This study evaluates the effectiveness of Indonesia’s defense industry policy from 2018 to 2023, focusing on PT Pindad, a pivotal state-owned defense enterprise. Using a Balanced Scorecard (BSC) framework, the study assesses PT Pindad’s performance across financial, customer, internal process, and learning and growth perspectives. The findings reveal strengths in financial stability (Current Ratio at 115.57% in 2023) and customer satisfaction, but challenges in Return on Investment (ROI), which fell from 6% in 2022 to 5.46% in 2023, signaling a need for further internal improvements. A mediation analysis using Shape-Restricted Regression indicates that Research and Development (R&D) serves as a crucial mediator, enhancing the impact of strategic alliances and technology transfer on PT Pindad’s self-reliance, with R&D showing a positive coefficient of β = 0.53 (p < 0.01). The systematic literature review complements these findings, underscoring the role of technology transfer, human capital development, and strategic partnerships as essential components for strengthening PT Pindad’s self-reliance and global competitiveness. Recommendations are made to enhance policy effectiveness by fostering robust technology transfer mechanisms, increasing investment in human capital, and expanding strategic partnerships. This research contributes to the literature on defense industry policies by providing a comprehensive evaluation framework that informs future policy decisions.

The multifaceted nature of the skills required by new-age professions, reflecting the dynamic evolution of the global workforce, is the focal point of this study. The objective was to synthesize the existing academic literature on these skills, employing a scientometric approach . This involved a comprehensive analysis of 367 articles from the merged Scopus and Web of Science databases. Science. We observed a significant increase in annual scientific output, with an increase of 87.01% over the last six years. The United States emerged as the most prolific contributor, responsible for 21.61% of total publications and receiving 34.31% of all citations. Using the Tree algorithm of Science (ToS), we identified fundamental contributions within this domain. The ToS outlined three main research streams: the convergence of gender, technology, and automation; defining elements of future work; and the dualistic impact of AI on work, seen as both a threat and an opportunity. Furthermore, our study explored the effects of automation on quality of life, the evolving meaning of work, and the emergence of new skills. A critical analysis was also conducted on how to balance technology with humanism, addressing challenges and strategies in workforce automation. This study offers a comprehensive scientometric view of new-age professions, highlighting the most important trends, challenges, and opportunities in this rapidly evolving field.

Fog computing (FC) has been presented as a modern distributed technology that will overcome the different issues that Cloud computing faces and provide many services. It brings computation and data storage closer to data resources such as sensors, cameras, and mobile devices. The fog computing paradigm is instrumental in scenarios where low latency, real-time processing, and high bandwidth are critical, such as in smart cities, industrial IoT, and autonomous vehicles. However, the distributed nature of fog computing introduces complexities in managing and predicting the execution time of tasks across heterogeneous devices with varying computational capabilities. Neural network models have demonstrated exceptional capability in prediction tasks because of their capacity to extract insightful patterns from data. Neural networks can capture non-linear interactions and provide precise predictions in various fields by using numerous layers of linked nodes. In addition, choosing the right inputs is essential to forecasting the correct value since neural network models rely on the data fed into the network to make predictions. The scheduler may choose the appropriate resource and schedule for practical resource usage and decreased make-span based on the expected value. In this paper, we suggest a model Neural Network model for fog computing task time execution prediction and an input assessment of the Interpretive Structural Modeling (ISM) technique. The proposed model showed a 23.9% reduction in MRE compared to other methods in the state-of-arts.

This paper investigates the potential of a concept for the commercial utilization of surplus intermittent wind-generated electricity for municipal district heating based on the development of an electric-driven heat storage. The article is divided into three sections: (1) A review of energy storage systems; (2) Results and calculations after a market analysis based on electricity consumption statistics covering the years 2005–2013; and (3) Technology research and the development of an innovative thermal energy storage (TES) system. The review of energy storage systems introduces the basic principles and state-of-the-art technologies of TES. The market analysis describes the occurrence of excess wind power in Germany, particularly the emergence of failed work and negative electricity rates due to surplus wind power generation. Based on the review, an innovative concept for a prototype of a large-scale underwater sensible heat storage system, which is combined with a latent heat storage system, was developed. The trapezoidal prism-shaped storage system developed possesses a high efficiency factor of 0.98 due to its insulation, large volume, and high rate of energy conversion. Approximate calculations showed that the system would be capable of supplying about 40,000 people with hot water and energy for space heating, which is equivalent to the population of a medium-sized city. Alternatively, around 210,000 inhabitants could be supplied with hot water only. While the consumer´s costs for hot water generation and space heating would be lowered by approximately 20.0–73.4%, the thermal energy storage would generate an estimated annual profit of 3.9 million euros or more (excluding initial costs and maintenance costs).

The effects of aid dependency on preventing the achievement of sustainable development in Africa has not been given appropriate academic attention. Aid dependency in Africa is undoubtedly among the most factors that have promoted poverty and underdevelopment. Aid dependency which hindered the growth of local innovation, promoted divisions that has affected good governance for sustainable development. Aid dependency has promoted chronic poverty, mental laziness and unstable health and well-being. It has ignited unhealthy condition that has created a perpetual vicious cycle of poverty that prevents the achievement of sustainable development. The study found that planning diplomacy can serve as a solution to aid diplomacy and address its effects thus promoting the achievement of sustainable development. Planning diplomacy was found to have critical links with Africa’s communalism theory, thus making it an ideal approach to addressing the effects of aid dependency in Africa. Planning diplomacy was found to promote local and business in collective manner. It is through this collective approach that sustainable development can be achieved in Africa. Planning diplomacy was found a key for sustainable development because it makes good use of foreign aids, promotes local ownership thus strengthens sustainable economic growth and development that makes sustainable development achievable. Planning diplomacy was equally found a remedy to aid dependency because it enhances knowledge and skills transfer. Knowledge and skills transfer promotes sustainable development because it facilitates sharing of skills that brings innovation and technologies to local citizens in a collective manner. The study adopted a qualitative research methodology with the use of secondary data collected from existing literature published in the public domain. Collected data was analysed and interpreted through document analysis technique.   

The food supply chain in South Africa faces significant challenges related to transparency, traceability, and consumer trust. As concerns about food safety, quality, and sustainability grow, there is an increasing need for innovative solutions to address these issues. Blockchain technology has emerged as a promising tool to enhance transparency and accountability across various industries, including the food sector. This study sought to explore the potential of blockchain technology in revolutionizing through promoting transparency that enable the achievement of sustainable food supply chain infrastructure in South Africa. The study found that blockchain technology used in food supply chain creates an immutable and decentralized ledger of transactions that has the capacity to provide real-time, end-to-end visibility of food products from farm to table. This increased transparency can help mitigate risks associated with food fraud, contamination, and inefficiencies in the supply chain. The study found that blockchain technology can be leveraged to enhance supply chain efficiency and trust among stakeholders. This technology used and/or applied in South Africa can reshape the agricultural sector by improving production and distribution processes. Its integration in the food supply chain infrastructure can equally improve data management and increase transparency between farmers and food suppliers.There is need for policy-makers and scholars in the fields of service delivery and food security to conduct more research in blockchain technology and its roles in creating a more transparent, efficient, and trustworthy food supply chain infractructure that address food supply problems in South Africa. The paper adopted a qualitative methodology to collect data, and document and content analysis techniques were used to interpret collected data. 

The aim was to examine the relationships between selected demographic and psychographic factors and consumers' willingness to accept content generated by advanced technological innovations (AIGC) in social infrastructure. The sample consisted of 1,308 respondents. Spearman's correlation coefficient was used to examine the relationships between ordinal variables. To assess the differences between groups of respondents, a one-way analysis of variance was used, during which multiple linear regression analysis was used to confirm the predictive power of awareness and experience in relation to AI-generated content in relation to the tendency to accept such content. The study confirmed a statistically significant but weak negative relationship between the age of respondents and their willingness to accept AIGC, with younger age groups showing a slightly higher rate of acceptance. Respondents' attitudes toward the use of personal data through AI and their overall awareness of technological trends had a more significant impact on acceptance. The findings show that respondents who are open to data collection through AI technologies show a significantly higher level of acceptance of automatically generated content. Similarly, respondents who positively evaluate the current quality of AIGC have higher expectations for the future transformation of marketing strategies and media practices. The decisive factors in the social infrastructure for the acceptance of AIGC are not so much the age of the respondents, but rather their awareness, technological literacy, and level of trust in the technology itself. The study therefore recommends increasing transparency and public awareness about the use of AI in marketing and media practices in order to strengthen consumer confidence in automated content.