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.

Manuscript type: Research paper. Research aims: This study aims to explore the determinants of voluntary IFRS application in listed firms in Vietnam. Design/methodology/approach: Analyzing data from 552 public companies listed on the Ho Chi Minh Stock Exchange and Ha Noi Stock Exchange during 2019–2022, this study employs a logistic model with robust analysis. Research findings: The findings indicate that voluntary IFRS application is positively associated with firm size, leverage, internationalization, corporate efficiency, state ownership, and foreign ownership. Particularly, internationalization has the most significant impact on voluntary IFRS application. Theoretical contribution/originality: These findings of this study align with positive accounting theory, which proposes how factors affect voluntary IFRS application. Practitioner/policy implications: Policymakers should consider these findings when developing or revising policies concerning voluntary IFRS application, particularly for state-owned and foreign-owned companies. Research limitation: This study spans from 2019 to 2022, during which economic and regulatory conditions may have fluctuated, potentially impacting the results. Moreover, the data on voluntary IFRS adoption were collected through surveys, which may be subject to respondent bias and dependent on participants’ understanding and willingness to provide accurate information.

This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.

Introduction: The growing global focus on Environmental, Social, and Governance (ESG) standards necessitates that companies optimize their corporate governance to balance economic, social, and ecological responsibilities. This study examines how the synergistic effects of Corporate Social Responsibility (CSR) and Environmental Responsibility (ER) can promote sustainable corporate development. Objective: The objective of this study is to analyze the critical elements of corporate governance structure optimization and to explore how companies can enhance their governance to achieve sustainable development through strengthened social and environmental management practices. Methods: The study uses case analysis and literature review to assess high-performing enterprises in CSR and ER integration, examining their governance, policy, and environmental strategies to uncover the factors behind their success in economic, social, and environmental spheres. Results: The research shows that optimizing governance structures markedly improves operational effectiveness. Companies need to create strong internal controls for equitable and transparent decisions, embedding CSR and ER into their strategies. CSR fulfillment builds public trust and environmental support, whereas ER improves brand reputation and competitiveness, driving sustainable and mutually advantageous development. Conclusion: The key to sustainable development in ESG practice lies in optimizing corporate governance and strengthening the synergy between social and environmental responsibilities. It is imperative for companies to build a governance structure that complies with ESG standards and to incorporate social and environmental considerations into their corporate strategies to effectively manage the triple bottom line of economic, social, and environmental performance.

Comparative studies of national values are becoming increasingly important in the context of contemporary globalization processes. An essential condition for the shaping of national values in learners is the enrichment of pedagogical technology with components of digital technology. Both qualitative and quantitative approaches were used in the current study. The purpose of this research is to examine the efficacy of mobile learning in shaping the national values of prospective teachers. The experiment included 180 participants. Diagnostics of the levels of national values formation in the initial stage confirmed the assumption about the low formation of national values among teacher candidates and, consequently, the need for targeted work on their formation. This study demonstrates that significant advances in students’ national values have occurred following the introduction and testing of mobile learning with experimental group (EG) participants to shape national values. The data from this study can serve as the basis for creating strategies for shaping the national values of learners in universities and as a methodological basis for adapting mobile learning for the shaping of national values.

Artificial intelligence has transformed teachers’ teaching models. This article explores the application of artificial intelligence in basic education in Macao middle schools. This study adopts case analysis in qualitative research, using a total of eight cases from the innovative technology education platform of the Macau education and Youth Development Bureau. These data illustrate how Macao’s artificial intelligence technology promotes teaching innovation in basic education. These eight cases are closely related to the application of artificial intelligence in basic education in Macao. The survey results show that Macao’s education policy has a positive effect on teaching innovation in artificial intelligence education. In teaching practice, the school also cooperates with the government’s policy. The application of AI technology in teaching, students’ learning styles, changes in teachers’ roles, and new needs for teacher training are all influential.

This study aimed to examine the impact of Environmental, Social, and Corporate Governance (ESG) scores and Country Governance Indicators (CGI) on companies’ value. The study procedures were carried out by creating a linear empirical model where the dependent variable was companies’ value. In addition, the variables of interest in the model were ESG scores and CGI. Analysis was carried out on annual data from 278 non-financial Asian companies spanning 11 years from 2011–2021. The feasible generalized least squares (FGLS) method was used for estimation due to the presence of serial correlation and heteroscedasticity in the data obtained. The results showed the presence of a positive relationship and correlation between ESG scores and companies’ value. Meanwhile, CGI had a negative impact, revealing the potential difficulties caused by country governance framework. This study also found a positive correlation between CGI and ESG on company value. These findings have important practical contributions emphasizing the significance of ESG factors in improving companies’ value and the complex relationship between country governance and corporate valuation.