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Examine the effects of sudden environmental disasters on the advancement of both renewable and conventional energy technologies.

Utilizing panel data from 31 Chinese provinces spanning 2011 to 2022, the SEM (Spatial Error Model) dual fixed model is utilized to examine the impact of sudden environmental disasters on energy technologies.

The findings reveal that: (1) Sudden environmental disasters exert a markedly positive influence on the Innovation of Renewable Energy Technologies (IRET), while their impact on conventional energy technologies is positively non-significant. (2) Sudden environmental disasters not only significantly enhance innovation in local renewable energy technologies but also extend this positive influence to neighboring regions, demonstrating a spatial spillover phenomenon. (3) Research and Development (R&D) funding serves as a partial mediator in the relationship between sudden environmental disasters and renewable ETI. In contrast, Foreign Direct Investment (FDI) exhibits a masking effect.

Consequently, the study advocates for intensified efforts in post-disaster reconstruction following abrupt environmental events, an elevation in the quality of foreign direct investments, and leveraging research funding to catalyze innovation in renewable energy technologies amid unforeseen environmental crises.

Energy and environment has gained traction within the field of entrepreneurship literature, but a comprehensive empirical study that examines the relationship between the cost of energy and small- and medium-sized enterprise (SME) innovation is an omission. Therefore, this novel study aims to examine the relationship between the cost of energy and SMEs innovation in Sub-Saharan Africa (SSA) by first examining the differential impact of the various generation sources on the price of electric energy. This research has enabled us to investigate and understand the transmission mechanism of increasing/decreasing electricity price on innovation decisions and activities of SMEs in SSA.

Using quantitative approach, with the data from the World Bank Enterprise and Innovation Follow-up Surveys, the study utilises a Tobit model to test whether the generation mix (renewable and non-renewable generation sources) increases or decreases electricity prices and examine the impact of the cost of electric energy on SMEs innovation in SSA.

The findings of this study shows that the cost of electricity affects negatively on SMEs innovation decision and activities of SMEs in SSA. The impact of renewables on the price of electricity has a larger magnitude relative to that of non-renewables. This finding has implications for policy makers promoting renewable energy without a policy design to tackle the unintended price effect of promoting renewable energy.

This is the first study to introduce cost of energy into an innovation model and to empirically examine the role of cost of energy for innovation activities of SMEs in SSA. Further, it examines the sources of generation on electricity price in SSA. The study contributes towards the empirical literature, and the findings also have implication for policy makers regarding the unintended consequences of promoting the transition to low-carbon electricity generation sources on SMEs via the cost of doing business implication.

This study is intended to analyze the impact of information and communication technology (ICT) infrastructure, technological innovation, renewable energy consumption and financial development on carbon dioxide emissions in emerging economies.

The present study adopts the autoregressive distributed lag (ARDL) cointegration technique for the annual data collection of Vietnam from 1990 to 2020.

The results of the study unveil that renewable energy consumption, the interaction between renewable energy consumption and ICT infrastructure and financial development have significant predictive power for carbon dioxide emissions. In the long term, renewable energy consumption, export and population growth reduce CO2 emissions, whereas the interaction between renewable energy consumption and ICT infrastructure and financial development increases CO2 emissions, while ICT infrastructure does not affect emissions. In the short run, changes in ICT infrastructure contribute to carbon dioxide emissions in Vietnam. In addition, changes in renewable energy consumption, financial development, the interaction between ICT infrastructure and renewable energy consumption and population growth have a significant effect on CO2 emissions. Notably, technological innovation has no impact on CO2 emissions in both the short and long run.

The current study provides new insights into the environmental effects of ICT infrastructure, technological innovation, renewable energy consumption and financial development. The interaction between renewable energy consumption and ICT infrastructure has a significant effect on carbon dioxide emissions. The paper suggests important implications for setting long-run policies to boost the effects of financial development, renewable energy consumption and ICT infrastructure on environmental quality in emerging countries like Vietnam in the coming time.

This conceptual paper articulates an analytical framework, which collectively borrows from the concepts of Sectoral, National and Technological Innovation Systems, for examining the prospects for the emergence of renewable energy industries in a given country. In order to examine the dynamics within the national energy system under consideration, a list of system functions has also been compiled from the literature. It is believed that the adoption of such a functions approach has the potential to enhance our understanding of the process of, and drivers behind, the emergence and transformation of energy innovation systems. Towards the end of this paper, other theoretical concepts are acknowledged as also relevant for investigating the potential establishment of renewable energy industries. While every theoretical approach has its strengths and weaknesses, an effort has been made in this paper to justify the adoption of a suitable framework that is based on the systems of innovation approach.

The purpose of this paper is to examine the effects of energy technological innovation on carbon emissions in China from 2001 to 2016.

Conditional mean (CM) methods are first applied to implement our investigation. Then, considering the tremendous heterogeneity in China, quantile regression is further employed to comprehensively investigate the potential heterogeneous effect between energy technological innovation and carbon emission intensity.

The results suggest that renewable energy technological innovation has a significantly positive effect on carbon emission intensity in lower quantile areas and a negative effect in higher quantile areas. Contrarily, fossil energy technological innovation exerts a negative correlation with carbon emission intensity in lower quantile areas and a positive effect on carbon emission intensity in higher quantiles areas.

Considering that energy consumption is the main source of CO₂ emissions, it is of great importance to study the impact of energy technological innovation on carbon emissions. However, the previous studies mainly focus on the impact of integrated technological innovation on carbon emissions, ignoring the impact of energy technological innovation on carbon emissions mitigation. To fill this gap, we construct an extended STIRPAT model to examine the effects of renewable energy technological innovation and fossil energy technological innovation on carbon emissions in this paper. The results can provide a reference for the government to formulate carbon mitigation policies.

This paper aims to show preliminary evidence of the link between the perceived low vulnerability of vital energy systems (LVRE) and social acceptance of renewable energy (SARE) while treating environmental opportunities and threats (EOPT), renewable energy technological innovations (TECH) and business model innovations as possible antecedents.

The objectives are delivered through a survey of 199 households (potential and actual customers/suppliers of electric power and renewable energy gadgets in Kampala and Wakiso districts of Uganda), and the data obtained were analysed using ordinary least squares (OLS) regression.

Both LVRE and EOPT, on their own, significantly predict SARE. TECH significantly mediate in the relation between EOPT and SARE. The highest form of SARE is market acceptance. Also, the current state of vulnerability of vital energy systems in the two Ugandan districts seems to espouse energy security as the real value of renewable energy. The study further finds that to deliver high SARE, there is a need to encompass potential user performance expectations of renewable energy technologies.

Because the current results are from only two cities (districts) of Uganda and also based on a non-probability sample, generalizing them can be considered remote. In other words, it appears that more complex models need developing and testing in the future concerning LVRE and SARE. The present preliminary results are offered as a stimulus to such efforts. Well, it is expected, and, consistent with the diffusion of innovations theory (Rogers, 1995), that the population in Kampala and Wakiso districts are potential change agents (i.e. capable of influencing others in rural areas of Uganda).

The study estimates the direct and indirect effects to show how strongly TECH operate. Basing on OLS regression coefficients, the indirect effects are larger. Using the medgraph, we find probably for the first time, the adoption of technological innovation explains a significant part of the link between EOPT and SARE in the current study setting.

One of the most important ways to pay attention to sustainable economic development is to invest in green technology and alter the energy consumption structure (ECS) in countries. Changing the ECS can be important in two ways: first, it increases the diversity of energy consumption and reduces energy dependence on other countries. Second, the use of highly polluted nonrenewable energy sources (such as oil and coal) is reduced, leading to the transfer of energy to natural gas with less carbon emissions or renewable energy. To this end, the authors examined the asymmetric effects of eco-innovation on the US ECS from 1980 to 2019. This paper aims to address this issue.

In this research, the nonlinear autoregressive distributed lag (ARDL) (NARDL) model is used and the results are compared with the linear ARDL model.

The ARDL results also confirm the positive effects of oil prices and GDP per capita in the long run. On the other hand, short-term and long-term Wald test results confirm the nonlinear effects of eco-innovation (LPATENT) on US ECS. These results indicate that 1% positive shock in LPATENTˆ+ increases the ECS by 0.179, while 1% negative fluctuations (LPATENTˆ-) leads to a decrease (−0.085) in the ECS. However, the ARDL results, in general, show the positive effects of LPATENT on the ECS in long run. Evidence suggests that ignoring nonlinear effects can lead to inaccurate results. Policy suggestions for environmental technology innovation are presented in the results.

This research has innovations in various aspects so that the previous studies in this field have examined the effects of environmental innovation on renewable or nonrenewable energy consumption, and so far no study has been done on the ECS. In this research, the Shannon–Wiener index has been used to calculate the ECS.

The purpose of this paper is to analyse the influence of economic growth, digitalisation, eco-innovation, energy consumption and patents on environmental technologies on the volume of greenhouse gas emissions (GHG) recorded in European countries for a period of nine years (2010–2018).

Two empirical methods were integrated into the theoretical approach developed based on the analysis of the current scientific framework. Multiple linear regression, an extended version of the OLS model, and a non-causal analysis as a robustness method, Dumitrescu–Hurlin, were used to achieve the proposed research objective.

Digitalisation described by the number of individual Internet users and patents on environmental technologies determines the amount of GHG in Europe, and economic growth continues to have a significant effect on the amount of emissions, as well as the consumption of renewable energy. European countries are not framed in well-established patterns, but the economic growth, digitalisation, eco-innovation and renewable energy have an impact on the amount of GHG in one way or another. In many European countries, the amount of GHGs is decreasing as a result of economic growth, changes in the energy field and digitalisation. The positive influence of economic growth on climate neutrality depends on its degree of sustainability, while patents have the same conditional effect of their translation into environmentally efficient technologies.

This study has a number of limitations which derive, first of all, from the lack of digitalisation indicators. The missing data restricted the inclusion in the analysis of variables relevant to the description of the European digitalisation process, also obtaining conclusive results on the effects of digitalisation on GHG emissions.

A similar analysis of the relationship among the amount of greenhouse gas emissions and economic growth, digitalisation, eco-innovation and renewable energy is less common in the literature. Also, the results can be inspirational in the sphere of macroeconomic policy.

This study aims to identify the various economic and non-economic determinants of renewable energy consumption (REC) in Brazil, Russia, India, China and South Africa (BRICS). Due to the adverse effect of carbon emission on the environment, every country is trying for a transition from fossil fuel towards renewable energy. Renewable energy plays a crucial role in reducing carbon emission and combating climate change. Understanding the determinants that influence REC helps to promote this transition.

The study is based on an unbalanced panel data over the period 2002–2019 for all five BRICS nations. The panel corrected standard error (PCSE) method has been adopted to examine the determinants of REC.

Industrialization, population growth and foreign direct investment (FDI) are found to be significant economic determinants of REC while patent on environmental technologies, political instability and industrial design are significant non-economic determinants of REC in the BRICS nations.

The findings imply that to increase REC in BRICS nations, policymakers should incentivize industries for investments in renewable energy, attract FDI aligned with environmental regulations, raise population awareness through training, enforce industrial design standards, establish fair technology transfer frameworks to overcome patent barriers and create stable, long-term renewable energy policies with risk mitigation instruments to address political instability.

The study captures the effect of patents on environmental technologies and industrial design on the consumption of renewable energy. Thus, the novelty lies in investigating unexplored variables in the previous literature likely to affect REC.

This study’s goal is to research and describe developing green technology and green business models, as well as their commercial advantages. However, it focuses on how old business breakthroughs and models may be transformed into new green technologies and innovations that can affect the global business environment. This research concentrates on the technology component of green technologies and provides information on a variety of relevant emerging green business models and innovations such as energy efficiency, renewable energy consumption, commodities and systems, environmental protection, nontoxic materials, and waste minimization, among others. Additionally, this research connects Emerging Green Technology (EGT) innovations to the business for sustainability. It also emphasizes the advantages of green technology adoption in business specially in developing economies.

For that purpose, a Systematic Literature Review (SLR) was performed based on the “inclusion/exclusion criteria” and “PRISMA flow diagram method”. The first screening and quality evaluation rejected 67 publications, 8 in eligibility and 10 in credibility. In the subsequent round, 45 papers out of 210 that met the search parameters were included to access the findings.

This study provides a foundation for future research into sustainable economic potential by examining the development, breakthroughs, obstacles, future trends and new research prospects of EGTs. As such, this research will serve as a helpful resource for economically growing nations looking to foster long-term growth in their businesses through sustainable development strategies.

The first limitation of the study is the generalization of the findings. The sample size of the study is limited. For that purpose, an SLR and “PRISMA flow diagram” methods were performed by “inclusion/exclusion criteria” for literature review. Except these, there are many new techniques of SLR. Further research with more sampling and sophisticated tests could produce better results for this study.

This research provides valuable insights for businesses and politicians seeking to protect the environment, promote economic growth and create a sustainable society. The findings will be particularly useful for emerging nations grappling with issues related to technical innovation, safe environmental practices, reliable renewable energy sources, and ecological and economic growth.

This study’s findings will aid in the design and implementation of new green technology and innovations in current businesses, which will assist in limiting climate change and eventually affect their move to sustainable growth paradigms. For emerging nations, this study will be useful in addressing issues about technical innovation, safe environmental conditions, reliable renewable energy sources as well as ecological and economic growth. According to our research results, the authorities of developing nations would gain from utilizing green business models and technology to spur economic development. Our findings should thus add to the current body of knowledge.