According to official data, modern Russia has the lowest unemployment rate. However, there is still a huge contingent of hidden unemployment, many times higher than the official level. This situation is paradoxically combined with an acute and continuously growing shortage of qualified production personnel. Using a lot of factual material, the author reveals the causes of this phenomenon. The main one is the depopulation of the indigenous population, which is being replaced by people of other ethnic groups with the lowest qualification level. At the same time, due to the destruction (“optimization”) of the education system, the intellectual and qualification level of the indigenous population is continuously decreasing. The other is the various types and waves of growing emigration of “brains” and “golden hands.” As a result, for more than thirty years, the contingent of old engineering and technical personnel has exhausted itself, while new ones have not been trained in the required volume and quality. A huge personnel “hole” has formed. The author proposes to close this “hole” on the basis of a radical reorientation of the entire Russian education system, starting with kindergarten, school, etc. It is also necessary to reformat the public consciousness accordingly, especially the mass consciousness of young people.

In developing metropolitan cities, the expansion of urban areas due to the urbanization phenomenon has resulted in massive transport infrastructure development in suburban areas. This development has prompted many governments to begin introducing Transit-Oriented Development (TOD) to organize emerging transit hubs in suburban areas into their city plans. The approach adopted to introduce TOD may differ, depending on the existing context. Countries with similar socio-cultural background typically adopt a uniform approach, but not Jakarta and Kuala Lumpur as the most developing metropolitan cities in Southeast Asia with similar urbanization and socio-cultural Based on the situation, through the examining documents and spatial analysis, this study seeks to examine the impact of different policy approach between Jakarta and Kuala Lumpur on the progressions of transport infrastructure and TOD areas in suburban. The results showed that Kuala Lumpur had a more rapid progression in transport infrastructures development, accompanied by the establishment of several transit zones in urban and suburban areas. Meanwhile, Jakarta’s approach comprised the gradual development of infrastructures, initially focusing on TOD in central urban areas and only a limited number of suburban areas with significant commuter traffic. These results indicate that differences in policy approaches in the two regions with similar urbanization and socio-cultural contexts influence the evolution of transport infrastructure and TOD areas development. Several factors contribute to these discrepancies, including efficiency, synchrony, bias, clarity of organizational structure, and conceptual comprehension. At macro basis, policy makers must underline that the characteristics suitability between the approach and region critically determines the success of urban development.

Road accidents involving motorcyclists significantly threaten sustainable mobility and community safety, necessitating a comprehensive examination of contributing factors. This study investigates the behavioral aspects of motorcyclists, including riding anger, sensation-seeking, and mindfulness, which play crucial roles in road accidents. The study employed structural equation modeling to analyze the data, utilizing a cross-sectional design and self-administered questionnaires. The results indicate that riding anger and sensation-seeking tendencies have a direct impact on the likelihood of road accidents, while mindfulness mitigates these effects. Specifically, mindfulness partially mediates the relationships between riding anger and road accident proneness, as well as between sensation-seeking and road accident proneness. These findings underscore the importance of effective anger management, addressing sensation-seeking tendencies, and promoting mindfulness practices among motorcyclists to enhance road safety and sustainable mobility. The insights gained from this research are invaluable for relevant agencies and stakeholders striving to reduce motorcycle-related accidents and foster sustainable communities through targeted interventions and educational programs.

Combining physical, social, and economic elements, urban planning plays a critical role in creating sustainable, resilient, and livable urban environments. It encompasses the regulation of land use, infrastructure, transportation systems, and environmental resources, with a focus on sustainable urban design and green infrastructure. While progress has been made, there are still areas that have not been fully explored, including the integration of renewable energy sources and the development of urban environments that are resilient to environmental stresses. This study aims to analyze the direction and scope of urban planning research and to identify research gaps in this area. The method used is bibliometrics by analyzing data obtained from the Scopus database in January 2024. The results of this study showed that Yufeng Zhang, a professor at Wuhan University, China, was the most productive author in producing publications, namely 22 documents. In addition, the article produced by Qianqian Zhou is also influential in this research topic because it gets a number of citations, as high as 204 citations. Additionally, the results indicate the current focus of research on sustainability, adaptation to climate change, and technology in urban planning. These findings can guide future research, direct policy, and ensure an interdisciplinary approach to modern urban and regional challenges.

This study examines the impact of Human Resource Management (HRM) practices, specifically Compensation, Job Design, and Training, on employee outcomes, including Engagement, Efficiency, Customer Satisfaction, and Innovation within an organizational framework. Employing a quantitative research methodology, the study utilizes a cross-sectional survey design to collect data from employees within a public service organization, analyzing the relationships through structural equation modelling. Findings reveal significant positive relationships between HRM practices and employee performance metrics, highlighting the pivotal role of Employee Engagement as a mediator in enhancing organizational effectiveness. Specifically, Compensation and Job Design significantly influence Employee Engagement and Efficiency, while training is crucial for driving Innovation and Customer Satisfaction. The practical implications of this research underscore the necessity for organizations to adopt integrated and strategic HRM frameworks that foster employee engagement to drive performance outcomes. These insights are vital for HR practitioners and organizational leaders aiming to enhance workforce productivity and innovation. In conclusion, the study contributes valuable perspectives to the HRM literature, advocating for holistic HRM practices that optimize employee well-being and ensure organizational competitiveness. Future research is encouraged to explore these dynamics across various sectors and cultural contexts to validate the generalizability of the findings.

Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.