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.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.

Studies show that Fourth Industrial Revolution (4IR) technologies can enhance compliance with COVID-19 guidelines within the parties in the construction industry in the future and mitigate job loss. It implies that mitigating job loss improves the achievement of Sustainable Development Goal 1 (SDG 1) (eliminate poverty). There is a paucity of literature concerning 4IR technologies application and COVID-19 impact on South Africa’s construction industry. Thus, this paper investigates the impacts of the pandemic on the sector and the roles of digital technologies in mitigating job loss in future pandemics. Data were collected via virtual semi-structured interviews. The participants proffered unexplored insights into the impact of the pandemic on the sector and the possible roles that 4IR technology can play in mitigating the spread of the virus within the sector. Findings show that the sector was hit, especially the low-income earners, threatens to achieve Goal 1, despite government institutions’ intervention, such as economic support programmes, health and safety guidelines awareness, and medical facilities. Findings group the emerged impacts into health and safety, environmental, economic, productivity, social, and legal and insurance issues in South Africa. The study shows that technology can be advantageous to improving achieving Goal 1 in a pandemic era due to limited job loss.

When COVID-19 hit all the Asian countries, Indonesia issued various laws and regulations. This study investigates these laws that do not improve the country’s ability to increase its adaptive structuration and foresight-oriented investment. It analyzes all the new laws, which should be based on the requirements of both concepts. It considers that all the laws are intended to defend the Government of Indonesia’s economic performance (GoI). It means that all the established regulations were built on the premise that they only focused on national economic preservation, especially economic growth. In other words, this study stated that the absence of regulations containing adaptive restructuration and foresight-oriented investment would decrease the state’s agility. This absence potentially impacts Indonesia to zcategorize the future as the state’s political failure. It shows evidence that Indonesia could not enforce and empower its structural potential. This study indicates that Indonesia made no foresight-oriented investment to cover the disbursed costs due to the COVID-19 pandemic. Future policies should be improved by including growth opportunities to enhance Indonesia’s agility. This agility could finally be achieved when all the laws issued by the GoI do not contain the praxis.

The article analyzes the process of formation of research universities as one of the elements of a strong innovation economy. The formation of a new university model is a global trend, successfully implemented in English-speaking countries. In Russia, the educational system is not yet ready to ensure the country’s effective competition in the innovation market. The Strategic Academic Leadership Program “Priority-2030” is designed to carry out the functional transformation of the entire infrastructure of human capital reproduction in a short period of time in Russia. The article presents an analysis of the main conditions for the development of a university with a research strategy, as well as an assessment of the implementation of this strategy by Moscow Polytechnic University. The methodological basis of the study was formed by qualitative methods: included observation and benchmarking of universities’ activities, which allowed to generalize the current global trends and best practices in the field of education. For the analysis we used the data of monitoring the activities of higher education organizations, data of official statistics, as well as data from reports and presentation materials of universities and online publications participating in the “5-100” and “Priority-2030” programs. The results of the study may be useful for researchers and practitioners engaged in the transformation of the Russian higher education system.