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South Asia is one of the fastest-growing regions in the world. With its fast economic development, the energy requirement for the region has rapidly grown. As the region relies mainly on nonrenewable energy sources and is suffering from issues like pollution, the high cost of energy imports, depleting foreign reserves, etc. it is searching for those factors that can help enhance the renewable energy generation for the region. Thus, taking these issues into consideration, this paper aims to investigate the impact of macroeconomic factors that can contribute to the enhancement of renewable energy output in South Asia.

An autoregressive distributed lag methodology has been applied to examine the long-term effects of remittance inflows, literacy rate, energy imports, government expenditures and urban population growth on the renewable energy output of South Asia by using time series data from 1990 to 2021.

The findings indicated that remittance inflows have a negative and insignificant long-term effect on renewable electricity output. While it was discovered that energy imports, government spending and urban population growth have negative but significant effects on renewable electricity output, literacy rates have positive and significant effects.

Considering the importance of renewable energy, this is one of the few studies that has included critical macroeconomic variables that can affect renewable energy output for the region. The findings contribute to the body of knowledge that a high literacy level is crucial for promoting renewable energy output, while governments and policymakers should prioritize reducing energy imports and ensuring that government expenditures on renewable energy output are properly used. SAARC, the governing body of the region, also benefits from this study while devising the renewable energy output policies for the region.

Energy security has been talked about by governments and policymakers because the global energy market is unstable and greenhouse gas emissions threaten the long-term health of the global environment. One of the most potent ways to cut CO₂ emissions is through the production and consumption of renewable energy. Thus, the purpose of this paper is to highlight the drivers that, if ambitious environmental policies are implemented, might improve energy security or prevent its deterioration.

The study uses a balanced panel data set for Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam that covers a period of 30 years (1990–2020). The pooled panel dynamic least squares is used in this study.

The findings show that renewable energy consumption is positively related to gross domestic product per capita, energy intensity per capita and renewable energy installed capacity. Wherein renewable energy use is inversely related to per capita electricity consumption, CO₂ emissions and the use of fossil fuel electricity.

There is a lack of research identifying the factors influencing energy security in the ASEAN region. Therefore, this study focuses on the drivers that influence energy security, which are explained by the proportion of renewable energy in final energy consumption. Without identifying the demand and supply sources of energy, especially electricity production based on renewable energy techniques, it is hard for policymakers to achieve the desired renewable energy-based outcome.

This study aims to examine the effect of governance on the consumption of modern renewable energy in the East African Community (EAC), controlling for economic growth, trade openness and foreign direct investment (FDI).

The study relied on secondary data sourced from the World Development Indicators, World Governance Indicators and the International Energy Agency (IEA) for the EAC from 1996 to 2019. A panel Cross-Sectional Augmented Distributed Lag (CS-ARDL) model and second-generation panel data models were employed in the analysis.

The findings indicate that poor governance and inadequate FDI are significantly responsible for the low level of modern renewable energy consumption (MREC) in the EAC. On the other hand, trade openness significantly enhances MREC, while GDP per capita has no significant effect on MREC.

The consumption of modern renewable energy sources (excluding the traditional use of biomass) and its determinants, as most studies focus on renewable energy consumption as a whole. The study also employed the panel CS-ARDL model and second-generation panel data models.

Due to an increase in energy demands, it has become vital to devise efficient energy policies. Literature has suggested multiple factors influencing the consumption of specific energy types. Among others, institutional quality (INQ) is another factor that can determine energy consumption. Given this, the current study aimed to investigate the impact of INQ on fossil fuel energy (FFE) and renewable energy consumption (REC).

The empirical analysis was conducted on 20 years (2000–2019) of data from South Asian economies, and regression among variables was established by employing the dynamic ordinary least square and fully modified ordinary least square models. The selection of both techniques is subject to the existence of cointegration identified by the Johansen cointegration test. Other pre-estimation techniques include cross-section dependence and unit root testing validating the estimation of coefficients in the long run.

The analysis mainly reveals the negative impact of INQ on FFE and the positive impact of INQ on REC. The authors further find the asymmetric impact of control variables including foreign direct investment inflow, economic growth, inflation rate, financial sector development and energy investment on the consumption of both types of energy.

Given the positive influence of INQ on REC, it is recommended to focus on improving the efficiency of institutions specifically those that are directly linked with energy-related policies. A better INQ can ensure environmental sustainability by enhancing the consumption of renewable energy. Therefore, it is advised to exert more efforts to improve the INQ.

In view of the positive influence of INQ on REC, it is recommended to focus on improving the efficiency of institutions specifically that are directly linked with energy-related policies. A better INQ can ensure environmental sustainability by enhancing the consumption of renewable energy. Therefore, it is advised to exert more efforts for improving the INQ.

This study offers robustness to the empirical findings of existing literature on the INQ-REC nexus and complements the underdeveloped literature on the INQ-FFE relationship.

This study aims to investigate the effect of oil prices, economic growth and information communication technology (ICT) on investment into renewable energy transition (RET).

Based on six selected African countries (i.e. Algeria, Egypt, Angola, Ethiopia, South Africa and Nigeria), the study uses a nonlinear autoregressive distributed lag model over the period from 1995 to 2020.

The results show that increasing oil prices, by substitution effect, leads to increasing RET investment, while declining oil prices lead to decreasing RET investment in the short and long run. Furthermore, the results reveal that increasing real gross domestic product leads to increased RET investment, while declining real gross domestic product (GDP) leads to decreasing RET investment both in the short and long run. Simultaneously, the study shows that increasing ICT has a significant and positive impact on RET investment, while declining ICT has a significant negative impact on RET investment in the short and long run.

The findings of this study have advanced the understanding of which factors significantly influence RET investment and the need to concentrate efforts on strategically addressing those factors. The findings indicate that these countries are at the progressive stage in terms of renewable energy; though increasing oil prices contribute to rising RET investment, the countries can be more proactive by improving the full potential of ICT as well as facilitating the growth of their economies.

The Organization for Economic Cooperation and Development (OECD) countries are facing unprecedented challenges related to climate change and population aging. The purpose of the analysis is to explore the relationship between population aging and environmental degradation, accounting for human capital, using a sample of 19 OECD countries over the period 1980–2019.

On the empirical methodology, the analysis uses panel estimators with heterogenous coefficients and an error structure that takes into consideration cross-country heterogeneity and cross-sectional dependence for a panel of 19 OECD countries over the period 1980–2019. To examine the relationship between population aging and environmental degradation, the authors employ two alternative measures of environmental degradation that is energy consumption and CO2 emissions in metric tons per capita. Concerning the regressors, the authors account for two alternative aging indicators, namely the elderly population and the old-age dependency ratios to confirm robustness.

The analysis provides evidence that population aging and human capital development (IHC) lead to lower energy consumption in the OECD sample. Overall, the growing number of elderly people in the OECD seems to act as a mitigating factor for energy consumption. The authors view these results as conveying the message that the evolution of population aging along with channeling government expenditures towards human capital enhancement are important drivers of curbing energy consumption and ensuring environmental sustainability. The authors' research is of great significance for environmental policymakers by illuminating the favorable energy consumption patterns that population aging brings to advanced economies.

The main limitation of this study concerns data availability. Future research, and subject to greater data availability in the future, could dig deeper into understanding the dynamics of this complex nexus by incorporating additional control variables. Similarly, the authors focus on aggregate renewable energy consumption, and the authors do not explicitly model the sources of renewable energy (wind, hydropower, solar power, solid biofuels and other). Additional analysis of the breakdown of renewable energy sources would be insightful – subject to data availability – especially for meeting the recently agreed new target of 42.5% for European Union (EU) countries by 2030. A deep transformation of the European energy system is needed for the EU to meet the target. Finally, extending the model to include a range of non-OECD countries that are also experiencing demographic transformations is a promising avenue for future research.

To the best of the authors' knowledge, this study is the first to examine the effects of population aging and human capital on environmental degradation using a broad set of OECD countries and advanced spectrum estimation methods. Given cross-sectional dependencies and cross-country heterogeneity, the authors' empirical results underline the importance of cross-OECD policy spillovers and knowledge diffusions across the OECD countries. The new “energy culture” calls for concerted policy action even in an aging era.

The intensity of carbon emissions has led to the serious problem of global warming, and the consequences in terms of climatic disasters are gaining increasing attention worldwide. As the energy sector is responsible for most global emissions, developing clean energy is crucial to combat climate change. This study aims to examine the relationship between corporate governance and renewable energy (RE) consumption and explore the interaction between RE production and RE use.

The study adopts an econometric framework of a panel model, followed by the robustness check using alternative methods, including logit regressions. The bivariate probit model is used to analyze the interaction between the decision to use and the decision to produce RE. The analysis is based on a sample of 3,896 firms covering 45 countries worldwide.

The results reveal that appropriate governance mechanisms positively impact RE consumption. These include the existence of a sustainability committee; environmental, social and governance-based compensation policy; financial performance-based compensation; sustainability external audit; transparency; board gender diversity; and board independence. Firms with appropriate governance mechanisms are more likely to produce and use RE than others. Finally, while RE use positively impacts firm value and environmental performance, the authors find no significant effect on current profitability.

This study goes beyond previous research by exploring the impact of multiple governance mechanisms. To the best of the authors’ knowledge, this is also the first study examining the relationship between RE use and firm value. Overall, the findings suggest that RE transition requires, first of all, establishing appropriate governance mechanisms within companies.

The purpose of this study is to propose a new mapping tool called Circular Value Stream Mapping (C-VSM) that combines Circular Economy principles with Lean tools to enhance sustainability performance in operations.

To develop the C-VSM tool, the researchers conducted a literature review and a focus group. The tool was then applied to two real case studies in the agri-food sector, specifically analyzing an artichoke and olive oil producer, to assess its validity and effectiveness.

The study introduces the Circular Resource Box (CRB) as a key innovation in the C-VSM tool. This visual representation effectively captures resource circularity and how resources and wastes are managed, making it easy to identify circularity in the production process. By combining qualitative and quantitative information with this visual representation, companies can identify improvement opportunities aligned with the CE.

The research is limited in scope as it focuses on the application of the C-VSM tool in the agri-food sector. Further research could explore its applicability in other industries and settings to understand its broader impact.

The C-VSM tool provides practical benefits to companies seeking to transition from linear to circular production processes. It enables practitioners to identify opportunities to reduce environmental impacts and optimize production operations in line with CE.

The introduction of the C-VSM tool is a novel approach that bridges the gap between Lean Manufacturing and CE concepts, advancing the understanding of how CE thinking can be effectively implemented in operations.

The present study identifies the factors that impact behavioral intentions to adopt solar water heaters (SWHs) and examines their relationship with behavioral intentions using an extended “Unified Theory of Acceptance and Use of Technology” (UTAUT) model.

The study used a primary survey to collect data from 423 respondents across seven Indian states selected through purposive sampling. The collected data was analyzed using IBM SPSS software and “Structural Equation Modeling” (SEM) was performed using SmartPLS 3.5.5.

The results suggest that social influence is the most significant factor affecting SWH adoption, followed by effort, performance expectancy and facilitating conditions. The perceived cost negatively affects behavioral intentions and social influence on behavioral intentions is partially mediated by facilitating conditions. People prefer SWHs if they are easy to install and compatible with other home appliances. Positive perception of friends and family, easy access and government incentives contribute to SWH adoption.

SWH adoption can be promoted by designing sector-specific programs and improving ease of installation, operation, maintenance and after-sale services.

This study explores the behavioral intentions of individuals in India to adopt SWHs. India is a developing tropical country with a high potential for SWH adoption but has not received much attention. Further, the research integrates the perceived cost construct in the UTAUT model and examines the partial mediation impact of facilitating conditions to improve the model’s comprehensibility.

Switching power converters for photovoltaic (PV) applications with high gain are rapidly expanding. To obtain better voltage gain, low switch stress, low ripple and cost-effective converters, researchers are developing several topologies.

It was decided to use the particle swarm optimization approach for this system in order to compute the precise PI controller gain parameters under steady state and dynamic changing circumstances. A high-gain q- ZS boost converter is used as an intermittent converter between a PV and brushless direct current (BLDC) motor to attain maximum power point tracking, which also reduces the torque ripples. A MATLAB/Simulink environment has been used to build and test the positive output quadratic boost high gain converters (PQBHGC)-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. The simulation results show that the PQBHGC-3 topology is effective in comparison with other HG cell DC–DC converters in terms of efficiency, reduced ripples, etc. which is most suitable for PV-driven BLDC applications.

The simulation results have showed that the PQBHGC-3 gives better performance with minimum voltage ripple of 2V and current ripple of 0.4A which eventually reduces the ripples in the torque in a BLDC motor. Also, the efficiency for the suggested PQBHGC-3 for PV-based BLDC applications is the best with 99%.

This study is the first of its kind comparing the different topologies of PQBHGC-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. This study suggests that the PQBHGC-3 topology is most suitable in PV-driven BLDC applications.