The purpose of this study is to examine how financial slack and board gender diversity affect carbon emission disclosure and how that disclosure affects firm value in energy sector companies that are listed on the Indonesian stock exchange between 2017 and 2021. Annual reports and sustainability sources provide secondary data for this quantitative study. Purposive sampling was employed in this investigation, including nine companies and a five-year observation period. Thus, 45 samples altogether were employed in the present study. The partial least squares approach is the data analysis strategy used in this investigation. The study’s findings indicate that the Gender Diversity Board does not significantly affect carbon emission disclosure and significantly influences firm value. Financial slack significantly affects carbon emission disclosure but does not directly affect firm value. Financial slack and board gender diversity through carbon emission disclosure have no significant effect on firm value.

The emerging growth digital application has driven ecosystems integrating digital banks and e-commerce platforms, enabling seamless, efficient transactions. This study examines the impact of user experience and satisfaction on reuse intention in this integrated environment. Using a mixed-method approach, data were collected through surveys of 471 respondents and interviews with 30 participants. Quantitative data were analyzed using structural equation modeling, while qualitative data were processed through content analysis. Results show that perceived ease of use, usefulness, reliability, value, and risk significantly affect user experience, while perceived security does not. These findings aim to help digital banks and e-commerce platforms design effective CRM strategies to enhance satisfaction and reuse intention.

The application of quality management methods and tools is an important prerequisite for the success and performance increase of manufacturing enterprises. The paper deals with the application of methods and tools of quality management (MTQM) in manufacturing enterprises. The paper aims to analyze whether there is a relationship between the application of MTQM and the size of enterprises, the use of MTQM, and the performance of enterprises measured through the achieved profit. It also analyzes the impact of MTQM on the agility of manufacturing enterprises measured through the decrease in sales expressed in revenues during the pandemic period. The paper presents the results of the research which was conducted between 2020–2022. Several statistical tools such as the Chi-square goodness-of-fit test, Pearson’s chi-square test, and contingency analysis were used to evaluate the different analyses as well as the representativeness of the sample. Based on the results, it can be concluded that there are differences in the use of MTQM and the size of the enterprise as well as the performance of the enterprises. At the same time, the hypothesis that enterprises using a wider range of quality management methods and tools have a higher potential to adapt to unexpected market changes was also confirmed.

This study assesses Vietnam’s state-level implementation of artificial intelligence (AI) technology and analyses the government’s efforts to encourage AI implementation by focusing on the National Strategy on AI Development Program. This study emphasizes the possibility of implementing AI at the state level in Vietnam and the importance of conducting continuous reviews and enhancements to achieve sustainable and inclusive AI growth. Impact evaluations were conducted in public organizations alone, and implication evaluations were considered optional. AI impact assessments were constrained by societal norms that necessitated establishing relationships among findings. There is a lack of official information regarding the positive impact of Vietnam’s AI policy on the development of AI infrastructure, research, and talent pools. The study’s findings highlight the necessity of facilitating extensive AI legislation, and strengthening international cooperation. The study concludes with the following recommendations for improving Vietnam’s AI policy: implementing a strong AI governance structure and supporting AI education and awareness.

This research investigates the impact of digital academic supervision (DAS) on teacher professionalism (TP), with a focus on the mediating role of personal learning networks (PLNs) and their implication for educational policy. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), data were collected from 276 teachers in prestigious secondary schools in East Java, Indonesia. The study uses a regression model design to explore direct and mediated effects between DAS, PLNs, and TP. Findings demonstrate that DAS directly impacts both PLNs (0.638) and TP (0.550), while PLNs also directly influence TP (0.293). Mediated analysis indicates that DAS enhances TP through PLNs (0.187). These results underscore the importance of digital tools in academic supervision, fostering collaboration, and promoting teacher professional development. The empirical evidence supports the effectiveness of DAS in enhancing teacher professionalism, suggesting significant implications for educational policy and practice in Indonesia in terms of regulatory framework, such as data privacy and security, standardization, training programs, and certification and accreditation.