This article examines the overseas corporate social responsibility (CSR) patterns of Chinese international contractors (CICs). Adopting an institutional and political economy approach, a unique dataset is constructed with country-specific contents drawn from CSR-related reports and website information of 50 top CICs. This dataset provides a foundation for systematic content analysis of CICs’ overseas CSR practices, revealing that both political legitimacy-seeking and strategic competitiveness-seeking motivations drive CICs’ CSR activities abroad, characterized by the prioritization of customer and community engagement. The findings highlight the coexistence of the exogenous pressures for the national image-building purpose and the endogenous awareness of CSR strategic importance for corporate internationalization. The hybridization of political and economic rationales is presented as the defining feature of CICs’ current overseas CSR patterns, with the balance between them being determined by stakeholder type and internal business needs influenced by corporate internationalization experience.

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.

This article presents a bibliographic review on the evolution of Geographic Information Systems (GIS) and their integration in the social sciences, which is important because the interrelation of these areas contributes to the knowledge of the people. In this sense, the objective was to contribute to the university academic knowledge, through the compilation, classification, analysis and synthesis of scientific works according to the subject treated. For this purpose, the historical, synthetic, dialectical, and analytical methods were used, with a descriptive and documentary type of research, obtaining as a result that the GIS are very useful in different fields of social sciences, ranging from archeology to sociology, including specific topics such as economics and criminology.

This study investigates the relationship between Corporate Social Responsibility (CSR) dimensions and employees’ satisfaction and retention for sustainability in banks.  Four components (economic, legal, ethical, and philanthropic) are analyzed CSR activities and their effects on employee’s satisfaction and retention in the company. Purposive and convenient sampling method was used to get the information from 221 participants. The entire form of the dataset is utilized to execute regression and correlation analysis using SPSS. In order to find out the relationship between economic, legal, ethical, and philanthropic factors and employee’s satisfaction and retention, regression beta coefficient and correlation were used to analyze. This study also examines the relationship between job satisfaction and intentions to retain with an organization. The findings demonstrate that the CSR aspects of ethical and philanthropic have a considerable and favorable influence on employee’s satisfaction. The outcome also demonstrates a good and prominent influence of legal CSR on the satisfaction of employee’s to retain with the firm. Moreover, this study demonstrates that economic aspect of CSR has no significant impact on employee’s retention and satisfaction. Correlation analysis depicts that economic CSR is positively and significantly connected with employee’s retention and satisfaction. This research came to the conclusion that enhancing employees view regarding CSR activities such as economic, legal, ethical, and philanthropic will increase employee’s satisfaction. Therefore, executives and managers in the banks should take steps to influence how employees see CSR areas in order to raise employee’s satisfaction and retention in the banks for sustainability.