Corporate social responsibility (CSR) is an important concept of modern economic theory. In the last few decades, it has become an increasingly popular marketing tool used by companies. Consumers too want to see more CSR activities, especially those focused on environmental protection. The petroleum industry produces both toxic and non-toxic waste at almost all stages of production. While petroleum companies satisfy market demand, they also want to meet consumers’ moral and ethical demands. In this light, CSR has become vital for the development of industry. This paper looks at CSR in the petroleum industry, and its effect on customer satisfaction and subsequently toward the customer repurchase intention in Malaysia. The starting point of this paper is the Stakeholder Theory. It then examines CSR endeavors within the oil and gas sector and its link to customer repurchase intentions. It also looks at the established hypotheses between the activities of CSR (Economic Responsibility, Legal Responsibility, Ethical Responsibility, Philanthropic Responsibility), customer satisfaction and repurchase intention. This paper aims to learn about the customer’s sense of fulfilment with the CSR activities, and what could be the reaction base on the customer’s expectation.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

This study conducted a systematic review of the existing literature on rhythmic gymnastics. Through searching databases such as PubMed, Web of Science, and Scopus, 37 out of 2319 articles were selected, covering training and physical fitness, nutrition and metabolism, as well as sports injuries and rehabilitation. The findings revealed that: (1) Core physical training significantly enhanced athletes’ performance; (2) Inadequate nutritional intake was prevalent; (3) The incidence of sports injuries was high, particularly those resulting from overtraining. The conclusion emphasizes the need to enhance strength training, optimize nutritional management, and further investigate injury prevention and rehabilitation measures to enhance athletes’ performance and health status.

Protecting the environment and the Earth's natural resources is one of the most important tasks for modern societies, economies, and countries. Changes in the environment have made climate protection a key task of state policy implemented at the local, national, and international. They also have caused such negative social manifestations as environmental radicalism and terrorism. The purpose of this paper was to analyze the capacity of state institutions to prevent environmental terrorism and radicalism, particularly in the Russian context, by identifying and prioritizing key challenges and countermeasures. A mixed-methods approach was adopted, involving both qualitative and quantitative analyses. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 35 articles and reviews were selected to provide a foundation for understanding eco-terrorism trends. Additionally, an expert survey was conducted with 44 qualified participants to rank problems and recommended actions. The Kendall concordance coefficient was used to assess the consistency of expert opinions. The authors conclude that low environmental awareness and insufficient cooperation between state institutions and environmental organizations are the most significant challenges in preventing eco-terrorism. To adequately and competently prevent environmental terrorism and radicalism in society, the prevention system must be based on clear and thoughtful actions by state institutions.

The purpose of this study is to examine the impact of tourist spending and the growth of Oman’s tourism industry on the country’s GDP from 1996 to 2018. The study uses the error correction model and other tests for assessing the link among variables, such as the cointegration test and the Granger causality test, to accomplish its aims. Findings from the error correlation model and cointegration test show that there is a link between the variables in Oman over the long and short term. There is a positive and statistically significant relationship between tourist expenditures and economic growth, as well as a negative and statistically significant relationship between tourism expansion and economic growth. We now use ARDL regression estimators to assess the robustness of the empirical results. There is no evidence of a direct relationship between increased tourism and GDP growth, according to the study’s results. According to the research, sustainable tourism development is an achievable economic growth driver, and Oman should prioritize economic policies that support this trend.

This study explores the role of intercultural communicative competence (ICC) and STEM education in building the soft infrastructure necessary for economic development within Kazakhstan’s transforming education system. The authors conducted an interdisciplinary analysis, emphasizing the cognitive and communicative aspects of foreign language education in secondary schools, proposing a model for integrating ICC through the use of information and analytical technologies. The research focuses on personalized education, teacher competencies, and student engagement, with experimental methods applied in a Karaganda-based school. The study aims to identify mechanisms and principles that enhance ICC development, contributing to Kazakhstan’s modernization efforts in fostering globally competitive graduates prepared for the demands of the international arena. This research lays the foundation for further practical experimentation in profiled schools, aligning education with national development goals.