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The outbreak and the spreading of the COVID-19 pandemic have impacted the global financial sector, including the alternative clean and renewable energy sector. This paper aims to assess the impact of the pandemic, COVID-19 on the stock market indices of the clean energy sector using quantile regression methods.

This study utilized daily data sets on the four major categories of stocks: (1) Morgan Stanley Capital International Global Alternative Energy Index, (2) WilderHill Clean Energy Index, (3) Renewable Energy Industrial Index (RENIXX) and (4) the S&P 500 Global Clean Index. The study adopts a multifactor capital asset pricing model.

Clean and alternative energy stocks are powerful instruments for diversification. However, the impact of the volatility index induced by infectious disease is negative and significant across quantiles.

For investors and policymakers, considering how the uncertainty caused by COVID-19 and the geopolitical index influences renewable energy markets is of great practical importance. For investors, it throws insights into portfolio diversification. For policy makers, it helps to devise strategies to reboot the economy along the lines of the deployment of renewables. This study sheds light on a global green-energy transition and has practical implications for renewable energy resilience in post-pandemic times.

This paper can be considered as a pioneer that explores the nexus between oil prices, interest rates, volatility index, and geopolitical risk upon the stock indices of clean and alternative sources of (renewable) energy in the COVID-19 pandemic situation. The results have important insights into the area of energy and policy decision-making. Additionally, the paper's novelty lies in using the explanatory variables associated with the Covid 19 pandemic.

This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.

The study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.

The study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.

The study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

The purpose of this study is to examine households’ behavior towards dirty cooking energy utilisation in an environment where relatively higher accessibility to clean energy is noted. Although the low utilisation rate of clean energy can partly be attributed to utility gains anticipated in dirty energy mixes (DEMs) arising out of accessibility constraints, affordances and enablers, it is still unclear on the extend at which each of these contributes towards DEMs manifestation among the seemingly well-to-do households with higher levels of clean energy mixes (CEM) access. This study, therefore, hinges on scrutinising on this lower utilisation patterns despite a seemingly higher accessibility of CEMs, specifically liquified petroleum gases (LPG).

The study is based on a household’s survey that was carried out in 2018, reaching a sample of 393 households using questionnaires in four wards of the Kigamboni district in Tanzania. Subsequent analyses were descriptive as well as inferential based on binary logistic regression analysis where utilisation of DEMs was predicted for both the high and low social economic status (SES) households by incorporating accessibility constraints, affordances and enablers.

The results show, first, if one assumes energy stacking is not an issue, as households become more constrained towards CEMs utilisation, they shift towards DEMs suggesting that the overall effect is a substitution, and second, the complementarity effect ultimately outweighs the substitution effect as households do not shift from DEMs to CEMs rather stack multiple energy. DEMs flourish in this case study area because those with high income are among those in the lowest SES, and some of those with the highest SES are from among the lowest income category, and all of them end up with more DEMs because shifting towards CEMs require income to complement SES.

Policy-wise, removing hurdles in accessing CEMs such as LPG subsidy programme, gas stove provision to the poor, and enhanced LPG awareness will most likely benefits only those who do not stack energy in cooking while strategies targeting those at the lowest SES such as higher education attainment, empower women as a family decision maker, encourage co-occupancy to enlarge the household size and contain urban growth within certain perimeter will have a significant impact only if they raise both incomes and SES.

Despite of the dominance of DEMs for cooking such as charcoal and firewood in Tanzania, CEMs such as LPG, have emerged as complements or alternatives in the household energy basket. The utilisation of such CEMs is, however, still very low despite the accessibility, cost, environmental and health advantages they offer. Accessibility is not the only factor fuelling CEMs; a complementarity must exist between SES and income for the positive transition towards CEMs to be realised.

The increased availability of reliable and efficient energy services stimulates new development alternatives. The purpose of this paper is to examine several issues relating to renewable energies, environment, and sustainable development, from both current and future perspectives.

Anticipated patterns of future energy use and consequent environmental impacts (acid precipitation, ozone depletion and the greenhouse effect or global warming) are comprehensively discussed in this article. An approach is needed to integrate renewable energies in a way to meet high building performance. However, because renewable energy sources are stochastic and geographically diffuse, their ability to match demand is determined by adoption of one of two approaches: the utilisation of a capture area greater than that occupied by the community to be supplied; or the reduction of the community ' s energy demands to a level commensurate with the locally-available renewable resources.

The adoption of green or sustainable approaches to the way in which society is run is seen as an important strategy in finding a solution to the energy problem. The key factors to reducing and controlling CO₂, which is the major contributor to global warming, are the use of alternative approaches to energy generation and the exploration of how these alternatives are used today and may be used in the future as green energy sources.

This study highlights the energy problem and the possible saving that can be achieved through the use of renewable energy technologies. Also, this study clarifies the background of the study, highlights the potential energy saving that could be achieved through use of renewable energy technologies and describes the objectives, approach and scope of the study.

As financial markets for environmentally friendly investment grow in both scope and size, analyzing the relationship between green financial markets and African stocks becomes an important issue. Therefore, this paper examines the role of infectious disease-based uncertainty on the dynamic spillovers between African stock markets and clean energy stocks.

The authors employ the dynamic spillover in time and frequency domains and the nonparametric causality-in-quantiles approach over the period of November 30, 2010, to August 18, 2021.

These findings are discernible in this study's analysis. First, the authors find evidence of strong connectedness between the African stock markets and the clean energy market, and long-lived but weak in the short and medium investment horizons. Second, the BDS test shows that nonlinearity is crucial when examining the role of infectious disease-based equity market volatility in affecting the interactions between clean energy stocks and African stock markets. Third, the causal analysis provides evidence in support of a nonlinear causal relationship between uncertainties due to infectious diseases and the connection between both markets, mostly at lower and median quantiles.

Considering the global and recent use of clean energy equities and the stock markets for hedging and speculative purposes, one may argue that rising uncertainties may significantly influence risk transmissions across these markets. This study, therefore, is the first to examine the role of pandemic uncertainty on the connection between clean stocks and the African stock markets.

The increasing use of complex, nonfinancial environmental performance measures in managerial decisions motivates consideration of contextual influences that potentially impact managerial judgments in environmental settings. This study extends general evaluability theory (GET: Hsee & Zhang, 2010) to environmental accounting by investigating the combined effects of evaluation mode and incomplete supplemental evaluability information (SEI; e.g., benchmark data) on management decisions. To elaborate, evaluation mode is the display format in which the accounting information system (AIS) provides available information for analysis; e.g., a manager’s or business unit’s performance is assessed either comparatively (i.e., in joint mode) or individually (i.e., in separate mode). GET suggests more decision weight on measures containing SEI in separate mode because that evaluation mode contains less context in which to analyze information. On the other hand, more decision weight should result for measures that do not contain SEI in joint mode because that mode already contains more context for analysis (e.g., comparing multiple performances with each other). To test these predictions, experimental participants (n = 53) evaluated environmental measures for factories with similar environmental performances. To operationalize the information available in many environmental AIS, some, but not all, performance measures contained benchmark data (incomplete SEI); factories were evaluated either jointly or separately. Participants evidenced decision intransitivity; i.e., in separate evaluation mode, factories rated higher when a favorable measure contained SEI, while in joint evaluation mode, factories rated higher when a favorable measure lacked SEI. The results extend previous AIS and management accounting research by investigating contextual influences, and potential systems design elements, in judgments using environmental AIS.

The purpose of this study is to explore the determinants influencing industrial adoption of green hydrogen amidst the global transition towards sustainability. Recognizing green hydrogen as a pivotal clean energy alternative for industrial applications is critical for understanding its potential integration into sustainable practices.

This research examines the impact of factors such as innovativeness, perceived ease of use, user comfort, optimism and governmental policies on the industrial intention towards green hydrogen usage. Using responses from 227 Indian industry professionals and conducting analysis via the SmartPLS software, the study reveals a discernible discomfort among industrial workers pertaining to the daily application of green hydrogen.

The research presents an array of policy recommendations for stakeholders. Emphasized strategies include the introduction of green hydrogen certificates, sustainable public procurement mechanisms, tax incentives, green labelling protocols and the establishment of a dedicated hydrogen skill development council, all of which can significantly influence the trajectory of green hydrogen adoption within the industrial sector.

This research synthesizes various elements, from industry perception and challenges to policy implications, presenting a holistic view of green hydrogen’s potential role in industry decarbonization and SDG realization. In essence, this study deepens not only the empirical understanding but also pioneers fresh theoretical frameworks, setting a precedent for subsequent academic endeavours.

The purpose of the present study is to investigate the community’s view of power outages and their effect on sustainable community development. This research has three aims. This project will first investigate how a blackout affects a community’s ability to live sustainably.

A survey questionnaire was developed that included 22 factors from the literature. The questionnaire was distributed to diversified segments of society from different regions of Pakistan and examined critical factors affecting sustainable community development. A total of 349 (77%) responses were received.

The study results confirm that power failure negatively affects the sustainable life of a community. This study found that the reduced production of large manufacturing, decrease leisure and comfort, reduced public administrative efficiency, loss of educational opportunities and increased use of traditional energy sources are the most important factors for sustainable community development. Findings also suggest that policymakers and practitioners in public organizations need to ensure that projects are completed in a timely manner to meet growing community needs.

The purpose of this research is to address knowledge gaps related to power outages and sustainable community development. The major impact of power disruptions on communities was previously disregarded in development discourse. Participants in these discussions recognize communities as genuine stakeholders and acknowledge that power outages can have a substantial impact on their economic and social development. However, previous studies have neglected to address this phenomenon.

The research is geared towards studying the impact of “GDP per capita (GDP)”, “energy consumption (EC)”, “human capital (HC)” and “trade openness (TO)” on India's ecological footprint (EF) from 1997–1998 to 2019–2020.

The autoregressive distributed lag model (ARDL) bound test was used to look at the short-run and long-term coefficients and the cointegration of the variables.

The results depicted a long-run connection between the variables. The long-run results found a favourable relationship between GDP, EC and EF, indicating that economic growth through heavy reliance on fossil fuels contributes to environmental unsustainability. An inverse relationship between HC, TO and EF was also observed, indicating that education fosters pro-environmental behaviour and leads to adopting cleaner technology that contributes to environmental sustainability.

The research substantiates India's pressing requirement for sustainable development, ensuring a harmonious balance between economic performance and environmental preservation. A carefully designed policy needs to be formulated to mitigate emissions stemming from growth in India. Policymakers are urged to implement measures that promote ecologically friendly tools, utilities and transportation to curb long-term environmental degradation.

The study is novel, incorporating an exhaustive review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study further examines how India's EF is affected by its HC; the preceding literature has yet to discuss much about the connection between HC and the environment. Finally, the study employed advanced econometric techniques, namely the cointegration technique and ARDL model, to find the relationship between EF, GDP, HC, EC and TO.

Nuclear energy investments contribute significantly to the energy independence of countries. This situation helps countries to develop both economically and socially. Therefore, countries need to develop strategies to increase their nuclear energy investments. However, radioactive waste generated in nuclear reactors is one of the most important disadvantages of this type of energy. Due to this situation, the wastes generated must be disposed of effectively for nuclear energy investments to be effective. In this study, it is aimed to create optimal strategies for the effective waste managements generated in nuclear power plants. Within this framework, four different balanced scorecard perspectives are considered as the criteria. In the analysis process, Analytical Hierarchy Process (AHP) methodology is taken into consideration. It is identified that learning and development is the most critical factor for the effective radioactive waste management created in nuclear power plants. On the other side, internal factors are the second most important criterion in this framework. Hence, it is understood that nuclear energy investors should give priority to the technological development for effective waste management in nuclear power plants. With the help of these technological improvements, the wastes can be disposed more successfully. As a result, environmental sustainability can be provided much easily.