Comparative analysis of the development history of sports social organizations in China, Japan and South Korea from multiple perspectives, in order to provide reference suggestions for solving the existing problems of the development of sports social organizations in China as well as for the sustainable development in the future. This paper explores the optimization path of sports social organizations in China by using the literature method and comparative analysis method. The study finds that the current development of sports social organizations in Japan and South Korea is characterized by independence and autonomy, a relatively rich number and variety of organizations, mutual separation of powers and responsibilities between government agencies and social organizations, and autonomous operation and efficient governance of sports social organizations. The development of sports social organizations in China has reached a new level since the founding of New China, and the Party’s attention to and support for their development has been increasing, but China still has deficiencies in the number of organizations, organizational capacity, and policy system. The study concludes that Japan and South Korea have three development conditions for sports social organizations: a socially oriented governance system, a more complete policy and regulation system, and a standardized and efficient financial support system. The study concludes that the prosperity of sports social organizations is crucial in building a strong sports nation at the present time. Combining the successful experiences of Japan and South Korea and integrating into China’s national conditions, we strive to build a governance system that combines government and society, construct a diversified financial support system, and improve the policy support system for sports organizations to promote the progress of sports social organizations in China, and open the way for the autonomy and independence of sports social organizations in China, and put the improvement of the governance system of sports social organizations on the agenda.

Measuring the performance of healthcare organizations has become a crucial yet challenging task, which is the focus of this study. The paper’s primary goal is to identify the key factors that shape healthcare organizations’ performance management systems in Serbia, which can serve as useful guidelines for implementing sustainable solutions. Additionally, the aim is to emphasize the importance of a broad implementation of performance measurement systems to facilitate strategy implementation and enhance organizational effectiveness. The empirical research involved an online survey of 280 respondents, including managers, executives, and operational staff from both private and public healthcare organizations in Serbia. Statistical analysis was conducted using SPSS 20. The study identifies key challenges, including the lack of a developed performance measurement system, weak support from information and management systems for performance improvement, and an organizational structure that does not support performance enhancement. Furthermore, it has been found that a deeper understanding of the essence of measurement significantly contributes to identifying problems in its application in the healthcare sector. It was also observed that the more challenges identified in the measurement process, the less favourable the perception of the flexibility and adaptability of the system.

This study investigates the roles of government and non-governmental organizations (NGOs) in constructing permanent housing for disaster-affected communities in Cianjur Regency following the November 2022 earthquake. Employing a qualitative methodology, the research utilizes in-depth interviews and field observations involving local governments, NGOs, and disaster survivors. The findings highlight the government’s central role in policy formulation, budget allocation, and coordination of housing development, while NGOs contribute through community empowerment, logistical support, and ensuring participatory planning. Challenges in collaboration, such as differing objectives and resource constraints, underscore the need for enhanced synergy. The study concludes that effective partnerships among the government, NGOs, and the community can expedite the development of sustainable, safe housing tailored to local needs. Emphasis on community empowerment and integrated resource management enhances resilience to future disasters. Success hinges on strong coordination, proactive challenge management, and inclusive stakeholder engagement throughout the recovery process.

We present an interdisciplinary exploration of technostress in knowledge-intensive organizations, including both business and healthcare settings, and its impact on a healthy working life. Technostress, a contemporary form of stress induced by information and communication technology, is associated with reduced job satisfaction, diminished organizational commitment, and adverse patient care outcomes. This article aims to construct an innovative framework, called The Integrated Technostress Resilience Framework, designed to mitigate technostress and promote continuous learning within dynamic organizational contexts. In this perspective article we incorporate a socio-technical systems approach to emphasize the complex interplay between technological and social factors in organizational settings. The proposed framework is expected to provide valuable insights into the role of transparency in digital technology utilization, with the aim of mitigating technostress. Furthermore, it seeks to extend information systems theory, particularly the Technology Acceptance Model, by offering a more nuanced understanding of technology adoption and use. Our conclusion includes considerations for the design and implementation of information systems aimed at fostering resilience and adaptability in organizations undergoing rapid technological change.

Young people are a traditional risk group for radicalization and involvement in protest and extremist activities. The relevance of this topic is due to the growing threat of youth radicalization, the expansion of the activities of extremist organizations, and the need to organize high-quality preventive work in educational organizations at various levels. The article provides an overview of research on the topic under consideration and also presents the results of a series of surveys in general educational institutions and organizations of secondary vocational education (n = 11,052), universities (n = 3966) located in the Arctic zone of the Russian Federation. The results of the study on aspects of students’ ideas about extremism are presented in terms of assessing their own knowledge about extremism, the presence/absence of radically minded people around them, determining the degree of threat from the activities of extremist groups for themselves and their social environment, and identifying approaches to preventing the growth of extremism in society. Conclusions are drawn about the need to improve preventive work models in educational organizations towards a targeted (group) approach.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.