The dynamics effect of green technology innovation on economic growth and CO2 emission in Singapore: new evidence from bootstrap ARDL approach

A simultaneous impact of digital economy, environment technology, business activity on environment and economic growth in G7: Moderating role of institutions

This study investigates the simultaneous influence of the digital economy, environmental technologies, business activity, and institutional quality on both the environment and economic growth in G7 economies from 1996 to 2020. The study provides an in-depth analysis to investigate the influence of institutional quality, particularly the regulatory environment, on business activity. Employing a rigorous methodology encompassing correlation analysis, long-term examination using Driscoll and regression estimators, and the utilization of various digital economy indicators such as internet usage and cell subscriptions, we uncover significant insights. The findings underscore the substantial impact of digital economies in mitigating carbon emissions and driving economic growth at an accelerated rate. Moreover, the study reveals that certain regulatory constraints on corporate operations can paradoxically facilitate carbon emission management while also fostering economic expansion. The study validates the presence of an inverted U-shaped Environmental Kuznets Curve (EKC) in G7 economies. This suggests that there is a specific point at which economic activities start to contribute more to carbon emissions. Moreover, the study highlights the importance of achieving a balance between economic growth driven by foreign direct investment and the goals of environmental sustainability. Environmental technology is becoming increasingly important in the regulation of emissions. Significantly, the study highlights the need to enhance the quality of implementing institutional regulations. It suggests that G7 economies can improve both environmental quality and economic growth by adopting superior regulatory methods. These findings are relevant for governments seeking economic growth and environmental protection. They suggest the need for specific policy actions to accomplish sustainable development goals.

Green innovation and enterprise digital transformation: Escape from the "dilemma" of development and governance choices

The digital economy is now the expected norm for economic development, warranting strategic importance for enterprise digital transformation. Nonetheless, enterprises have a lengthy journey to embark upon for digital transformation. On the one hand, resource-based demands pose a significant challenge due to the development characteristics of the initiative; on the other hand, excessive emphasis on economic gains may result in severe environmental issues. Therefore, this paper examines whether green innovation, which combines environmental and economic benefits, can effectively address the above dilemma. The study includes all A-share listed companies from 2010 to 2020 as the research sample, and empirically investigates the impact of green innovation on enterprise digital transformation and its mechanism based on resource-based view. The study concluded that (i) green innovation has a significant positive impact on corporate digital transformation performance, exhibiting asymmetric effects. The robustness tests confirmed the validity of the findings. (ii) Enterprises that actively engage in green innovation can effectively reduce their financial constraints, enhance their operational capacity, and enable the efficient allocation of resources, thereby promoting digital transformation within the enterprise. (iii) There is a regional imbalance in the conversion of green innovation performance into economic performance. The aforementioned results offer fresh insights for investigating the connection between green innovation and digital transformation. Additionally, these findings hold significant implications for the discourse on the synergistic advancement of the environment and economy.

Environmental regulation, green technology progress and haze reduction and carbon reduction

Coordinated efforts to reduce haze and carbon emissions are important in promoting global climate governance and sustainable development. In this paper, based on prefecture-level data of China from 2005 to 2019, we investigate the impact of environmental regulatory intensity on the emissions of the concentration of PM2.5 and carbon dioxide (CO2). The research indicates that environmental regulation facilitates synergistic governance for PM2.5 reduction and carbon mitigation. Green technological advancement emerges as the primary mechanism through which environmental regulation achieves haze reduction and carbon mitigation. This conclusion remains robust after a series of robustness tests. Furthermore, the results from quantile regression reveal that the haze reduction and carbon mitigation effects of environmental regulation are subject to certain conditional dependencies. Environmental regulation exhibits a significant negative impact on carbon emissions across various quantile points. However, their influence on different quantile levels of PM2.5 concentration displays an asymmetric pattern. Finally, threshold regression findings suggest that there is no significant threshold effect of environmental regulation on CO2 emissions, but there are dual threshold effects on the PM2.5 concentration. Therefore, it is recommended that local governments judiciously implement environmental regulatory intensity, establish interregional policies for haze reduction and carbon mitigation, and fully harness the driving force of green technology to promote a comprehensive green transformation of economic and social development.

The impact of technological innovation on the green digital economy and development strategies

To investigate the interplay among technological innovation, industrial structure, production methodologies, economic growth, and environmental consequences within the paradigm of a green economy and to put forth strategies for sustainable development, this study scrutinizes the limitations inherent in conventional deep learning networks. Firstly, this study analyzes the limitations and optimization strategies of multi-layer perceptron (MLP) networks under the background of the green economy. Secondly, the MLP network model is optimized, and the dynamic analysis of the impact of technological innovation on the digital economy is discussed. Finally, the effectiveness of the optimization model is verified by experiments. Moreover, a sustainable development strategy based on dynamic analysis is also proposed. The experimental results reveal that, in comparison to traditional Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) models, the optimized model in this study demonstrates improved performance across various metrics. With a sample size of 500, the optimized model achieves a prediction accuracy of 97.2% for forecasting future trends, representing an average increase of 14.6%. Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. In the examination of changes in industrial structure using 2020 data to forecast the output value of traditional and green industries in 2030, it is observed that the output value of traditional industries is anticipated to decrease, with an average decline of 11.4 billion yuan. Conversely, propelled by the development of the digital economy, the output value of green industries is expected to increase, with an average growth of 23.4 billion yuan. This shift in industrial structure aligns with the principles and trends of the green economy, further promoting sustainable development. In the study of innovative production methods, the green industry has achieved an increase in output and significantly enhanced production efficiency, showing an average growth of 2.135 million tons compared to the average in 2020. Consequently, this study highlights the dynamic impact of technological innovation on the digital economy and its crucial role within the context of a green economy. It holds certain reference significance for research on the dynamic effects of the digital economy under technological innovation.

Green technology innovation and regional carbon emissions: analysis based on heterogeneous treatment effect modeling

The impact of green technology innovation on regional carbon emissions has been a contentious issue in academic research. In this study, we attempt to analyze the influence of green technology innovation on regional carbon emissions using panel data from 28 Chinese provinces for the period of 2007-2020. Utilizing a heterogeneous treatment effect model, we systematically examine the effects of green technology innovation on regional carbon emissions. Firstly, we conduct a feature selection analysis on the factors influencing regional carbon emissions using causal inference methods based on machine learning. Subsequently, we explore the conditional and marginal treatment effects of green technology innovation on regional carbon emissions using the heterogeneous treatment effect model. Finally, we investigate the dynamic effects of green technology innovation on regional carbon emissions across different periods. Empirical results indicate that firstly, green technology innovation indirectly reduces regional carbon emissions by promoting energy efficiency improvement; secondly, the impact of green technology innovation on carbon emissions exhibits significant regional heterogeneity, with the largest effect observed in the eastern region, followed by the western region and the smallest effect in the central region; thirdly, at a significance level of 5%, green technology innovation has a direct inhibitory effect on carbon emissions in certain regions.

Coordinated development of green finance and green technology innovation in China: from the perspective of network characteristics and prediction

Under the path of sustainable development, the key to achieving green and low-carbon transformation lies in green technology innovation (GTI), and how to effectively coordinate the relationship between green finance (GF) and GTI is an issue worth studying. This paper constructed an evaluation system of GF and GTI and combined them with the coupled coordination degree model to explore their coordination of Chinese provinces from 2012 to 2019. Then, the core network evolution and spatial structure characteristics of GTI and GF were studied using the modified gravity model. Finally, based on the link prediction, the general future network prediction is made to provide guidance and direction for the future GTI and GF development and construction. The results found that the coordination level between GF and GTI has been continuously improved from 0.356 to 0.436. The core network structure is keeping changing with their connection becoming more complex, and there is still room for optimization. Network centrality characteristics show that the spatial spillover effects are stronger in the more economically developed regions. The overall network possibility prediction shows the potential network connections in different urban agglomerations. This paper provides a certain reference role for China and developing countries to predict the GF and GTI cooperation network development in the future.

Interdependency and causality between green technology innovation and consumption-based carbon emissions in Saudi Arabia: fresh insights from quantile-on-quantile and causality-in-quantiles approaches

In this paper, we examined the asymmetric dynamics and causality of technological progress--proxied by green technology innovation--on both consumption-based carbon (CCO2) and territory-based carbon (TCO2) emissions in Saudi Arabia using quarterly data from 1990Q1 to 2021Q4. Our initial results reject the normality and linearity assumptions of data series and thus emphasize that the observed associations are quantile dependent. We firstly utilized the quantile-on-quantile regression (QQR) approach to draw the interdependency between green technology innovation and both CCO2 and TCO2 emissions. We found a strong emission-mitigating impact of green technology innovation only at (extreme) upper emission levels. We also identified a weak positive effect at (extreme) higher emission quantiles. Furthermore, we found that higher emission levels are linked with lower green technology innovation across all emission quantiles whereas a weak positive effect is perceived at lower and medium emission quantiles. We further utilized linear and nonlinear Granger causality-in- quantiles (GCQ) tests to capture an entire picture of the impact of green technology innovation on both CCO2 and TCO2 emissions. Under linear specifications of the quantile regression model, we found evidence of strong bidirectional causality between carbon emissions and green technology innovation across lower and upper quantiles. However, we found unidirectional causalities from carbon emissions to green technology innovation at medium quantiles of the conditional distribution. Besides, there is no causality at both extreme lower and extreme upper quantiles. Under nonlinear specifications of the quantile regression model, we found a weak unidirectional causality from green technology innovation to carbon emissions at (extreme) lower quantiles. We also found a weak unidirectional causality from carbon emissions to green technology innovation at medium and extreme upper quantiles. Overall, our findings indicate that green technology innovation helps abate both CCO2 and TCO2 emissions in Saudi Arabia. Our study shows policies that target green technology innovation would significantly change carbon emissions.

Green technology advancement, energy input share and carbon emission trend studies

In order to study the theoretical mechanism of the impact of green technology progress on carbon emissions, this article constructs a theoretical mechanism of the impact of green technology progress on carbon emission growth. Explore the conditions for achieving carbon peak and carbon reduction. Based on the Cobb Douglas production function, construct a three sector model that includes capital, labor, and energy. Empirical methods were used to analyze the quantitative impact of green technology progress on carbon emission growth and the moderating effect of energy input share. This study mainly used provincial panel data from 1995 to 2020. Calculate carbon dioxide emissions based on energy consumption and carbon dioxide emission coefficients of various energy sources in different regions. Using the perpetual inventory method to calculate capital growth rate, green computing progress rate, etc., to provide data support for the green technology carbon reduction model. Empirical analysis of the impact of green technology progress on carbon emissions using the FGLS panel model. Theoretical and empirical analyses show that green technological progress promotes an increase in the carbon emission growth rate through the scale effect, with an impact coefficient of 0.607; it promotes a decrease in the carbon emission growth rate through the technological effect, with an impact coefficient of - 0.667; the combined effect promotes a decrease in growth rate of carbon emissions, with an impact coefficient of - 0.06. The share of energy inputs has a positive regulating effect on the scale effect.

Ragab A. Evidence from the energy-technology-growth nexus: A new study based on technology-minerals based complexity index

The increasing trend in sustainable economic growth over the last few decades has elevated the energy demand, technological innovation, and access to minerals resources are contributing well to economic development. This article investigates the nexus among minerals resource complexity, energy consumption, technology, and economic growth by employing autoregressive distributed lag and vector error correction techniques for Pakistan from 1995 to 2021. Following thorough research, the long-term results show that an important 9.73 points of economic growth result from every 1 % increase in the complexity of natural resources. On the other hand, technology and energy use negatively affect economic growth, causing drops of -0.03 and -12.9 points, respectively. One-way causality was noted between mineral resources' complexity and economic growth. Moreover, a one-sided causality effect was also confirmed between energy use, technology, and economic growth. Additionally, it was predicted that there is a neutral causality between mineral resources and technology. Corresponding to this, technology and energy consumption have a bidirectional causal relationship. These results imply that energy consumption, technological advancements, and mineral resources contribute as major economic growth drivers and can improve environmental quality.

Analyzing the impacts of renewable energy, patents, and trade on carbon emissions-evidence from the novel method of MMQR

Achieving sustainable development necessitates proactive measures to mitigate the economy's negative impact on environmental standards. A new empirical association between renewable energy patent innovation and net international trade on carbon emissions in ASEAN countries from 1990 to 2021 is presented, along with its significance. Using present panel data techniques, this study investigates the connections between these factors. Second-generation cointegration and unit root tests, as well as a novel method of Moments Quantile Regression, are used in the econometric procedure. Compared to standard quantile regression, this method is more resistant to outliers and provides an asymmetric relationship between the variables. The findings show that trade increases carbon emissions in countries with medium to high emissions, that patent innovation contributes to increasing emissions, and that renewable energy mitigates carbon emissions in countries with low to medium emerging economies. Our results are consistent with other specifications, including quantile regression canay (Canay 2011), fully modified, dynamic, and fixed effect regressions, proving the EKC hypothesis. These countries need to prioritize greener products and adopt advanced manufacturing technologies to reduce carbon emissions from consumption. However, as prosperity increases, it also leads to higher consumption-based carbon emissions, worsening ecological damage in the region. Implementing policies like trade synchronization and increasing investment in patent innovations are proposed in this study to lower the current level of carbon emissions.

Does green innovation reduce environmental degradation? A panel threshold analysis for BRICS countries

In this present age, innovation has become inextricably tied to both long-term economic growth and environmentally sound development. In this context, the impact that environmentally focused technological advancements or innovations have on environmental quality is of the utmost importance. Therefore, the main goal of the present study is to determine how Green innovation (GI) affects environmental degradation in the BRICS countries from 1992 to 2021. The ecological footprint (EFT) is an indicator used in the study to measure environmental degradation. The study divides the components that contribute to the explanation into two categories: the GI threshold variable and the independent variables RE, GDP, and population (POP). Additionally, this study investigates the indirect impact of RE, GDP, and POP through the threshold effect of GI. The stochastic impacts of the explanatory factors are explored using sophisticated panel data estimation methods and a panel threshold model. According to the findings of the study, an improvement in environmental quality occurs when the threshold level of GI is achieved, which indicates that innovation in the form of a lower EFT is responsible for the improvement. In light of the findings, recommendations for policymakers and stakeholders in BRICS countries are to promote RE and drive GI.

Towards green economy and sustainable development in Bangladesh: assessing the role of social and environmental indicators

The evolution towards a green economy integrating social, economic, and environmental concerns has opened a new window to pursue the sustainable development goals (SDGs), especially for emerging nations. Nonetheless, despite being a pressing concern on a global scale, empirical research into the potential for green economy development in the context of Bangladesh has remained notably inadequate. To fill this void, this study is an attempt to evaluate the connection among economic growth, carbon dioxide (CO2) emissions, education, life expectancy, and technology to conclude the ecological and socio-economic repercussions of a green economy in Bangladesh's framework of achieving SDGs. Considering the statistical features of the annual data from 1990 to 2019, the autoregressive distributed lag (ARDL) method has been employed to analyze the connections between the chosen variables. The empirical outcomes show that an upsurge in CO2 is accompanied by a 3.66% increase in GDP over the long term, suggesting a positive and statistically significant relationship between the two variables. In addition, GDP increases by about 4.2% for every 1% increase in life expectancy. However, the relationship between technological innovation and education found an insignificant positive linkage with GDP. The most important takeaway from these findings is that the growth of Bangladesh's economy is occurring at the expense of the environment. Hence, this research recommends that, as a developing nation, Bangladesh should concentrate on environment-friendly alternatives, which can be done through the introduction of a green economy to achieve a sustainably developed economy.

Digital inclusive finance, agricultural green technology innovation and agricultural carbon emissions: Impact mechanism and empirical test

The impact of digital financial inclusion (If) and agricultural technology innovation (Gi) on agricultural carbon emissions has attracted wide attention from the academic community, but the inconsistent conclusions of existing studies and the reality that few studies have gathered them into a framework require more evidence to fill this gap, which can contribute more insights to promoting economic development and controlling carbon emissions. Taking the provincial-level relevant data of China's agriculture from 2011 to 2020 as a sample, the GMM method is used to integrally test the relationship between the three factors. The results show that (1) from 2011 to 2020, China's overall agricultural carbon emissions experienced two stages of fluctuating rise (2011-2015) and continuous decline (2015-2020). In 2015, China's agricultural carbon emissions peaked at 1,040 million tons; Overall, Hunan, Hubei, and Henan were the provinces with the largest agricultural carbon emissions; Beijing, Tianjin, and Shanghai are provinces with relatively low agricultural carbon emissions. (2) Although the impact of digital financial inclusion on agricultural carbon emissions is negative, it is not significant. (3) Agricultural technology innovation promoted the reduction of agricultural carbon emissions. If the level of agricultural technology innovation increased by 1 percentage point, agricultural carbon emissions would decrease by 0.09 percentage points. (4) Mechanism analysis showed that agricultural technology innovation could reduce carbon emissions through the efficiency of agricultural resource allocation, and its effect reached 56%. The results can provide a scientific basis for the government to formulate targeted policies, and the methods can be extended to other places.

Moderating role of green innovation and fiscal expenditure towards achieving the Sustainable Development Agenda 2030 at provincial-level in China: policy implication from green total factor productivity

Amidst resource loss and environmental protection constraints, achieving green development necessitates enhancing green total factor productivity (GTFP) as a means of promoting rational and efficient resource allocation, thereby balancing economic growth and environmental preservation. Meanwhile, literature on the subject matter of GTFP from a sustainability viewpoint is minimal. As a result, this study employs the panel dataset from 30 provinces of China spanning the period 2005 to 2020 and utilizes the method of moments quantile regression (MMQR) developed by Machado and Santos Silva (2019) to analyze the heterogeneous role of green innovation, environmental regulations, and fiscal expenditure on GTFP. Moreover, the controlling variable for this study includes renewable energy and economic growth. Furthermore, this study investigates the heterogeneous combined impact of green innovation and fiscal expenditure (GTE*FSE) on GTFP. The findings of the MMQR reveal that green innovation has a positive impact on GTFP, while fiscal expenditure, environmental regulations, and renewable energy consumption have a negative impact. GTE*FSE has a positive and significant effect on GTFP, indicating that FSE can reinforce and increase the positive impact of GTE on GTFP in the long run. The study also reveals that economic growth has a mixed effect on GTFP, depending on the quantiles. Furthermore, environmental regulation has a significant and negative impact on GTFP, contradicting the Porter hypothesis. Likewise, the robustness of the findings is confirmed by the results of the fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimations, which indicate a similar impact of the determinants on GTFP as observed in the MMQR analysis. This reinforces the validity of the findings and suggests that the observed relationships are robust to different estimation techniques. Furthermore, the findings of the Dumitrescu and Hurlin (D-H) panel causality test reveal significant bidirectional causality between renewable energy consumption and GTFP and fiscal expenditure and GTFP. Policy-makers need to channel a large chuck of their fiscal spending into green innovation so as to boost sustainability.

Green technology, exports, and CO2 emissions in Malaysia

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.

Exploring the roles of green finance and environmental regulations on CO2es: defining the roles of social and economic globalization in the next eleven nations

Achieving sustainable environmental growth and preventing further environmental degradation are challenging goals for policymakers. This study looks at environmental laws and green finance's role in fostering a more sustainable environment. The literature still needs to empirically or theoretically investigate how environmental laws and green financing affect carbon dioxide (CO2) emissions, particularly when combined with moderating factors such as social and economic globalization. As a result, this study investigates how environmental laws and green funding can help the N-11 nations cut their CO2 emissions. Our research uses empirical data from a group of the N-11 nations that span the years 2000 to 2019. To handle issues with panel data analysis, such as cross-sectional dependence and slope heterogeneity, we use advanced panel approaches (CIPS and CADF unit root and cointegration test and cross-sectional augmented ARDL). This research demonstrates that green financing (GFI) and environmental laws (ENV) have a negative but significant effect on CO2 emissions. While social globalization moderates the causal relationship between energy consumption and GDP while negatively and significantly causing GFI and ENV with CO2 emissions among the N-11 countries, economic growth has had a positive and significant effect on CO2 emissions in the N-11 countries. According to our research, nations could achieve the SDG-7 and SDG-13 goals if they adopted green financial and environmental policies.

How to achieve carbon neutrality while maintaining economic vitality: An exploration from the perspective of technological innovation and trade openness

The significant drop in global carbon emissions in 2020 was credited to the enormous loss of economic activity from the impact of COVID-19. The challenge is now to reduce carbon emissions without causing massive disruption and damage to economic production. To achieve carbon neutrality while maintaining economic vitality, the impact of technological innovation and trade openness must be considered. This paper sets technological innovation and trade openness as core variables and establishes two extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) models. The first model focuses on carbon emissions and the second focuses on economic growth. Comparisons were made between the BRICS (i.e., Brazil, Russia, India, China, and South Africa) and G7 (i.e., Canada, France, Germany, Italy, Japan, the UK, and the USA) countries. The fully modified ordinary least squares (FMOLS) regression analysis was used to explore the impact of technological innovation and trade openness on low-carbon economic development. A Panel Granger Causality Test explores the causal relationship between the core, control and dependent variables. The results illustrate that: (1) technological innovation is the primary factor that inhibits carbon emissions and promotes economic growth in both international organizations, (2) trade openness promotes the growth of carbon emissions in BRICS countries, but restrains G7 growth, confirming the "Pollution Haven Hypothesis", (3) per capita GDP is the largest contributor to carbon emissions growth in both the G7 and BRICS countries, which illustrates that per capita GDP is the largest contributor to carbon emissions. It is proportional to G7 and BRICS carbon emissions. This paper provides several policy recommendations: breaking through basic research, adjusting the science and technology evaluation system, optimizing the export trade structure, and increasing the proportion of renewable energy.

Achieving carbon neutrality: the effect of China pilot Free Trade Zone policy on green technology innovation

Evaluating the effect of China pilot Free Trade Zone (FTZ) policy on green technology innovation is important for achieving China's carbon neutrality targets. Based on the panel data of 30 provincial administrative regions in China from 2009 to 2019, this study investigates the effect of the pilot FTZ policy on green technology innovation by using the difference-in-differences method. The study's findings indicate the following: (1) The pilot FTZ policy promotes the development of green technology innovation, and there is a policy lag in a few pilot regions. (2) The mediation effect analysis shows that the pilot FTZ policy promotes the development of green technology innovation by improving the marketization process and enhancing innovative talent gathering. (3) The heterogeneity analysis shows that the pilot FTZ policy is more effective in promoting green technology innovation when implemented in regions with developed economies or higher levels of human capital. Moreover, the pilot FTZ policy mainly has a significant promoting effect on green utility model patents. Based on these results, policy recommendations are proposed to promote the development of green technology innovation and the achievement of China's carbon neutrality targets.

Asymmetrical effects of renewable energy consumption, financial development, and urbanization on the economic growth of China: does the role of technology matters

Our paper investigates the association of renewable energy, financial development, urbanization, and growth in China along with technology. The newly developed econometric techniques (asymmetries) have been applied to explore short and long-run nonlinear relation among variables by utilizing annual data for the period of 1965-2021. In nonlinear cointegration, findings highlight the importance of renewable energy consumption for growth and development. Urbanization also confirms a positive association with growth and development where positive shocks were more dominant to support the growth process. The stock of technology brings a positive impact on growth and development whereas financial development results reveal to consider policy carefully. Asymmetric causality supports a uni-directional causal association between renewable energy, financial development, and growth. Policy recommendations are also highlighted according to the results.

The influences of the advancement of green technology on agricultural CO2 release reduction: A case of Chinese agricultural industry

The development of green technology (GT) may have a vital influence in decreasing carbon releases, and the linkage between the advancement of GT and CO2 releases in China's agricultural industry has not attracted enough attention. The main objectives of this study are to assess the influence of agricultural green technology advancement on efficiency enhancement, release control capabilities, agricultural energy structure, and agriculture industrial structure. This article decomposes the advancement of green technology (AGTP) in the agricultural industry in China into resource-saving green technology advancement (AEGTP) and emission reduction green technology advancement (ACGTP). At the same time, to evaluate the intermediary impact of green technology advancement, a two-step econometric model and an intermediary impact model were utilized to evaluate the panel data of 30 provinces in China from 1998 to 2018. The role of AGTP (including ACGTP and AEGTP) and CO2 release concentration has also been explored critically. The results show that (i) under the two-step measurement method, AGTP has substantial favorable impacts on agricultural energy efficiency (EF) and possesses a negative impact on agriculture industrial structure (PS) and agricultural energy structure (ES). Agricultural energy efficiency (EF) and agriculture industrial structure (PS) under AGTP will reduce CO2 release concentration, but the path of agricultural energy structure (ES) will increase CO2 release concentration. (ii) At the national level, AGTP has an immediate unfavorable influence on CO2 releases. After introducing the intermediary variables, the intermediary impact of AGTP on CO2 releases through agricultural energy efficiency (EF), agriculture industrial structure (PS), and agricultural energy structure (ES) is also significantly negative, and the direct impacts of each variable are higher than the intermediary impact. (iii) In terms of different zones, the direct impacts of AGTP are all significant. The order of significance of the direct impacts of different zones is west to central and central to eastern. The overall significance ranking of the mediating impact is ACGTP > AEGTP > AGTP, and the significance ranking of each index is ES > EF > PS. Finally, this article puts forward some policy recommendations to reduce CO2 releases.

The paradigms of transport energy consumption and technological innovation as a panacea for sustainable environment: is there any asymmetric association?

Technological innovations have a great potential to develop the transportation system as more efficient, intelligent, connected, and sustainable. Therefore, transport energy consumption fundamentally transmutes how goods and people are moved with significant effects on transport demand with related energy consumption on a sustainable environment. To this end, our research aimed at investigating the environmental performance (carbon dioxide and ecological footprint) by stochastic impact by regression through a population, affluence, and technology (STIRPAT) model, and econometric approach for estimation of transport energy consumption from 1975 to 2018 for Pakistan. Moreover, our study supports the literature by exploring the association of technological innovations, financial development, carbon damage costs, and economic growth with the environment. The linear relationships of the variables are governed by the autoregressive distributive lag (ARDL) model that interestingly explored that economic growth and energy consumption, and financial development degrade the environment and resource depletion; however, technological innovations are inclined towards cleaner technologies. For asymmetric findings, we employ the non-linear autoregressive distributive lag technique recently introduced by Shin et al. (2014). The findings validate the existence of an asymmetric relationship between transport energy consumption and environmental indicators. The policymakers' prerequisites the alternative energies apart from conventional energies in the transport sector with technological innovations in transport sector energy consumption like the electronic and hybrid vehicles for a cleaner environment.

Effect of "green technology-institution" collaborative innovation on ecological efficiency-the moderating role of fiscal decentralization

With the tightening of resource constraints and the proposal of the Chinese High-quality Development strategy, innovation-driven has emerged as a new option to balance economic progress with environmental protection. The paper takes Chinese inter-provincial panel data from 2007 to 2017 as a research sample and is based on a spatial Durbin model, investigating the association among green technology innovation (GTI), "green technology-institution" collaborative innovation, and ecological efficiency (EE), while fiscal decentralization is discussed as a moderating factor. According to the results, "green technology-institution" collaborative innovation is positively promoting ecological efficiency and causing spatial spillovers if the economic distance is taken into account. Compared with the single role of green technology innovation, collaborative innovation has a greater role in improving ecological efficiency. Among them, to improve ecological efficiency, it is best to develop green technology innovation and encourage production institutions in a coordinated manner. According to the moderating effect, fiscal decentralization moderates the impact of innovation collaboration on ecological efficiency in a negative way. Therefore, balancing the decentralization of local fiscal expenditures is important to promoting China's ecological efficiency. In addition, China should purposefully promote the degree of synergy between green technology innovation and related institutions for enhancing eco-efficiency.

Realizing the Sustainable Development Goals through technological innovation: juxtaposing the economic and environmental effects of financial development and energy use

The BRICS comprise of group of emerging market economies which are committed to achieving the Sustainable Development Goals agenda of the United Nations by the end of the year 2030. In this regard, it is critically important for these nations to sustain their annual rise in their economic growth rates while simultaneously declining the rate of discharge of carbon dioxide emissions. Against this backdrop, this study aims to investigate how financial development, greater primary energy consumption, and technological innovation affect the prospects of the BRICS nations in achieving economic and environmental sustainability. Considering the period from 1990 to 2020 and utilizing methods that are robust to working with cross-sectionally dependent, heterogeneous, and endogenous panel data, the key analytical findings derived in this study reveal that higher levels of financial development, primary energy consumption, and technological innovation boost the per capita economic growth rates of the BRICS nations. Besides, technological innovation also moderates the financial development-economic growth and the primary energy consumption-economic growth nexuses by jointly boosting economic growth rates with these two macroeconomic variables. On the other hand, financial development and higher primary energy consumption are seen to boost the annual per capita carbon dioxide emission growth in these emerging nations, while technological innovation is observed to do the opposite. Furthermore, technological innovation is witnessed to moderate the nexus between energy use and economic growth to further reduce the emission growth rate in the BRICS nations. Accordingly, a set of policies are recommended to the concerned governments in order to enable the BRICS nations to attain the Sustainable Development Goals agenda.

Heterogeneous impact of eco-innovation on premature deaths resulting from indoor and outdoor air pollution: empirical evidence from EU29 countries

Environmental innovations play a vital role in reducing air pollution and the number of pollution-related mortality. Most of the previous studies have examined the role of eco-innovations in environmental quality. However, to our knowledge, no study has evaluated the effects of eco-innovation on air pollution as a cause of mortality. For this purpose, this research examines the effect of eco-innovations on premature deaths from indoor and outdoor air pollution in twenty-nine European countries from 1995 to 2019. The Method of Moments Quantile Regression (MM-QR) is used to assess the impacts. The results confirm the heterogeneous effects of the main variables in both models. Both models indicate that eco-innovations reduce premature deaths from outdoor and indoor air pollution, and these effects are more significant in high quantities (75th and 90th). Also, the effect of eco-innovations on reducing mortality due to indoor pollution is more significant than that related to outdoor pollution. Eco-innovation, economic growth, renewable energy consumption, and urbanization reduce premature mortality indoors and outdoors, but CO₂ emissions increase this mortality. The results of the Dumitrescu-Hurlin causality test also support that all variables, including eco-innovation and CO₂ emissions, have a bidirectional causal relationship with indoor (LIND) and outdoor (LOUT) mortality due to air pollution. Governments and politicians can help mitigate this problem by providing more environmental innovations by increasing support packages and reducing taxes.

The Relationship between Environmental Regulation, Green-Technology Innovation and Green Total-Factor Productivity-Evidence from 279 Cities in China

This paper employs the SBM-DDF method to measure the index of green total-factor productivity (GTFP), based on the panel data of 279 prefecture-level cities in China from 2007 to 2019, and constructs a spatial Durbin model (SDM) and a threshold effect to empirically test the effects of dual environmental-regulations and green technological innovation on GTFP. The results are as follows: (1) the SDM supports a nonlinear contribution of dual environmental-regulations spillover to GTFP. The relationship between formal environmental-regulation and GTFP is an inverted U-shape, while a U-shaped nonlinear relationship is found between informal environmental regulation and GTFP. (2) Green technology innovation has a significant negative moderating effect on the process of dual environmental-regulations affecting GTFP in local regions, but a positive moderating effect on informal environmental regulation in neighboring regions. (3) There is a significant green technology innovation threshold effect of dual environmental-regulations affecting GTFP. Specifically, the promotion effect of dual environmental-regulations on GFFP gradually increases as the level of green technology innovation increases.

Research on the impact mechanism of heterogeneous environmental regulation on enterprise green technology innovation

Green technology innovation (GTI) is an effective way to promote the green development of economy, and government environmental regulations are an important means to encourage enterprises to carry out GTI. Taking Chinese A-share listed enterprises from 2010 to 2019 as samples, this paper divides environmental regulations into three categories: command-based environmental regulation (ER₁), market-based environmental regulation (ER₂) and voluntary environmental regulation (ER₃), studies their impact on enterprise GTI, and discusses the joint effect of enterprise research and development (R&D) investment and government support from the perspective of internal and external linkage of enterprises. In addition, this paper also analyzes the compound effect and time effect of environmental regulation. The research conclusions are as follows: (1) From the perspective of policy types, both ER₁ and ER ₂ could stimulate enterprises to carry out GTI, and the promotion effect of green utility model patents is slightly higher than that of green invention patents. ER₃ inhibits enterprise GTI. In addition, this paper finds that the effect of three environmental regulations acting at the same time is greater than that of one of them. (2) The mechanism analysis shows that the R&D investment of enterprise positively could moderate the relationship between ER₂ and green invention at the significance level of 5%, positively moderate the relationship between ER₂ and green utility model patent at the significance level of 1%, and negatively moderate the relationship between ER₃ and green utility model patent at the significance level of 5%. The government support could moderate the relationship between environmental regulation and green utility model patents at the significance level of 5% and 10%. (3) The effect analysis shows that the transformation rate of GTI in China needs to be improved. The three environmental regulations could have an effect on enterprise GTI in a short period, and ER₁ has the fastest effect. (4) Considering the differences in the level of economic development and resource endowments in various regions of China, this paper classifies the sample enterprises and finds that the impact of environmental regulation on enterprise GTI is heterogeneous in terms of location, ownership nature, factor density and industry type. The research results provide the important reference for the formulation and implementation of environmental regulation policies according to local conditions.

Coupling Coordination Analysis of Regional IEE System: A Data-Driven Multimodel Decision Approach

Coordinating regional innovation–economy–ecology (IEE) systems is an important prerequisite for overall continuous regional development. To fully understand the coordination relationship among the three, this study builds a data-driven multimodel decision approach to calculate, assess, diagnose, and improve the regional IEE system. First, the assessment indicator system of the regional IEE system is established. Secondly, the range method, entropy weight method, and weighted summation method are employed to calculate the synthetic developmental level. Thirdly, a multimodel decision approach including the coupling degree model, the coordination degree model, and the obstacle degree model is constructed to assess the spatiotemporal evolution characteristics of the regional IEE system coupling coordination and diagnose the main obstacles hindering its development. Finally, the approach is tested using Anhui Province as a case study. The results show that the coupling coordination degree of the Anhui IEE system presents a stable growth trend, but the coupling degree is always higher than the coordination degree. The main obstacle affecting its development has changed from the original innovation subsystem to the current ecology subsystem. Based on this, some countermeasures are put forward. This study, therefore, offers decision support methods to aid in evaluating and improving the regional IEE system.

Spatial effect analysis of heterogeneous green technology innovations on pollution emission reduction: evidence from China's power industry

Based on the provincial panel dataset of the power industry in China from 1997 to 2020, this study employed the dynamic spatial Durbin model (SDM) to investigate the spatial effects of heterogeneous green technology innovations (GTIs) of the power industry chain-clean energy GTIs (GTI1), fossil-fueled GTIs (GTI2), energy-saving GTIs (GTI3), and power transmission technology innovations (GTI4)-on three pollution emission reduction: SO2, solid waste (SW), and waste water (WW). The empirical results revealed that three pollution emissions showed "path dependent" and "snowball effects." GTI1, GTI2, and GTI3 reduced local SO2 and SW emissions, while GTI2 and GTI4 had no obvious reduction effects on WW emissions. Different GTIs had the same spatial "symbiotic effects" on SO2 emission reduction in the short term, showing positive spatial spillover reduction effects. Finally, it is of great significance to make full use of the positive spatial spillover effects of GTIs to promote the regional collaborative linkage of pollutant governance in the power industry.

Green technology innovation and carbon emissions nexus in China: Does industrial structure upgrading matter?

Compared with traditional technological innovation modes, green technology innovation is more targeted for low carbon development and critical support for countries worldwide to combat climate change. The impact of green technology innovation on carbon emissions is considered in terms of fixed effect and mediating effect models through industrial structure upgrading. For this purpose, the sample dataset of 30 provincial administrative areas in China from 2008 to 2020 is employed. The results demonstrate that green technology innovation exerts significantly inhibitory effects on carbon emissions, whose conclusion still holds after removing municipalities and replacing the dependent variable. Industrial structure upgrading is vital for green technology innovation to diminish carbon emissions. There is significant regional heterogeneity in the effects of green technology innovation on carbon emissions, i.e., the direct and indirect impact of green technology innovation on carbon emission reduction is significant in the eastern-central area, but its effect is insignificant in the western region. Therefore, it is essential to realize carbon emission reduction by further bolstering green technology innovation and accelerating industrial structure upgrading to fulfill the synergy of technology and structure.

Management of Green Economic Infrastructure and Environmental Sustainability in One Belt and Road Enitiative Economies

Green infrastructure has been considered as one potential solution for improving air quality as well as enhancing environmental sustainability in the modern era. Therefore, the study aims to examine the impact of green economic infrastructure on environmental sustainability in one belt and road initiative (OBRI) economies for the period 2007 to 2019. For empirical investigations, the study adopts 2SLS and GMM approaches. The study uses three proxies to measure green economic infrastructure, namely, green logistics, use of the internet, and green technology. Our 2SLS findings demonstrate that green logistics increases CO2 in OBRI, Central Asia, MENA and reduces CO2 in Europe. However, GMM findings report that green logistics increases CO2 in OBRI, central Asia, and MENA and reduces CO2 in Europe. While our 2SLS findings show that internet use reduces CO2 in OBRI and East and Southeast Asia Europe and increases CO2 in MENA. While GMM findings reveal that the use of the internet reduces CO2 in OBRI and Europe and increases in East and Southeast Asia and MENA. While green technology also enhances environmental sustainability in OBRI. Based on the findings, environmental policies can be revised for OBRI economies.

Research on the impact of energy technology innovation on total factor ecological efficiency

Promoting sustainable economic development from the perspective of energy technology is crucial, given limited energy resources and severe environmental pollution. Based on the panel data of China's provinces from 2000 to 2017, we empirically explore the complex relation among energy technology innovation, regional economic growth, and total factor ecological efficiency. We innovatively introduce ecological footprint as one of the input indicators of total factor ecological efficiency measured using slack-based measure-data envelopment analysis, thereby comprehensively quantifying sustainable economic development. Moreover, we adopt spatial econometric and threshold regression models to empirically assess the relation between energy technology innovation and total factor ecological efficiency. We infer the following conclusions. First, both China's provincial ecological efficiency and energy technology innovation possess significant spatial positive correlation, manifesting a spatial geographical distribution agglomerated by similar characteristics. Second, the regional energy technology innovation has a remarkable spatial effect on ecological efficiency, displaying a U-shaped trend. Compared with the direct effect, the spatial spillover effect is more intense, along with a much stronger long-term influence. Third, under the regulation of regional economic growth, two inflection points exist in the effect of energy technology innovation on ecological efficiency. Energy technology innovation is not conducive to total factor ecological efficiency under low regional economic growth. No significant relation exists between the two core variables under medium regional economic growth. Furthermore, energy technology innovation positively influences total factor ecological efficiency only when regional economic growth reaches a certain peak.

Research on the coordination characteristics and interaction between the innovation-driven development and green development of the Yangtze River Economic Belt in China

Both innovation-driven development and green development are important ways to achieve regional sustainable development. This study considers the innovation-driven development and green development evaluation systems of 130 cities in the Yangtze River Economic Belt. The entropy TOPSIS method is used to measure the innovation-driven development index and the green development index of 130 cities in the Yangtze River Economic Belt. Then, a coupling coordination evaluation model and a spatiotemporal heterogeneity analysis model are constructed to discuss the coupling coordination index of regional innovation-driven development and green development in the Yangtze River Economic Belt and to determine its temporal and spatial distribution characteristics. Finally, we choose a spatial panel regression model to explore the relationship between the innovation-driven development index and the green development index of the Yangtze River Economic Belt. The research results show that there is a significant difference between the innovation-driven development index and the green development index of the 130 cities in the Yangtze River Economic Belt in terms of the temporal and spatial distribution. The level of innovation-driven development lags behind the level of green development on the whole, and the two fail to form a good spatial matching degree. The coordination index of the two has an imbalanced distribution feature, and there is a significant direct or indirect relationship between the two structural indicators in a mathematical sense. This study improves the academic community's understanding of the interaction between innovation-driven development and green development, provides scientifically based support for green development, and offers guidance for the implementation of innovation capabilities.

Does financial development reinforce ecological footprint in Singapore? Evidence from ARDL and Bayesian analysis

Singapore has been ranked in the most dynamic financial market and the highest ecological deficit country, indicating that the trade-off hypothesis may exist. The main goal of the present study is to probe the impact of financial development, economic growth, and human capital on ecological footprint in Singapore from 1980 to 2016. The outcomes obtained from the Autoregressive Distributed Lag (ARDL) method have failed to provide a clear impact of financial sector development on ecological footprint. However, the Bayesian analysis reveals that both financial development and economic growth have a harmful influence on EF, while the impact of human capital is beneficial. A theoretical conclusion derived is that monetary expansion policies should be associated with improving human capital to achieve the United Nations SDGs in the context of Singapore. The findings of the study are of particular interest to policymakers for developing sound policy decisions for sustainable economic progress which is not at the cost of environment.

Impact of innovation in renewable energy generation, transmission, or distribution-related technologies on carbon dioxide emission in the USA

Innovation in renewable energy generation, transmission, or distribution-related technologies (IREGT) is an effective way to deal with environmental pollution. Even though previous studies have focused on renewable energy generation in the USA, the impact of IREGT on carbon dioxide emissions (CO₂e) remains widely unexplored. Recognizing this gap, this study inspected the IREGT-CO₂e nexus in the USA, with international collaboration in green technology development (ICGTD), trade openness (TO), renewable energy consumption (REC), and gross domestic product per capita (GDPPC) as control variables from 1990Q1 to 2018Q4. The study applied the canonical cointegration regression (CCR), fully modified ordinary least squares (FMOLS) method, and dynamic ordinary least squares (DOLS) approach to assess the long-run association among variables. First, the findings validated the cointegration relationship among IREGT, ICGTD, TO, REC, GDPPC, and CO₂e. Second, the results indicated that the IREGT, REC, and ICGTD had benefited the USA in mitigating CO₂e. Third, GDPPC and TO were positively connected to CO₂e. Fourth, the Granger causality depicted that GDPPC, TO, and ICGTD Granger caused CO₂e in the USA, while IREGT and CO₂e had a bidirectional relationship. The study's findings encourage the government should devise policies to induce higher research institutions and private enterprises to engage in IREGT.

Do international collaborations in environmental-related technology development in the U.S. pay off in combating carbon dioxide emissions? Role of domestic environmental innovation, renewable energy consumption, and trade openness

Many economies are seeking new ways to improve environmental quality through international collaboration in environmental-related technology development (ICERTD). Cost reduction, green market penetration, and green technology development are central to global partnerships for sustainable development, even though no empirical study explains the ICERTD-carbon dioxide (CO₂) emissions nexus. The paper fills this knowledge gap in the environmental economics literature by examining the relationship between ICERTD and CO₂ emissions in the U.S. from 1990Q1 to 2018Q4 using domestic environmental innovation, trade openness, renewable energy consumption, and gross domestic product per capita as control variables. Fully modified ordinary least squares, dynamic ordinary least squares, and correlated component regression methods were employed for testing the long-run nexus among the variables. The present study revealed that (i) a long-run cointegration existed among ICERTD, domestic environmental innovation, trade openness, renewable energy consumption, gross domestic product per capita, and CO₂ emissions; (ii) ICERTD, domestic environmental innovation, and renewable energy consumption benefited the U.S. in lowering CO₂ emissions in the long run; and (iii) trade openness and gross domestic product per capita were positively associated with CO₂ emissions. This study recommends important policy recommendations for increasing ICERTD for decarbonization.

Do higher education research and development expenditures affect environmental sustainability? New evidence from Chinese provinces

Even though higher education R&D expenditures (HEEXP) are important determinants of economic growth that facilitate science, technology, new ideas, and innovation, yet its effect on environmental sustainability remains unexplored. This paper examines the nexus between HEEXP and carbon dioxide emissions (CO₂e), followed by control variables such as electricity consumption (EC), foreign direct investment (FDI), gross domestic product (GDP), and total population (TP) for the period 2000Q1-2019Q4. Data were evaluated using different tests, e.g., the cross-sectional dependence test, cross-sectionally augmented Dickey-Fuller unit root test, Westerlund error-correction-based panel cointegration test, mean group, augmented mean group, common correlated effects mean group, and Dumitrescu-Hurlin panel causality test. First, the results validated the cointegration association among HEEXP, EC, FDI, GDP, TP, and CO₂e. Second, the finding showed significant long-term negative nexus between HEEXP and CO₂e. Third, the findings indicated that electricity consumption, foreign direct investment, gross domestic product, and total population are the important factors that intensify the overall situation of CO₂e. Fourth, the results indicated that there exists bidirectional causality between EC and CO₂e; FDI and CO₂e; GDP and CO₂e; POP and CO₂e; and HEEXP and CO₂e. This paper's findings call for devising policies and strengthening financial support to induce higher education for developing green patents.

Energy–Growth Nexus in the MENA Region: A Dynamic Panel Threshold Estimation

This study provides new evidence regarding the nonlinear relationship between energy consumption and economic growth in the Middle East and North Africa (MENA) region for the 1990–2014 period. The empirical estimation is conducted using a dynamic panel threshold model. We found one threshold in the relationship between energy consumption and economic growth and one threshold in the relationship between carbon dioxide (CO2) emissions and economic growth. The results indicate that energy consumption positively and significantly affects economic growth in the low energy consumption regime. In contrast, it has a negative and significant impact on economic growth in the high energy consumption regime. Moreover, CO2 emissions are positively and significantly related to economic growth in the low regime of CO2 emissions. Nevertheless, the relationship between CO2 emissions and economic growth in the high CO2 emissions regime is negative and significant. Therefore, policymakers should implement other effective energy policies, such as stricter regulations on CO2 emissions, increase energy efficiency, and replace fossil fuels with cleaner energy sources to avoid unnecessary CO2 emissions and combat global warming. Future studies should identify the root causes of failures and issues in real time for inflation and link the energy–growth nexus to achieving the 2030 Sustainable Development Goals (SDGs) Agenda, Goal 7: Affordable and Clean Energy.

The role of trading environment-friendly goods in environmental sustainability: Does green openness matter for OECD countries?

Achieving carbon neutrality targets is a major challenge for Organization for Economic Co-operation and Development (OECD) countries that experience mounting ecological degradation over the last few decades. To deal with this situation, the trading of green products may play a crucial role. However, previous studies have not captured the net impact of green trading, and also the international trade basket used in these studies is proxied by the trade openness index including both environment-friendly and not-so-friendly goods. To provide a solution, this research intends to capture the net effects of green goods on the environment over the period 2003 to 2016 in 35 OECD countries. This study extends the literature by computing a new Green Openness Index based on the OECD Combined List of Environmental Goods (CLEG) basket that consists of 255 products. After this, an empirical model based on the Environmental Kuznets Curve (EKC) hypothesis is developed to test the role of the Green Openness Index in environmental sustainability using methodology robust against heterogeneity and cross-sectional dependence. The outcomes unfolded the validity of the EKC hypothesis in 35 OECD countries. Empirical estimates confirmed that the Green Openness Index, which considers traditional environment-friendly goods as well as environmentally preferable goods, stimulates environmental sustainability. Finally, numerous policies are directed to accomplish carbon neutrality targets.

Dynamic Nexus between Technological Innovation and Building Sector Carbon Emissions in the BRICS Countries

The greatest contribution to global CO₂ emissions comes from the BRICS countries (Brazil, Russia, India, China, and South Africa). The building sector in these countries is one of the sectors that increases CO₂ emissions significantly. Increasing CO₂ emissions in the building sector adversely affects sustainable development. Therefore, measures to mitigate environmental damage become substantially important. Improvements in technological innovation can be among the measures considered to mitigate CO₂ emissions. In this study, the effects of technological innovation on the carbon emissions caused by the building sector are examined by panel data methods for the BRICS countries in the period 1992-2018. It has been observed that there is a long-term relationship between the series. As the results of Dynamic Common Correlated Effects indicated, increased technological innovation reduces carbon emissions. This result is meaningful to encourage investments related to technological innovation.

The role of green innovation and tourism towards carbon neutrality in Thailand: Evidence from bootstrap ADRL approach

The recent years have been marked by the role of green tech innovation in decreasing carbon emissions worldwide to attain the carbon neutrality target. Despite many studies examining the nexus between the former and energy consumption, tech innovation's effects on CO2 releases have not been extensively researched, and the extant empirical findings are often contradictory. Also, a major concern regarding the available literature is the scarcity of papers that scan the impact of tourism on carbon emissions, even though the industry has a high potential to affect ambient air pollution. In this case, the evidence is mixed, and no consensus among academics on the relationships between the two. Therefore, this study seeks to investigate the relevance of green innovation and tourism in decreasing environmental damage in Thailand based on the bootstrapping ARDL causality model suggested by (McNown et al., 2018). This specification includes a new cointegration feature and conventional ARDL bounds tests, which increases the power of the t- and of the f-test and has several advantages, being more adequate for dynamic models with more than one explanatory variable. Our findings reveal that green innovation and tourism lead to lower environmental damage by reducing CO₂ emissions, similar to foreign investments and that green tech innovation improves the environmental quality via lower carbon emissions.

Towards a green economic policy framework in China: role of green investment in fostering clean energy consumption and environmental sustainability

Recently, China has relished rapid green investment, and its influence on clean energy consumption and environment is substantial. Therefore, this study scrutinizes the effects of green investment on clean energy consumption and CO2 emissions in China by using autoregressive distributed lag model (ARDL) approach over time from 1998 to 2019. The results show that green investment tends to have a positive effect on clean energy consumption in China in the long run. The outcomes of study also show that green investment also tends to have a negative effect on CO2 emissions in China, but it has a small effect on carbon emissions in magnitude in the long run. Importantly, possible channels revealed green investment encouraging consumers and producers to consume clean energy, thereby positively affecting the environmental quality in China. Other control variables' findings show that environmental tax and financial development have increased the environmental quality by decreasing the CO2 emissions. Based on the findings, it recommends that green investment is considered necessary for encouraging clean energy consumption to reduce carbon emissions in high pollutant economies.

The effects of green innovation and environmental management on the environmental performance and value of a firm: an empirical study of energy-intensive listed companies in China

There is a debate in the literature about the relationship between green innovation, environmental management, environmental performance, and the value of a firm. Herein, the effects of green innovation and environmental management on environmental performance are analysed using a stochastic frontier model for energy-intensive listed companies from 2011 to 2017; the effects thereof on the value of a firm are assessed empirically. The results show that green innovation and environmental management have a positive effect on corporate environmental performance, and green innovation plays a complete mediating role between environmental management and environmental performance. The significant positive effect of green innovation on value of a firm confirms Porter's hypothesis, but the positive effect of environmental management on value of a firm is not verified. Finally, recommendations that are aimed at improving corporate environmental performance are given.

Environmental Outcomes of Green Entrepreneurship Harmonization

Establishing equilibrium between business growth and environmental sustainability is one of the core focuses of green entrepreneurship. However, the scarcity of resources, ecological concerns, business growth, and survival are among the issues that are recognized by entrepreneurs. In the light of the Natural Resource-Based View (NRBV) and Dynamic Capability View, this study aims to examine the effects of Green Innovation Performance (GIP) on Green Entrepreneurship Orientation (GEO) and Sustainability Environmental Performance (SEP). As advocated by NRBV, this study emphasizes the importance of pursuing the three types of distinct yet interrelated environmental strategies and its association impact on GEO. The results indicated that internal green dynamic capabilities, namely, green absorptive capacity, environmental cooperation, and managerial environmental concern to have significant positive effects on GIP, where GIP positively impacted GEO and SEP. Besides, GIP partially mediated the relationship between internal green dynamic capabilities on GEO and SEP. The results also demonstrated that environmental regulations significantly moderated the relationship between GEO and SEP. Furthermore, by linking these three concepts in a single model, this study theoretically pioneering and responding to bridge significant gaps emerged in the NRBV theory. This study provides crucial practical implications for entrepreneurs, policymakers, and academicians. Limitations were also discussed.