Objective/Aim: In the context of a constantly changing legislative environment and the necessity for professionals to develop their skills, the research focuses on identifying effective methods and tools that facilitate efficient learning and professional development in the field of labour law. This study aimed to propose a pedagogical technology for the preparation and training of specialists in the field of labour law and to assess the effectiveness of the training based on the specified technology. Method: The study involved 124 participants, with 63 in the experimental group and 61 in the control group. Statistical analysis was performed using Microsoft Excel. The student’s t-test indicated significant improvements in the experimental group’s training effectiveness, confirming the proposed pedagogical technology’s efficacy. Results: Consequently, implementing training and education technology for specialists in the labour law field was proposed to enhance the indicators. The criteria for the preparation of specialists in the field of labour law were delineated, including knowledge of labour legislation, consulting and support skills, analytical skills, communication skills, and continuous learning. According to the criteria above, levels of preparation for specialists in the field of labour law were established, namely high, medium, and essential. The proposed training and education technology for specialists in the field of labour encompasses the following tools: The utilisation of online platforms and educational resources, virtual classes and simulations, the incorporation of multimedia materials, the integration of adaptive learning technologies, the implementation of project- and problem-oriented teaching methodologies, the incorporation of interactive methodologies, the incorporation of cloud technologies and mobile applications, and the provision of assessment and feedback. Conclusion: The proposed pedagogical technology effectively enhances the training and education of labour law specialists. The experimental group’s significant improvement in learning outcomes confirms the technology’s efficacy. Implication: The findings of this research hold significant social implications. Improved training and education of labour law specialists leads to a more competent and effective legal workforce. This, in turn, ensures better protection of workers’ rights and fairer employer-employee relations, contributing to overall social stability.

This study explores the relationship between GDP growth, unemployment rate, and labor force participation rate in the Gulf Cooperation Council (GCC) countries from 1990 to 2018. Furthermore, the study incorporates control factors such as government spending, trade openness, and energy use into the regression equation. We used panel dynamic ordinary least squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS) estimators to investigate the relationships between variables in this investigation. The econometric technique accounts for nonstationary, endogeneity bias and cross-sectional dependencies between country-year observations. Cointegration was found among GDP growth, unemployment rate, and labor force participation. Long-term, the unemployment rate has a statistically significant negative effect on economic growth in the GCC nations. Meanwhile, the labor force participation rate significantly influences economic expansion in the long term. The expansion of government expenditures and international trade reduces economic growth. Alternatively, it is discovered that energy consumption has a substantial and positive effect on economic expansion. Okun’s rule and the unidirectional causality from economic growth to unemployment indicate that the primary cause of unemployment in GCC nations is a failure to adequately expand their economies. When developing economic strategies to reduce unemployment, policymakers are particularly interested in determining whether or not economic development and the unemployment rate are cointegrated.

The problem of flooding in the capital is still classified as a classic problem, but this problem still continues to emerge and becomes a trending problem during the rainy season in urban weather. This research aims to analyze the effectiveness of governance collaboration in overcoming the Jakarta flood problem. This research uses qualitative analysis and a content analysis approach. This research found that flood management using a collaborative governance approach was running optimally, the involvement of the private sector and the community was a good and rare synergy. support from international funding sources is used with effective management with the aim of using the budget on target. In the end, this research concludes that collaborative governance in Jakarta flood management is carried out optimally but requires sustainable collaborative efforts. This research has limitations in reaching the involvement of personal actors as a source of supporting information in disaster mitigation studies. Further research requires a more comprehensive discussion by reviewing the involvement of important actors in flood disaster mitigation.

While the healthcare landscape continues to evolve, rural-based hospitals face unique challenges in providing quality patient care amidst resource constraints and geographical isolation. This study evaluates the impact of big data analytics in rural-based hospitals in relation to service delivery and shaping future policies. Evaluating the impact of big data analytics in rural-based hospitals will assist in discovering the benefits and challenges pertinent to this hospital. The study employs a positivist paradigm to quantitatively analyze collected data from rural-based hospital professionals from the Information Technology (IT) departments. Through a comprehensive evaluation of big data analytics, this study seeks to provide valuable insights into the feasibility, infrastructure, policies, development, benefits and challenges associated with incorporating big data analytics into rural-based hospitals for day-to-day operations. The findings are expected to contribute to the ongoing discourse on healthcare innovation, particularly in rural-based hospitals and inform strategies for optimizing the implementation and use of big data analytics to improve patient care, decision-making, operations and healthcare sustainability in rural-based hospitals.