The issue of energy has been debated among policymakers and economists. Energy plays an important role in generating economic activities. On the other hand, it can have deleterious impacts on the environment as more carbon dioxide (CO₂) emissions will be released. Most previous studies focused on total energy rather than types of energy such as oil and gas in investigating the effects of energy consumption on CO₂ emissions. Therefore, this study investigates the effects of oil and gas consumption rather than total energy consumption on CO₂ emissions in 20 Organization of Islamic Cooperation (OIC) countries. The dynamic heterogeneous panel (panel autoregressive distributed lag model – panel ARDL) approach namely pooled mean group (PMG), mean group (MG), and dynamic fixed effect (DFE) were employed. The main results reveal that in the long run, overall national output contributes to higher environmental degradation. However, in the short run, overall national output does not affect CO₂ emissions. The results also suggest that the population can reduce CO₂ emissions in the short run but leaves no effect in the long run. Besides, gas consumption and oil consumption can have deleterious effects on the environment. The effect of oil consumption is greater than the effect of gas consumption on the environment. Therefore, it is important to consume more renewable energy such as solar, biodiesel, and hydro to replace non-renewable energy, particularly oil, in a bid to conserve the environment.

The pressing global effort to tackle CO₂ emissions has brought about a strong emphasis on adopting green technology by economies striving for low-carbon development. Within this context, this research investigates the environmental significance of green technology and exports in Malaysia. By examining 30-year data from 1989 to 2019 and utilising the autoregressive distributed lag model (ARDL), this study explores these variables' long-run and short-run effects on Malaysia's environment. The outcomes reveal noteworthy insights: population growth and green technology negatively impact environmental degradation, whereas exports and economic expansion contribute to environmental depletion over the long term. However, the influences of a higher population and exports are inconsequential in the short term. Additionally, the study captures the influences of transient economic challenges, such as the COVID-19 outbreak. Consequently, the study emphasises crucial policy implications for the Malaysian government. Firstly, it strongly recommends increasing investment in sustainable technology, especially within the manufacturing sector, to mitigate the adverse environmental impact of exports. Furthermore, it suggests incentivizing companies to embrace green technology through subsidies for acquiring renewable energy and imposing higher taxes on non-renewable energy sources. Additionally, policymakers are urged to prioritise human capital development by raising public awareness about the dangers of heightened CO₂ emissions. Malaysia can leverage its expertise to foster economic expansion without compromising the environment by engaging the working population in environmentally sustainable economic activities. These policy recommendations aim to expedite the shift towards a decarbonised economy, promote sustainable development, and safeguard Malaysia's natural resources.

Foreign direct investment (FDI) can boost economic growth and provide job opportunities. FDI inflows in ASEAN+3 countries have dropped markedly, which may affect economic development in the region. Many previous studies have investigated a multitude of factors that can influence FDI, such as market size, inflation, trade openness, corruption, and inflation. Previous studies did not, however, consider environmental degradation as a potential factor. Besides corruption and inflation, imposing stringent environmental regulations, such as carbon pricing and taxes to reduce environmental degradation, might deter foreign investors from the country. This is due to heightened costs for foreign investors, which may cause FDI inflows to drop. To shed some light on the reality of this situation, this study examines whether environmental degradation can significantly affect foreign direct investment in the region. This study includes environmental degradation as a potential factor and employs the panel ARDL approach to analyse data from 1995 to 2019. Results show that environmental degradation, infrastructure, and corruption can affect the inflow of FDI in the long run. In the short run, inflation can affect FDI. The findings of this study can be utilized by policymakers in formulating the right policies to attract more investors. An increase in infrastructure facilities should be considered to attract more foreign investment. It is also vital for governments to reduce corruption and inflation to attract more FDI inflows. Environmental incentives should also be introduced to ensure that attempts to reduce environmental degradation do not affect FDI inflows.

This article explores how Artificial Intelligence (AI) transforms workforce optimization in logistics and supply chain operations. By integrating technologies like machine learning, predictive analytics, robotic process automation, natural language processing, computer vision, and digital twins, organizations can shift from manual, reactive workforce planning to proactive, data-driven strategies. AI enables dynamic scheduling, real-time task reassignment, predictive labor forecasting, and continuous performance monitoring, improving efficiency and reducing costs. The article also addresses ethical concerns such as transparency, bias, and privacy, and outlines key implementation challenges including data quality, employee resistance, and digital skills gaps. Ultimately, it argues that AI is not just a tool for automation but a catalyst for strategic transformation, helping organizations create agile, resilient, and human-centered workforce ecosystems suited for today's complex supply chain landscape.

Reduced life expectancy is the result of various factors, including income inequality, poverty, inadequate access to education and healthcare facilities, poor governance, pollution, climate change-related risks, natural disasters, and a lack of access to clean water and sanitation. The purpose of this study is to examine the impacts of socioeconomic, political, and environmental factors on life expectancy in the selected ASEAN+3 countries between 1995 and 2021. This study utilised the panel static method (pooled ordinary least square, fixed effect, and random effect), and the Hausman test will be used to select the appropriate estimator. The results indicate that both models demonstrate significant negative effects of the corruption perception index and CO₂ emissions on life expectancy. However, labour income shows a positive and significant association with life expectancy in both models. Moreover, in developed countries, there is a positive and significant impact on life expectancy due to the interaction between the dummy country and the corruption perception index. Therefore, it is important to implement policies that promote the equitable distribution of wealth and ensure access to essential resources and services for all individuals. To ensure the efficient allocation of resources, promote accountability, and increase public trust in healthcare systems, it is necessary to implement effective governance procedures, increase transparency, and combat corruption. Enforcing environmental regulations to reduce pollution levels and promoting sustainable development practices are crucial. Besides, implementing measures to mitigate the impacts of climate change, including adaptation strategies and transitioning towards cleaner and renewable energy sources, is essential.