This study examines the spatial distribution and structure of traffic offences in the Northern Great Plain region. The research is unique in that it examines a specific area through the lens of geography. The research shows and demonstrates that the research area of crime and transport geography is much broader than previous researches has shown. At the beginning of the study, the authors clarified the conceptual framework, as the terms “violation” and “offence” are often confused even in technical materials. The research shows which routes are the most frequently used by road hauliers in the regions under study and what type of checks have been carried out on these routes by the Transport Authorities of the Government Offices. The type of administrative penalty detected and the nationality breakdown of the infringements are described. The study typifies the infringements involving administrative fines by nationality category.

The northern territories of Russia need high-quality strategic digital changes in the structure of the regional economy. Digitalization and the introduction of digital technologies in the medium term will be able to transform economic relations in the old industrial and raw materials regions of the North, improve the quality of life of local communities. The growth of digital inequality among the regions under study leads to disproportions in their socio-economic development. The purpose of this study is to develop and test a methodology for assessing the level of development of the digital infrastructure of the Russian northern regions, including classification of an indicators system for each level of digital infrastructure, calculation of an integral index and typology of the territories under study. The objects of the study were 13 northern regions of the Russian Federation, the entire territory of which is classified as regions of the Extreme North and equivalent areas. The methodology made it possible to determine the level of technical, technological and personnel readiness of the northern regions for digitalization, to identify regions with the best solutions at each level of digital infrastructure development. The analysis of the results in dynamics helped to assess the effectiveness of regional policy for managing digitalization processes. As a result, the authors came to the conclusion that increasing the competitiveness of northern regions in the era of rapid digitalization is possible through investments in human capital and the creation of a network of scientific and technological clusters. The presented approach to assessing the development of individual levels and elements of digital infrastructure will allow for the diagnosis of priority needs of territories under study in the field of digitalization. The results of the study can form the basis for regional policy in the field of sustainable digital development of Russia.

Sustainability has become a generalized concern for society, specifically businesses, governments, and academia. In the specific case of universities, sustainability has been approached from different perspectives, some viewing it from environmental practices, management initiatives, operational criteria, green buildings, and even education for sustainable development. This research focuses on sustainability as a managerial practice and investigates how it affects the performance of five private universities in Medellin, Colombia. For this purpose, a literature review using a mixed sequential approach, including bibliometric and content analysis, was initially conducted. In the s second phase, more than 5000 responses from students, professors, and employees of the five mentioned private universities were collected. A previously validated instrument for both sustainability and performance was applied in the quantitative phase, and a novel dimensionality of the constructs was proposed by conducting an exploratory factor analysis using the SPSS software. Results were then processed through a structural equation analysis with the Smart PLS software. The impact of sustainability on university performance is verified, making some managerial recommendations.

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.

The aim of this research is to determine the incidence of socioeconomic variables in migration flows from the main countries of origin that form part of the international South-North migration corridor, such as Mexico, China, India, and the Philippines, during the 1990–2022 period. The independent variables considered are GDP per capita, unemployment, poverty, higher education, and public health, while the dependent variable is migration flows. An econometric panel data model is implemented. The tests conducted indicate that all variables have an integration order of I (1) and exhibit long-term equilibrium. The econometric models used, Dynamic Ordinary Least Squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS), reveal that unemployment and poverty had the strongest influence on migration flows. In both models, within this international migration corridor, GDP per capita, higher education, and health follow in order of importance.

Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).