The COVID-19 crisis, which occurred in 2020, brought crisis events back to the attention of scholars. With the increasing frequency of crisis events, the influence of crisis events on stock markets has become more obvious. This paper focuses on the impact of the subprime crisis, the Chinese stock market crash crisis and the COVID-19 crisis on the volatility and risk of the world’s major stock markets. In this paper, we first fit the volatility using EGARCH model and detect asymmetry of volatility. After that, a VaR model is calculated on the basis of EGARCH to measure the impact of the crisis event on the risk of stock markets. This paper finds that the subprime crisis has a significant influence on the risk of the stock market in China, US, South Korea, and Japan. During the COVID-19 crisis, there was little change in the average risk of each country. But at the beginning of the COVID-19 crisis, there was a significant increase in the risk of each country’s stock market. The Chinese stock market crash crisis had a more pronounced effect on the Chinese and Japanese stock markets and a lesser effect on the US and Korean stock markets.

This study explores the application of the co-design approach in participatory planning for the development of Kambo Tourism Village, located at the intersection of urban and rural areas in Indonesia. By combining the Delphi Consensus Method and Analytic Hierarchy Process (AHP), the study successfully identified and prioritized key aspects in the planning process, with a primary focus on local community participation. The results indicate that the co-design approach is effective in creating a masterplan that not only aligns with the needs and aspirations of the community but also supports the sustainability and inclusiveness of tourism village development. AHP results reveal that local community participation was assigned the highest priority with a weight of 0.35, followed by stakeholder collaboration with a weight of 0.27. Community participation not only contributed to the creation of a well-structured tourism village masterplan but also enhanced human resource quality and strengthened stakeholder collaboration. The impact of this participatory planning process includes increased national recognition for Kambo Village, the village’s success in receiving awards, and local economic growth. Moreover, the study identified a gap between the calculated and expected weights in the AHP process, highlighting the complexity of aligning diverse stakeholder perspectives. These findings offer both practical and theoretical contributions and open opportunities for further research to address the challenges of participatory planning in the context of tourism villages.

The purpose of the article is to present the current situation in the rail freight transport in Thailand and the direction of changes in this area. Firstly, Thailand statistics in volume of freight transport by rail and modal share of freight transport have been presented. Afterwards, problems and obstacles in railway operational practices and in using rail transport services have been identified to improve railway system in Thailand and the outcome was assessed in terms of railway capacity and utilization. The findings were used to outline the direction of changes in rail freight transport. The results show that the rail transport capacity in double-track would increase by 48% (at present by 15.5% and as plan by 30%) and the ratio by rail transport to total freight transport would increase from at present by 1.87% to 10% in 2037.

This study delves into the role of pig farming in advancing Sustainable Development Goal (SDG) 8—Decent work and economic growth in Buffalo City, Eastern Cape. The absence of meaningful employment opportunities and genuine economic progress has remained a significant economic obstacle in South Africa for an extended period. Through a mixed-method approach, the study examines the transformative impact of pig farming as an economic avenue in achieving SDG 8. Through interviews and questionnaires with employed individuals engaged in pig farming in Buffalo City, the study further examines pig farming’s vital role as a source of decent work and economic growth. The study reveals inadequate government support and empowerment for pig farming in Buffalo City despite pig farming’s resilience and potential in mitigating socio-economic vulnerabilities and supporting community’s livelihoods. To enhance pig farming initiatives, this study recommends government’s prioritization of an enabling environment and empowerment measures for the thriving of pig farming in Buffalo City. By facilitating supportive policies and infrastructures, the government can empower locals in Buffalo City to leverage pig farming’s potential in achieving SDG 8.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.