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.

Indonesia has experienced problems with refugees in recent years. Despite not being a state party to the 1951 Refugee Convention, Indonesia is still subject to the principle of non-refoulement as a norm that binds all states (jus cogens). This principle is regulated in Presidential Regulation Number 125 of 2016 and Regulation of the Director General of Immigration of 2016 as basic regulations for handling refugees. However, the principle of non-refoulement is not applied absolutely to refugees in Indonesia. The government is in a difficult situation and seems hesitant in taking a legal political stance, to accept or expel the presence of refugees. This research article aims to evaluate the application of the principle of non-refoulement in Indonesian national law. The findings of this research show that the state cannot apply the principle of non-refoulement to refugees in an absolute manner as it will have an impact on national security stability. The legal position of the Presidential Regulation and the Regulation of the Director General of Immigration contradict other regulations, potentially leading to norm conflicts and legal uncertainty. This regulation cannot be applied in all situations. Although this regulation is binding, its application is highly dependent on the needs and urgency of the country. The principle of non-refoulement does not apply to refugees if their presence threatens national security or disturbs public order in transit countries, especially for Indonesia, which has not ratified the 1951 Refugee Convention. Normatively, the application of this principle can be limited by the Constitution, Immigration Law, the theory of state sovereignty, the theory of primordial monism of national law, the principle of selective immigration policy, the principle of immigration essence, and the principle of immigration traffic control. This provision emphasizes that the application of this principle is relative and can be limited based on state sovereignty and national security interests.

The Malaysian dilemma presents a complex challenge in the wake of the COVID-19 pandemic, requiring a comprehensive statistical analysis for the formulation of a sustainable economic framework. This study delves into the multifaceted aspects of reconstructing Malaysia’s economy post-COVID-19, employing a data-driven approach to navigate the intricacies of the nation’s economic landscape. The research focuses on key statistical indicators, including GDP growth, unemployment rates, and inflation, to assess the immediate and long-term impacts of the pandemic. Additionally, it examines the effectiveness of government interventions and stimulus packages in mitigating economic downturns and fostering recovery. A comparative analysis with pre-pandemic data provides valuable insights into the extent of economic resilience and identifies sectors that require targeted support for sustained growth. Furthermore, the study explores the role of technology and digital transformation in building a resilient economy, considering the accelerated shift towards remote work and digital transactions during the pandemic. The analysis incorporates data on technological adoption rates, digital infrastructure development, and innovation ecosystems to gauge their contributions to economic sustainability. Addressing the Malaysian Dilemma also involves an examination of social and environmental dimensions. The study investigates the impact of economic policies on income distribution, social equity, and environmental sustainability, aiming to achieve sustainable economic growth. The study contributes a nuanced analysis to guide policymakers and stakeholders in constructing a sustainable post-COVID-19 economy in Malaysia.

Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.

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.

Every sector must possess the ability to identify potential dangers, assess associated risks, and mitigate them to a controllable extent. The mining industry inherently faces significant hazards due to the intricate nature of its systems, processes, and procedures. Effective risk control management and hazard assessment are essential to identify potential adverse events that might lead to hazards, analyze the processes by which these occurrences may transpire, and estimate the extent, importance, and likelihood of negative consequences. (1) The stage of industrial hazard analysis assesses the capability of a risk assessment process by acknowledging that hidden hazards have the potential to generate dangers that are both unknown and beyond control. (2) To mitigate hazards in mines, it is imperative to identify and assess all potentially dangerous circumstances. (3) Upon conducting an analysis and evaluation of the safety risks associated with identified hazards, the acquired knowledge has the potential to assist mine management in making more informed and effective decisions. (4) Frequently employed methods of data collection include interrogation of victims/witnesses and collection of information directly from the accident site. (5) After conducting a thorough analysis and evaluation of the safety hazards associated with hazard identification, the dataset has the potential to assist mine management in making more informed decisions. The study highlights the critical role of management in promoting a strong safety culture and the need for active participation in health and safety systems. By addressing both feared and unknown risks, educating workers, and utilizing safety-related data more effectively, mining companies can significantly improve their risk management strategies and ensure a safer working environment.