per agency, which is involved in ODA projects, is small, the size of the assistance per ODA project is small. The second type combinations, in which Denmark included, is that the capacity for innovation is high, the willingness to delegate power is high, the size of the assistance per ODA agency is high, the size of the assistance per recipient country is small and the size of the assistance per ODA project is small. It is suggested that less effective countries regarding ODA project implementation should benchmark one of the two types so that they could be effective in terms of ODA projects implementation.

본 연구는 한국의 ODA 공여액 규모가 2017년에 약 2조 7천억원 수준으로 커져 가는 상황에서 ODA 사업에 대한 효율적 관리 필요성을 인식하고 ODA 사업의 효과성을 강화하기 위한 방안을 모색하고자 하는 것이 목적이다. 이를 위해서 ODA 사업 추진과정을 중요한 영향요인들이 포함된 인과지도 형태로 세분화하고 추진과정에 영향을 미치는 중요한 영향요인들을 활용하여 정책 시뮬레이션을 수행한다. 이러한 과정을 거쳐서 첫째, ODA 사업의 효과성 제고를 위해서 관련되는 중요한 영향요인들이 무엇인지를 규명하고, 둘째, 중요한 영향요인들에 대한 정책시뮬레이션을 통하여 향후 ODA 사업의 효과성이 어떻게 달라질 수 있는 지를 예측하며, 셋째, ODA 사업추진과 관련된 상황이 변동될 수 있음을 감안하여 민감도 분석을 통하여 ODA 사업의 효과성에 대한 향후 추이를 예측해 보고자 한다. 분석결과, ODA 사업의 중요한 독립변수들의 수준 변화 시나리오가 ODA 목표달성이라는 종속변수에 미치는 변화정도를 추정할 수 있었다.

이 연구는 지금까지 많은 연구가 이루어지지 않았던 커뮤니티 웰빙을 구성하는 조건들의 결합형태를 탐색해 보고자 하는데 목적이 있다. 이를 위해서 커뮤니티 웰빙수준을 측정하기 위해 설계된 척도를 사용하여 수집된 설문지 결과를 이용하였다. 17개 도 지역의 커뮤니티 웰빙 수준을 개인들의 주관적 평가수준과 자기가 살고 있는 지역이 가지고 있다고 느끼는 수준으로 나누어서 두 조건을 다 충족하는 도 단위 지역이 어디인지를 먼저 찾고자 하였다. 그 다음, 이러한 웰빙조건을 갖춘 지역에는 어떤 영향요인들이 관련되어 있는 지를 질적 비교방법 (QCA) 방법을 통하여 분석하였다. 이를 통하여 웰빙조건을 갖춘 커뮤니티는 우리나라의 경우 어떤 곳이 포함되는 지를 알 수 있고, 더 나아가서 이러한 지역을 결정하는 영향요인들의 결합형태는 어떠한가를 발견할 수 있었다.

This paper attempts to identify the determinants affecting the success of the smart schooling system in Korea which is one of the leading countries across the world in terms of education through ICT, to prioritize the indicators necessary for the success of the smart schooling system in terms of weight, using the Analytical Hierarchy Process (AHP) method, and to put forward policy implications for policymakers and practitioners involved in smart school and education policy. The AHP analysis shows that the indicator teacher’s commitment has the highest weight score, followed by attitudes towards e-learning and IT, implying that the individual involved in the activities of the smart schooling system should be regarded as more important than any other indicators.

The aim of this study is to construct a causal relationship model explaining the relationships between social policy factors and national competitiveness and national happiness; and to analyse how the former affect the latter as final dependent variables. In doing this, the study employs data for OECD member countries. Research regarding the determinants affecting national competitiveness and people’s happiness has tended to focus mainly on personal or collective characteristics such as age, gender, economic infrastructure, etc. As a result, social policy factors, including welfare budget, unemployment support budget and income inequality, have rarely been addressed in the analysis of determinants affecting national competitiveness or happiness, which is regarded as the final policy aim to be achieved by government. In particular, there has been little academic research utilizing OECD database statistics on social policy indicators. Against this background, this study uses the Structural Equation Modeling approach (SEM) to identify the direct and indirect effects of social policy factors on national competitiveness and happiness, and puts forward policy suggestions for attaining these two great goals of social policy.

This study was conducted in order to investigate the relationships between different factors affecting educational competitiveness, which is crucial to enhancing national competitiveness in every country, and to put forward policy implications whereby each country may raise the level of its educational competitiveness. PISA score was selected as an indicator representing the educational competitiveness of 22 OECD countries, and this included some independent variables, such as per capita GDP, total public expenditure on education as a percentage of GDP, and total per capita public expenditure on education (US dollars), affecting educational competitiveness. We employed the fuzzy set analysis method (FS/QCA) to analyze the complex causal relationships among the factors affecting educational competitiveness. The research results show that there are three significant combinations of variables affecting educational competitiveness (PISA score). Model 1 is a configuration of four variables (high total expenditure on education as a percentage of GDP, high total per capita expenditure on education, high ratio of private-source expenditure on education to GDP, and high GDP), and includes Netherlands, Finland, Australia, and Ireland. Model 2 is a configuration of five variables (low total expenditure on education, low total per capita expenditure on education, low ration of students to teaching staff, low private-source expenditure on education, and low GDP, and includes Poland. Model 3 is a configuration of five variables (low total expenditure on education, low total per capita expenditure on education, high private-source expenditure on education, high ratio of students to teaching staff, and high GDP), and includes Japan. Finally, the study suggests that each country should endeavour to enhance its own educational competitiveness, considering how the factors associated with this relate to each other.

This study aims to investigate the causal relationships among the key factors related to education that affect the happiness of adolescents, to find combinations of conditions explaining adolescents’ happiness in OECD countries, and to put forward policy implications whereby OECD countries may raise their levels of adolescent happiness. The HBSC (Health Behaviour in School-aged Children) score of adolescents of OECD countries was selected as an indicator for happiness, and some independent variables such as per capita GDP, per capita educational expenditure amount were included in the subject of analysis. QCA (Qualitative Comparative Analysis) method was employed for the analysis. Research results show that there are six configurations and three selected prime implicants explaining the high happiness score of adolescents in OECD countries. Three prime implicants are TEPC*GDP*PUPTEA, tee*GDP*PRIVATEXP, and tee*tepc*gdp*privatexp. In other words, while there are a number of further steps required to obtain a more parsimonious expression, in this research the suggestions posed by the solution are six configurations and three prime implicants explaining adolescents’ happiness in OECD countries. The first prime implicant is a combination of TEPC(high total per capita expenditure on education)*GDP(high per capita gdp)*PUPTEA(high ratio of students to teaching staff). The second implicant is a combination of tee(low total expenditure on education)*GDP(high per capita gdp)*PRIVATEXP(high ratio of private source expenditure on education to gdp). Finally, the third implicant is a combination of tee(low total expenditure on education)*tepc(low total per capita expenditure on education)*gdp(low per capita gdp)*privatexp(low ratio of private source expenditure on education to gdp). It is important to note that the results presented in this paper are illustrative only and need to be investigated in a more comprehensive perspective. Rather than being a limitation of QCA, consideration of alternative causal configurations are appropriate for the complexity of adolescents’ happiness.

In Korea, a policy of encouraging the production and distribution of local food has been implemented in order to resolve the problems rural societies are facing. The policy has focused not only on ensuring profits for farmers, but also on recovering the communal character of rural areas and restoring their living foundations. Wanju-gun (similar in size to a US county) in Jeollabuk-do Province is today regarded as one of the most successful examples in terms of policy implementation and achievement. Wanju has been supporting local food as a core business, and is launching various activities such as reforming local farming toward a small quantity batch production system, revitalizing farmers’ education, and opening up direct local food markets. Against this background, this study aims to identify the success factors of the local food movement in Wanju-gun, and to discuss measures for spreading this movement further. Data on the area of Wanju, homepage websites and news reports were employed to analyze the success factors of Wanju's local food movement.