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This study aims to assess financial development and debt status impact on energy efficiency in Nigeria as a developing economy.

This study combined the autoregressive distributed lag (ARDL), fully modified ordinary least squares and canonical cointegration regression analytical methods to estimate the parameters for energy efficiency policy recommendations. Secondary data between 1990 and 2020 were used for the analysis.

The result confirms the long-run nexus between energy efficiency, financial development and total debt stock. Furthermore, the ARDL estimates for this study’s key variables show that financial development promotes energy efficiency in the short run but hinders long-run energy efficiency. Total debt stock limits energy efficiency in Nigeria in short- and long-run periods.

The limitation of this study is that the scope is limited to Nigeria as a developing economy. The need to support energy efficiency projects is a global call requiring cross-country analysis. Despite this study’s focus on Nigeria, it provides useful insights that can guide energy efficiency policy through the financial sector and debt management.

The financial sector must ensure the availability of long-term credit facilities to clean energy investors. The government must maintain a sustainable debt profile to pave the way for capital expenditure on clean energy projects that promote energy efficiency.

The environmental consequences of energy intensity are being felt globally, with the developing countries most vulnerable. The cheapest way to curb these consequences is to promote energy efficiency to reduce the disastrous effect. Driving energy efficiency requires investment in energy-efficient technology but the challenge for developing economies, i.e. Nigeria’s funding, remains challenging amid a blotted debt profile. This becomes crucial to investigate how financial sector development and debt management can accelerate energy-efficient investments in Nigeria.

The purpose of this paper is to examine the relationship between top management commitment and energy management in small and medium manufacturing firms in a developing country context.

This study was executed through a survey of 66 manufacturing firms in Kampala, Uganda. The data collected were analysed using SPSS v.26.

The results show that top management commitment influences energy management. A further probe of its three dimensions of top management participation, top management support and top management beliefs reveals that all of them positively and significantly predict energy management in manufacturing firms.

The current study results were obtained from manufacturing small and medium firms in Kampala, Uganda. Therefore, caution should be taken prior to generalization. Furthermore, this study only focuses on top management participation, top management support and top management beliefs as the dimensions of top management commitment. This study thus provides the foundation for future studies to test other dimensions of top management commitment, particularly in other sectors.

To the best of the authors’ knowledge, this is the first study to examine the contribution of top management commitment dimensions top management participation, top management support and top management beliefs to energy management in a developing country context. Although all dimensions are significant, top management beliefs contribute more to energy management.

This study aims to explore the perceptions of investors regarding the risks associated with funding renewable energy projects in India, as well as the various factors that influence these perceptions. The investigation is limited to debt providers and seeks to pinpoint the primary risks that bankers perceive and the drivers that shape these perceptions.

This study draws on interviews and surveys of Indian bank executives, investigating how finance providers perceive risks in the Indian context and the factors driving such perceptions. Qualitative interviews have been used for operationalizing “risk perception” within the renewable energy domain, followed by a quantitative survey and exploratory factor analysis.

The authors find that experience and capacity are the most important factors that account for 30% of the overall variance. The second factor, which accounts for 15% of the variance, includes the perceived risks in funding renewable energy projects as compared to infrastructure projects. Among individual risks, the authors find that bankers perceive technological risk to be the lowest (5%) and contractual and regulatory risks as the highest (66%) in renewable energy projects.

The study contextualizes risk perception toward renewable energy investments in the Indian context by drawing from the risk perception literature and qualitative interviews with senior bankers. It presents empirical evidence on the decision-making behavior of bankers, who are important stakeholders of the renewable energy ecosystem. The main limitation of the study is the relatively small sample, and generalizing the results to the broader population might require a larger sample. This will facilitate the use of confirmatory factor analysis and structural equation modeling, which can facilitate a more comprehensive understanding of risk perceptions in renewables financing.

Insights gained can be used to provide policy recommendations for improving the financing ecosystem of renewable energy projects. The research significantly contributes to the extant literature within the renewable energy financing domain for emerging economies.

Research on solar energy adoption offers a multidimensional scope and warrants exploration from multiple perspectives, including political, economic, management, behavioral, policy and innovation aspects. The aim of this paper is to comprehensively consolidate major research findings on the premise of solar energy adoption and to disclose gaps in the existing literature.

A bibliometric analysis of the vast literature is conducted on 1,009 meticulously shortlisted articles following the semi-systematic literature review methodology. A text analytics tool named BibExcel is used for synthesizing the literature, and the results are visualized using Gephi, Pajek and a spreadsheet application.

This paper reports the evolution of research in the selected domain. It is noted that research in this domain was primarily concentrated on four broad themes, namely, peer effects and spatial patterns, public perceptions, policies and economics and technological evolution. The analysis further reveals the merging of two of these themes as a result of transdisciplinary research and also projects future research trends emphasizing political interventions in technological evolution and diffusion.

Research trends and future research scope are identified and discussed in detail. The information revealed from the analysis, along with the research implications, will assist policymakers in noting the flaws in the current doctrines and practices, entrepreneurs in understanding potential enablers and barriers influencing solar energy adoption and budding scholars in comprehending the current research status and framing promising research objectives to close the existing research gaps.

This study aims to identify sustainability indicators in the energy sector through a literature review and validate them from the perspective and context of professionals working in the sector in an emerging economy country, Brazil, considering the relationship of these indicators with the achievement of the targets set by the United Nations sustainable development goals (UN SDGs).

To accomplish this, a literature review on sustainability indicators specific to the energy sector was conducted. Subsequently, a research instrument (questionnaire) based on the identified indicators was developed and a survey was administered to professionals in the field. The collected data were analyzed using the Lawshe method.

The results revealed 20 indicators, distributed across environmental, economic and social dimensions. Among these, nine indicators were validated, including global impacts, local impacts, renewable energy production as a percentage of total production, greenhouse gas emissions, access to electricity, investment in the energy sector, installed capacity in the electricity sector, energy prices in the end-use sector and energy distribution and conversion efficiency.

Consequently, it was possible to determine which SDGs are directly impacted and provide a foundation for future actions that can contribute to the sustainable advancement of the energy sector in emerging countries.

This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions.

This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis.

In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles.

First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of public–private partnership (PPP) infrastructure projects. Such conferences together with available project reports and empirical studies recommend project managers and practitioners to adopt smart technologies and develop robust measures to tackle climate risk exposure. Comparatively, artificial intelligence (AI) risk management tools are better to mitigate climate risk, but it has been inadequately explored in the PPP sector. Thus, this study aims to explore the tools and roles of AI in climate risk management of PPP infrastructure projects.

Systematically, this study compiles and analyses 36 peer-reviewed journal articles sourced from Scopus, Web of Science, Google Scholar and PubMed.

The results demonstrate deep learning, building information modelling, robotic automations, remote sensors and fuzzy logic as major key AI-based risk models (tools) for PPP infrastructures. The roles of AI in climate risk management of PPPs include risk detection, analysis, controls and prediction.

For researchers, the findings provide relevant guide for further investigations into AI and climate risks within the PPP research domain.

This article highlights the AI tools in mitigating climate crisis in PPP infrastructure management.

This article provides strong arguments for the utilisation of AI in understanding and managing numerous challenges related to climate change in PPP infrastructure projects.

This study investigates how the initiatives and controversies related to environmental, social and governance (ESG) explain firm efficiency.

Firstly, this study applies data envelopment analysis with the epsilon-based measure to estimate the firm efficiency of 80 companies in the Chinese energy sector in 2022. This approach accounts for the diversity and relative importance of inputs and outputs from a multidimensional perspective. Secondly, this study regresses the variables of ESG initiatives and controversies on the estimated firm efficiency scores through a generalised additive model, which can capture nonlinear patterns.

This study finds that a) the samples have i) about 49% room for improvement in efficiently optimising their resources and business outcomes and ii) the highest scores in governance initiatives, followed by social initiative. b) 69% of them have controversy scores that are greater than the average value. c) A cluster analysis indicates that companies with higher social initiatives have higher firm efficiency than their counterparts. d) ESG initiatives and controversies are nonlinearly related to firm efficiency.

The findings have practical implications for policy makers and managers who prioritise ESG, particularly regarding (i) the need to examine firm performance from a multidimensional perspective, that is, to measure multiple inputs and outputs simultaneously, (ii) the nonlinearity of the nexus between ESG and efficiency in graphical forms, and (iii) the need to balance ESG initiatives and address ESG controversies.

This study integrates statistical approaches in examining and ensuring sustainable growth and efficiency within the Chinese energy sector and beyond.

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 this study is to analyze the aspects of the organizational culture (OC) of companies operating in the Brazilian oil, gas and biofuels (O&G) sector based on semistructured interviews with managers of these organizations and its content analysis.

This research was conducted based on semistructured interviews with 12 managers of Brazilian O&G companies and analyzed with a computer-assisted qualitative data analysis software, namely, MAXQDA™.

The results make it possible to obtain the perception of managers about OC, generally understood as a set of attributes and variables of social order, supported by the historical–culturalist theoretical approach. Information about the explicit and implicit manifestation of culture, as well as the evaluation of the most appropriate research instruments and metrics, were also obtained after the interviews.

This study presents detailed results about OC and its characteristics in the perception of managers of the O&G companies that operate in the Brazilian market.