In the context of establishing businesses in a new region, neglecting environmental orientation may lead to the omission of crucial motives for entrepreneurs’ migration and the subsequent course of their businesses. This present study aims to investigate the effect of green space quality (GSQ), green campaign (GC), and green attitude (GA) on green entrepreneurship pioneering intention (GEPI). Further, national pride (NP) was added as a moderator. This study utilized a cross-sectional approach using a survey method targeting small and medium-sized enterprise (SME) owners who will be relocated to the new capital city. Partial least square structural equation modeling was employed in the data analysis. The results revealed that GSQ, GC, and GA positively influence GEPI. Also, NP moderates the positive influences of GC and GA on GEPI. Entrepreneurs were motivated to pioneer green entrepreneurship in the new region due to environmental factors. Furthermore, their nationalism reinforces the connection between environmental motivations and the aspirations to undertake such pioneering endeavors. The findings present valuable insights for governments to formulate policies that encourage entrepreneurs to migrate internally and establish new economic nodes. Further, the results demonstrate how nationalism encourages green business pioneering endeavors in an untapped market.

In the human and economic development context, this study examines the relationship between human capital, life expectancy, labor force participation rate, and education level in Indonesia, Malaysia, and Thailand. The World Bank’s 2001–2021 data are examined using a panel vector autoregressive model. The findings demonstrate the substantial influence of health expenditure from the prior period on present health expenditure. Though not significantly different, life expectancy and education levels from earlier periods also impact present health spending. A slight positive correlation exists between prior labor force involvement and present healthcare costs. An increase in current health expenditure supports an increase in life expectancy. Health expenditure in the previous period had a significant positive effect on education, although insignificant. Life expectancy in the previous period harms current education but is also insignificant. Education in the previous period significantly positively affects current education, indicating a sustained impact of education investment. Labor force participation in the previous period also positively affected education, although not significantly. The prior period’s health spending, life expectancy, and educational attainment impact the current labor force participation rate. The length of life has a significant favorable impact on entering the labor sector. Currently being in the job field has a good correlation with prior education as well. These findings support that higher education levels lead to higher labor force participation rates. Life expectancy, health care costs, education level, and prior work experience all influence current life expectancy. While prior life expectancy significantly influences current life expectancy, health expenditures have a negligible negative impact. Prior education positively impacts life expectancy but negatively impacts prior labor force engagement. These results reject the hypothesis that increasing life expectancy causes current health expenditure to increase.

The objective of the study was to determine the relationship between open government and municipal effectiveness State a region of the Peruvian jungle. The research followed a quantitative approach with a non-experimental, cross-sectional, and correlational design. The population comprised citizens of State in a region of the Peruvian jungle, with a sample of 625 individuals. A structured survey was employed as the data collection technique, using a validated questionnaire as the instrument. The results revealed a positive, high, and significant correlation between governance and municipal effectiveness (Spearman’s Rho = 0.813, p < 0.01). Furthermore, the dimensions of transparency, integrity, accountability, and citizen participation showed moderate to high correlations with municipal effectiveness, with accountability (Rho = 0.779) emerging as the most influential dimension. It was concluded that the principles of open government play a crucial role in shaping the perception of effective municipal management. This underscores the need to strengthen transparency, integrity, and citizen participation policies to enhance public services and foster trust in local authorities.

This research focused on the design and implementation of the flipped classroom approach for higher mathematics courses in medical colleges. Out of 120 students, 60 were assigned to the experimental group and 60 to the control group. In the continuous assessment, which included homework and quizzes, the average score of the experimental group was 85.5 ± 5.5, while that of the control group was 75.2 ± 8.1 (P < 0.05). For the final examination, the average score in the experimental group was 88.3 ± 6.2, compared to 78.1 ± 7.3 in the control group (P < 0.01). The participation rate of students in the experimental group was 80.5%, significantly higher than the 50.3% in the control group (P < 0.001). Regarding autonomous learning ability, the experimental group spent an average of 3.2 hours per week on self-study, compared to 1.5 hours in the control group (P < 0.005). Other potential evaluation indicators could involve the percentage of students achieving high scores (90% or above) in problem-solving tasks (25.8% in the experimental group vs. 10.3% in the control group, P < 0.05), and the improvement in retention of key concepts after one month (70.2% in the experimental group vs. 40.5% in the control group, P < 0.01). In conclusion, the flipped classroom approach holds substantial promise in elevating the learning efficacy of higher mathematics courses within medical colleges, offering valuable insights for educational innovation and improvement.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.