In Ghana, youth unemployment remains significant challenges, with technical and vocational education and training (TVET) emerging as a potential solution to equip young people with practical skills for the job market. However, the uptake of TVET programmes among Ghanaian youth remains low, particularly among females. This study therefore explores the determinants that influence TVET choices among Ghanaian youth, with the goal of informing policy development to enhance participation in vocational education. Applying an enhanced multinomial logistic regression (MLR) model, this research examines the influence of socio-economic, demographic, and attitudinal factors on career decisions. The enhanced model accounts for class imbalances in the dataset and improves classification accuracy, making it a robust tool for understanding the drivers behind TVET choices. A sample of 1600 Ghanaian youth engaged in vocational careers was used, ensuring diverse representation of the population. Key findings reveal that males are approximately three times more likely to choose TVET programs than females, despite females making up 50.13% of Ghana’s population. Specific determinants influencing TVET choices include financial constraints, parental influence, peer influence, teacher influence, self-motivation, and vocational limitations. In regions with limited vocational options, youth often pursue careers based on availability rather than preference, which highlights a gap in vocational opportunities. Parental and teacher influences were found to play a dominant role in steering youth towards specific careers. The study concludes with recommendations for policymakers, instructors, and stakeholders to increase the accessibility, relevance, and quality of TVET programmes to meet the socio-economic needs of Ghanaian youth.

Climate change is the most important environmental problem of the 21st century. Severe climate changes are caused by changes in the average temperature and rainfall can affect economic sectors. On the other hand, the impact of climate change on countries varies depending on their level of development. Therefore, the aim of this paper is to investigate the relationship between climate changes and economic sectors in developed and developing countries for the period 1990–2021. For this purpose, a novel approach based on wavelet analysis and SUR model has been used. In this case, first all variables are decomposed into different frequencies (short, medium and long terms) using wavelet decomposition and then a SUR model is applied for the examination of climate change effects on agriculture, industry and services sectors in developed and developing countries. The findings indicate that temperature and rainfall have a significant negative and positive relationship with the agriculture, industry and services sectors in developed and developing countries, respectively. But severity of the negative effects is greater in the agricultural and industrial sectors in all frequencies (short, medium and long terms) compared to service sector. Furthermore, the severity of the positive effects is greater in the agricultural sector in all frequencies of developing countries compared to the industrial and services sectors. Finally, developing countries are more vulnerable to climate change in all sectors compared to developed countries.

Although much bibliometric research has been conducted to analyze publications on energy policy, a systematic investigation of the sustainability of nuclear energy use after the Fukushima nuclear accident is still lacking. Therefore, this study conducted a comprehensive bibliometric review of the sustainability of nuclear energy policy (NEP). This study discusses NEPs, highlighting their disadvantages; emerging research themes; and networks of the most productive authors, countries, journals, and institutions over the last 20 years (2002–2022). This timeframe was selected because of the Fukushima nuclear accident, which has been one of the largest environmental disasters in recent years. Bibliometric analysis was carried out by reviewing 1146 documents from the Scopus database using the keywords “energy policy” and “nuclear energy.” The OpenRefine software was used to deep-clean keywords with the same meaning, and VOSviewer was used to visualize them. The results show that over the past two decades, future research themes and trends in the study of NEP have focused on nuclear fuel, the Fukushima nuclear accident, risk perception, energy transition, and renewable energy. Bibliometric analysis has positively affected the development of NEP in countries that do not yet have nuclear power plants, such as Indonesia.

Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.

The research explores academia and industry experts’ viewpoints regarding the innovative progression of Virtual Reality (VR)-based safety tools customized for technical and vocational education training (TVET) within commercial kitchen contexts. Developing a VR-based safety tools holistic framework is crucial in identifying constructs to mitigate the risks prevalent in commercial kitchens, encompassing physical, chemical, biological, ergonomic, and psychosocial hazards workers encounter. Introducing VR-based safety training represents a proactive strategy to bolster education and training standards, especially given the historically limited attention directed toward workers’ physical and mental well-being in this sector. This study pursues a primary objective: validating a framework for VR-based kitchen safety within TVET’s hospitality programs. In addition to on-site observations, the research conducted semi-structured interviews with 16 participants, including safety training coordinators, food service coordinators, and IT experts. Participants supplemented qualitative insights by completing a 7-Likert scale survey. Utilizing the Fuzzy Delphi technique, seven constructs were delineated. The validation process underscored three pivotal constructs essential for the VR safety framework’s development: VR kitchen design, interactive applications, and hazard identification. These findings significantly affect the hospitality industry’s safety standards and training methodologies within commercial kitchen environments.

This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.