Today urban development lacks ecological foundations in many cities of Turkey. The purpose of this study is to reveal the relationship between urban green spaces and ecological zones in the sample of Aksaray/Turkey. In this study, a study design has been created to improve the urban ecological infrastructure and to associate the green space network with the ecological zones. This design is divided into four parts as data processing, landscape pattern of urban green spaces, analysis of the spatial boundaries of urban natural ecological zones, and determination of the importance of spatial regions by overlaying two different stratified analyses. This study proposes a methodological framework that can be integrated into efforts to identify ecological zones to increase the sustainability of urban ecology and green space quality. One potential limitation of the proposed methodology can be the lack of consensus and enthusiasm among the administrative actors regarding the issue. Therefore, it is recommended that the administrative bodies should be correctly informed by the relevant scholars and practitioners who are working on the subject.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

Weather is almost inevitable and plays an important role in determining the duration of construction projects. The construction industry ultimately thrives upon the physical input, put in by the labours. The majority of the construction projects are executed in the outdoor environment and hence face a high impact of weather conditions. This study therefore evaluated the influence of weather conditions on construction workers’ productivity in Jos, Plateau State and proceeded to make recommendations geared towards the improvement of construction workers’ productivity in Jos. The study was conducted through the direct observation method. Three hundred and ninety-six (396) works were purposively sampled in selected working sites. The outcome shows that during dry weather, there was considerably less significant productivity of manual excavation. In contrast, a large increase in blockwork and plasterwork productivity was observed with a percentage difference of 33%, 56.3% and 61%, respectively. On the other hand, during wet weather conditions, the labour productivity for manual excavation increases, whereas it decreases for block work and plasterwork with percentages difference of 58%, 40% and 47%, respectively. Besides, relative humidity and wind speed have no impact on labours’ productivity in dry and wet weather. Besides, the temperature has the most decisive impact on workers’ productivity. Moreover, wind speed and humidity have a lower influence on workers’ productivity. The construction industry stakeholder in Jos, Nigeria, would benefit from this study’s recommendations for reducing the influence of weather on the building sector. Besides, the output can be extended to other regions having similar characteristics.

Given the multifaceted nature of crime trends shaped by a range of social, economic, and demographic variables, grasping the fundamental drivers behind crime patterns is pivotal for crafting effective crime deterrence methodologies. This investigation adopted a systematic literature review technique to distill thirty key factors from a corpus of one hundred scholarly articles. Utilizing the Principal Component Analysis (PCA) for diminishing dimensionality facilitated a nuanced understanding of the determinants deemed essential in influencing crime trends. The findings highlight the necessity of tackling issues such as inequality, educational deficits, poverty, unemployment, insufficient parental guidance, and peer influence in the realm of crime prevention efforts. Such knowledge empowers policymakers and law enforcement bodies to optimize resource allocation and roll out interventions grounded in empirical evidence, thereby fostering a safer and more secure societal environment.

Social and environmental issues gain more importance for society that stimulates companies to adopt and integrate more sustainability practices into their business activities. This study is embedded in almost uncovered in the literature context of Russian business that undergoes its ESG transformation in conditions of unprecedented sanctions and hostile institutional environment. The study aims to reveal the role of internal stakeholders (top managers, line managers, and employees) in successful implementation of a company’s ESG practices along various dimensions. Using the primary data from 29 large Russian companies the fsQCA method is applied to identify various configurations of contingencies that stimulate their ESG performance. The analysis results in identification of two alternative core conditions for high ESG performance in Russian companies: high top management commitment to sustainability and low employees’ commitment to sustainability or the employees’ awareness about sustainability. At the end, the study results in two generic profiles composed of top management commitment, line management support, and employees’ awareness, behavior, and commitment towards ESG performance. The results show two different approaches towards ESG transformation that may bring a company to the comparably similar desired outcome. The study has a potential for generalization on a wider scope of emerging market contexts.

In the era of rapid technological development, the integration of technology in education has become crucial (Hashim et al., 2022). The digital transformation of education requires universities to transform their traditional operational models, strategic directions, and teaching practices, re-examine their own value propositions, and promote high-quality innovative development in universities. Transformation and change bring challenges to organizational management, especially leadership. Can digital leadership positively influence the innovative behavior of university teachers? Can digital leadership improve organizational innovation performance by influencing innovation behavior? These questions urgently need to be answered through practical surveys of digital transformation in universities. From March 2024 to May 2022, we conducted a survey of 1142 participants from 12 universities in Kunming, southwestern China. Our research findings indicate that digital leadership has a positive impact on the innovation performance of university organizations; Innovation behavior plays a mediating role between digital leadership and organizational performance. These findings provide new insights into the potential mechanisms by which digital leadership influences organizational innovation in universities. The research findings emphasize that in the process of transforming traditional operational models, strategic directions, and teaching practices in higher education, in order to achieve high-quality innovative development, it is necessary to attach importance to digital leadership and continuously stimulate innovative behavior.