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Since 1990, global forest area has been reducing; tropical forests have suffered from different anthropogenic and natural factors that account for forest loss. Tropical deforestation is the second driver of anthropogenic emissions; increasing demand and investments in tropical forests drive these emissions. These forests attract significant foreign direct investments, but the effects of these investments on carbon emissions from land use, land-use change, and forestry are not well enshrined in the literature for the countries under study. This paper seeks to analyse the impact of foreign direct investments on carbon emissions from land use, land-use change, and forestry amongst 30 tropical forest countries from 1996 to 2019. The sampled countries were disaggregated by tropical blocs: Amazon, Congo basin, Australasia, and Southeast Asia, and by income levels; low-income, lower-middle, upper-middle, and high-income. The findings reveal a U-shape structure of the impact of FDI on carbon emissions from LULUCF within Congo basin and Amazon countries; at higher levels of FDI, emissions from LULUCF will increase while Australasia and Southeast Asian countries show an inverted U-shape impact, thus at higher levels of FDI, there will be a negative and significant impact on carbon emissions from LULUCF. The income levels reveal an inverted U-shape for low-income and high-income countries and a U-shape for upper-middle-income countries; the impact for lower-middle-income countries is not significant. Overall, for the whole sample, the impact depicts a U-shape. This paper proposes high-level development of environmental conditions for FDI for different sectors that align with country and regional green growth plans. Enhancing national and regional governance systems to enforce decisions and fight corruption effectively can significantly promote green FDI for green growth. [ABSTRACT FROM AUTHOR]

This paper firstly uses the DEA-based Range Directional Model (RDM) and the Global Malmquist–Luenberger (GML) index to calculate the Green Efficiency Index (GEI) of China's cities under the constraints of pollution emissions, energy consumption, and natural resource occupancy. The GEI shows that the average green efficiency of the 285 sample cities achieved a total improvement of 10.1% from 2003 to 2019. The average cumulative improvement rate of green efficiency in the 110 cities in Pollutants Emission Trading Pilot Scheme (PETPS) from 2003 to 2019 was 14.9%, which was higher than the average of non-pilot cities (8.6%). Subsequently, this paper constructs a spatial difference-in-differences model (Spatial-DID) to empirically test the green efficiency promotion effect of PETPS from two aspects: local and spatial spillover. It is found that PETPS can promote the progress of local green efficiency in pilot cities, but there is a spatial spillover effect that is not conducive to the green efficiency progress in surrounding areas. The results of the mediation effect analysis show that the launch of PETPS will significantly reduce the clustering of industrial production activities in the pilot cities, thereby accelerating the green efficiency progress. However, PETPS can also promote clustering of industrial production activities in surrounding areas, thereby inhibiting the green efficiency progress in surrounding areas. These analysis results can fully explain the cause of the negative spatial spillover effect of PETPS. [ABSTRACT FROM AUTHOR]

As one of the most important macroeconomic regulation methods, fiscal and tax policy is supposed to play an active role in green economic transformation. Industrial structure optimization is a fundamental approach to address environmental problems, which has been fully demonstrated in the current studies. It is necessary to identify whether the fiscal and tax policy can promote the green economic transition through optimizing industrial structure. Taking property tax policy as an example, this paper investigates whether fiscal and tax policy promotes the green transformation of the urban economy from the perspective of industrial structure upgrading. The results show that the fiscal and tax policy implemented for a certain industry has a significant positive spillover effect on the optimization of the city's overall industrial structure. Scientific and reasonable fiscal and tax policy accelerates the intensive development of urban economy by promoting the upgrading of urban industry. These findings suggest that in terms of cities in the new and old kinetic energy transformation period, government should consider the upgrading of industrial structure in the formulation of fiscal and tax policy and attach great importance to the green development of urban economy. [ABSTRACT FROM AUTHOR]

The pilot of Accountability Audit of Natural resources (AANR) is an important initiative for the Communist Party of China Central Committee to eradicate environmental pollution and promote the construction of ecological civilization. The purpose of this study is to explore the relationship between AANR and green innovation in heavily polluting enterprises, so as to promote regional sustainable development. With a sample of the national key monitoring enterprises in China from 2011 to 2018, this paper investigates the impact of AANR on green innovation in heavily polluting enterprises by applying the multi-period difference-in-differences model. The results indicate that AANR significantly promotes green innovation in heavily polluting enterprises. The results of mechanism testing indicate that AANR stimulates green innovation by promoting government environmental governance and government innovation-driven strategy. The heterogeneity testings indicate that the promoting effect of AANR on green innovation in heavily polluting enterprises is more significant in regions with higher environmental carrying capacity, higher pressure of GDP achievement and higher transparency of government environmental information. Therefore, China should deepen the enforcement of AANR to promote the green transformation of heavily polluting enterprises. [ABSTRACT FROM AUTHOR]

Based on the panel data of 625 industrial listed enterprises of China from 2012 to 2020, this paper employs the method of propensity score matching–difference in difference to investigate the effect of financial–industrial integration on the enterprise's green development performance and the moderating role of green technology innovation on the relationship between the two is also addressed. It finds that first, financial–industrial integration has a significant promoting effect on the improvement in green development performance of enterprises, and green technology innovation has a positive moderating effect on the relationship between the two. In addition, the effect of financial–industrial integration on enterprise's economic and social performance is not significant, and it mainly promotes enterprise's green development by stimulating environmental performance. Moreover, the degree of financial–industrial integration has a moderate range in which the role of financial–industrial integration can be better played. Further, compared with state-owned enterprise and large-scale enterprise, financial–industrial integration is more conducive to the green development of non-state-owned enterprises and small-scale enterprises. [ABSTRACT FROM AUTHOR]

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

Carbon emissions are a major contributor to global warming and climate change. The government has adopted carbon tax (CT) and cap-and-trade policies to reduce carbon emissions from carbon companies. This paper develops a production–inventory model for scarce perishable goods under different carbon policies and outside green technology. This study covers the contribution of energy-efficient green technology in a multi-stage supply chain to control carbon emissions in producing and transporting goods from the manufacturer to the dealer. However, it discusses a different combination of carbon policies chosen for manufacturers and retailers in their countries. According to the findings, changes in carbon pricing, CT, and exchange rates under various policy combinations have varying effects on the entire supply chain, each member's interests, and the social benefits of reducing carbon emissions. It seeks to provide useful information to decision-makers in businesses or supply chains, especially multinational corporations, to make decisions related to fixed rate CT and cap partial deficit cases, long cycle time, reasonable profit with small value, and long term and low cost of green technology investment. The main objective is to find the best material sourcing, production, and distribution strategy for manufacturers and the best replenishment strategy for retailers to maximize the overall joint profitability of the supply chain. In summary, sensitivity analysis has provided an optimal solution management implication based on certain key parameters and CT size. [ABSTRACT FROM AUTHOR]

Green economic development is an effective tactic for China to cope with the predicament of resources and the environment. As "smoke-free industries", producer services are becoming the main contributors to urban green economic development (UGED). The paper adopts the super-efficiency EBM model to estimate the UGED index of 268 Chinese cities from 2005 to 2019. Based on the theoretical analysis, econometric models are constructed to systematically test how the specialized and diversified agglomeration of producer services impacts UGED. The findings reveal that both agglomeration modes considerably enhance UGED in the local area and its surroundings. Diversified agglomeration exerts a stronger radiation and promotion effect than specialized agglomeration. In addition, the impact of the two agglomeration modes on UGED demonstrates pronounced heterogeneity in urban scales, economic development stages, and industries. Furthermore, mechanism studies suggest that agglomeration substantially boosts UGED by improving human capital, technological innovation, and upgrading industrial structure. As such, our findings serve as an empirical basis for understanding the mechanism of the impact of PSA on UGED and also offer significant insight for local governments to adopt differentiated industrial policies to enhance the positive agglomeration effect on UGED. [ABSTRACT FROM AUTHOR]

How to formulate an effective intervention mechanism to stimulate green technological innovation (GTI) has become a key problem that plagues the government. Existing researches on GTI seldom consider consumer preference and market competition, and there is a lack of comparative research on GTI governance mechanisms among different governments. Therefore, considering consumer green technology preference and market competition, this paper proposes three different government intervention policies, i.e., no intervention (B), intervening firm (F) and intervening consumer (C), and develops a three-layer Stackelberg game model including the government, green and non-green firms and consumers to study the impact of three government interventions on GTI, product pricing and profits. Backward induction is used to solve optimal decisions. Then, to maximize social welfare, the optimal government intervention schemes under different conditions are discussed. Considering the impact of consumer behavior and product competition on GTI, this paper innovatively compares the optimal decision-making of manufacturers and the optimal government intervention scheme selection in different conditions from the perspective of maximizing social welfare. The results show that there is no optimal decision that is immutable. Market share of green products is positively correlated with the production cost adjustment coefficient. The intervention decision, GTI and green product pricing are negatively correlated with the green improvement coefficient and positively correlated with the environmental improvement coefficient. This research can be used to better guide the government how to design and select effective GTI incentive mechanism and guide manufacturers how to make the best response mechanism in the competitive environment. [ABSTRACT FROM AUTHOR]

This paper introduces the vitality of science and technology innovation and the ability to coordinate science and technology strength of green development, builds green innovation knowledge system, studies the new endogenous growth law driven by green innovation knowledge system under the active, conscious and autonomous practice of green low-carbon behavior has become a common form. This paper constructs a green development equilibrium model of economic system from the aspects of production, household and government intervention and discusses the relationship between economic growth and environmental quality driven by green development behavior. In the production part, the green innovation knowledge system becomes endogenous factor of production under the stimulation of vitality of science and technology innovation and integrates into the production of green low-carbon behavior goods. In the consumption part, the household utility function is given from the aspects of environmental quality, carbon emission and consumption. Through empirical analysis and research, the environmental effects which are cognitive dissonance effect and loss aversion effect can be obtained. [ABSTRACT FROM AUTHOR]

In this paper, green finance is incorporated into the theoretical framework of technological progress bias to investigate the internal mechanism of green finance influencing environmental technological progress bias and the cleaning of industrial structure. Quantitative analysis is carried out by parameter calibration and numerical simulation. The results show that the environmental technology progress bias has obvious path-dependent characteristics. By means of financing scale and financing cost, green finance influences the relative profit, R&D behavior choice and environmental technology progress preference of the two types of R&D firms and then influences the cleaning of industrial structure through direct productivity effect, indirect price effect and market size effect. Only when the proportion of financing scale of clean R&D departments or the interest rate subsidy exceeds a certain critical value, can green finance successfully induce the occurrence of clean technological progress and promote the cleanliness of industrial structure. However, when the proportion of financing scale or interest rate subsidy of clean R&D departments is lower than a certain critical value, the improvement effect of green finance on the output value of clean industry is offset by the effect of polluting technological progress, which is not conducive to the clean industrial structure. [ABSTRACT FROM AUTHOR]

To ameliorate the efficiency of urban green innovation is the key to realizing green economic transition. This paper constructs a Super-NSBM model with green patents as the intermediate output, uses this model to assess and decompose the green innovation efficiency of 284 Chinese cities, and finally analyzes the spatiotemporal characteristics and influential factors. The research result showed the gap of urban green innovation total efficiency among various regions in China is narrowing, while the spatial differentiation of decomposition efficiency is deepening. This means that a spatial collaborative innovation division pattern of "Eastern Region R&D + Southwest and Northeast Region Transformation" has gradually formed. In the meantime, this paper also found that the spillover effects of the urban green innovation total efficiency and phased efficiency all can form a significant demonstration effect on the surrounding areas. Finally, financial agglomeration, industrial structure, knowledge sharing, economic activity, higher education, opening, and environmental regulations may affect urban green innovation total efficiency and phased efficiency, and this effect has regional heterogeneity. [ABSTRACT FROM AUTHOR]

As an ecological barrier to ensure the high-quality development of China's economy, the Yangtze River Economic Belt has attracted more and more attention from academic circles on how to promote the green development of the Yangtze River Economic Belt. This paper uses the SBM directional distance function and the Malmquist–Luenberger index to measure the green total factor productivity of 110 cities in the Yangtze River Economic Belt from 2006 to 2018, and then based on the panel threshold model to empirically explore the intensity of environmental regulations that induce trade openness and promote green total factor productivity. Studies have shown that: Firstly, trade openness has significantly inhibited the increase in green total factor productivity, but environmental regulations can play a positive regulatory role, that is increasing the intensity of environmental regulation can alleviate the adverse effects of trade openness, and it is mainly to improve the adverse effects by promoting the progress of green technology. Secondly, the results of the panel threshold model show that environmental regulations have a nonlinear regulatory effect on trade openness and green total factor productivity. When the intensity of environmental regulations crosses the second threshold, trade openness has a significant positive effect on the impact of green total factor productivity. Finally, the heterogeneity results show that in order to reverse the adverse impact of trade openness on green total factor productivity, the upper, middle and lower reaches of the Yangtze River Economic Belt should formulate relatively strict environmental regulations. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of artificial intelligence, industrial robots, as an important manifestation of artificial intelligence technology application, provide enterprises with a "creative destruction" environment, and play a positive role in energy utilization and environmental governance. Therefore, academics have focused a lot of attention on the question of whether industrial robot application can successfully improve corporate green innovation (CGI), thus achieving green transformation, and upgrading the manufacturing industry. This paper builds a "Bartik instrument variable" to calculate the micro-enterprise robot penetration rate from 2007 to 2019, looks at the effect of industrial robot application on CGI using data from manufacturing listed companies, and discusses the mechanism, heterogeneity, and robustness of this effect. The research finds that industrial robot application significantly improve CGI, indicating that they can promote corporate green technology transformation. This effect not only enhances the scale of CGI but also strengthens the quality of CGI. In addition, the above conclusion still holds after a series of endogeneity and robustness tests. Mechanism research shows that industrial robot application contribute to CGI by improving production efficiency, human capital, and environmental governance levels. It has a good complementary optimization effect on CGI. Furthermore, heterogeneity research shows that industrial robot application has a more significant role in enhancing green innovation for enterprises that are labor-intensive, more intense market competitive, more serious environmental pollution, and have lower level of digital economy development. The research conclusion verifies the effect of artificial intelligence technology and explores its mechanism, which provides empirical references for improving corporate environmental performance and green transformation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study what are the characteristics that make firms less or more prone to greenwashing. We collect data from sustainability disclosures of the S&P top 100 companies, to investigate the determinants of greenwashing. We use content analysis to measure the level of reporting of the companies. We define the "greenwashing" variable as the difference between what the company says it does in terms of commitment to sustainability, and what the company actually does as evaluated by external parties (Bloomberg ESG scores). Our results show that companies in environmentally sensitive industries greenwash less than their counterparts in other industries, as well as companies following the GRI guidelines. Companies that issue a sustainability report and assure it greenwash less than those that do not do it. Contrary to our intuition, companies in industries with close proximity and high visibility greenwash more than their counterparts. A limitation of the paper is the inclusion in the sample of data from one country. Our findings have implications for policy-makers, particularly in Europe, where some European states have already regulated on green issues reporting and lately on blue issues. It might be interesting to consider both the industry effect and the relevance of reporting mechanisms when developing regulation and policies in order to improve the quality of sustainability reporting. We contribute to literature by proposing a new quantitative measure to assess greenwashing practices, to better understand the effect of industry and reporting mechanisms on greenwashing. [ABSTRACT FROM AUTHOR]

Using novel Fourier-based approaches, this paper investigates the effect of green logistics and financial innovation on environmental sustainability in China over the period 2000/Q1-2018/Q4. The Fourier ADL cointegration analysis indicates that all indicators are integrated. Additionally, the findings of the Fourier-ARDL long run indicate as follows: (i) Green logistics mitigate environmental degradation and increase environmental sustainability in China; (ii) in contrast, the impact of financial innovation and economic growth decreases the environmental quality and increases production-based CO2 emissions in the region. The research findings offer valuable insights for policymakers, providing a basis for adopting green logistics operations that promote sustainable practices in China. By implementing such practices, policymakers can mitigate the adverse impacts of economic and financial activities in the country, fostering sustainable development and environmental responsibility. [ABSTRACT FROM AUTHOR]

In the context of global climate change, much hope is placed in technological progress's ability to address environmental problems. However, the persistence of technology inequality across countries undermines environmental technology innovation's contribution to environmental issues. In such a context, this paper introduces a new approach that combines Data Envelopment Analysis (DEA) with the Gini coefficient to gauge technology inequality. Additionally, decomposition analysis is adopted to identify the driving factors affecting technology diffusion. Empirically, the proposed approach is applied to 49 African countries from 2000 to 2017. The results of our study show that, although the unified efficiency of African countries improved slightly during the study period, there is still much room for improvement in terms of economic prosperity and environmental performance. Secondly, there is group heterogeneity between two groups of African countries (low-efficiency group and high-efficiency group) under both managerial and natural disposability. Thirdly, the inequality decomposition revealed that cross-group inequality is the source of group heterogeneity and the main barrier to technology diffusion, followed by within-group inequality. Finally, environmental technology progress exhibits a low contribution to enhancing sustainability in Africa due to technological inequality persistence. In future, it would be quite meaningful to perform sector-level analysis, which could provide more detailed information on sustainability. [ABSTRACT FROM AUTHOR]

Rising temperatures and sea levels, as well as the depletion of natural resource stocks, places green growth more than ever at the center of our political and economic agendas. But how can a country or region exactly "go green"? Transforming current economic structures into a green economy is a complex process. The structure of an economy is determined by the type of jobs that are present in an economy. Therefore, the creation of green jobs is one of the components of the "going green" process. Using occupational data for 27 Brazilian states between 2003 and 2013, this paper examines whether the level of economic complexity of a state explains why one state has a greener occupation space than another. First, we construct a "green jobs index" which quantitatively measures the greenness of the occupation space of a state. We then empirically show that economic complexity has a positive explanatory power when it comes to differences in this green jobs index. We also show that transitioning through this occupational space is a slow and difficult process. Nonetheless, we find evidence of declining regional differences in greenness. Initially, states which had a low green jobs index became relatively greener than states that had initially a high green jobs index. This indicates convergence across states. [ABSTRACT FROM AUTHOR]

Environmental deterioration and global warming has created a substantial impact on international companies to incorporate eco-friendly, green supply chain practices and remain competitive in the market. In food supply chain, the selection of the best supply chain management (SCM) strategy can improve the overall performance and can be crucial in managing the food supply chain challenges and achieving sustainable food supply chain. In this paper, different green SCM strategies were explored and evaluated for food supply chain using combinative distance-based assessment method under interval-valued q-rung orthopair fuzzy information as interval extension of q-rung orthopair fuzzy can effectively handle the ambiguity and uncertainty of preference given by experts in decision making. A generalized p-distance between two interval-valued q-rung orthopair fuzzy numbers is proposed in the current study and is used to formulate interval-valued q-rung orthopair fuzzy Hamming distance and interval-valued q-rung orthopair fuzzy Euclid distance. Five supply chain strategies, namely risk-based, efficiency-based, resource-based, innovation-based, and closed-loop strategy, are evaluated to select best strategy for food supply chain based on different attributes such as green manufacturing, green design and development, green management system, green procurement, and green marketing which contribute toward sustainability. It is found that closed-loop supply chain strategy is the best strategy for food supply chain to attain sustainability. A comparative analysis and sensitivity analysis are done to examine the reliability of results obtained from the proposed framework. [ABSTRACT FROM AUTHOR]

The study investigates the effect of international tourist advents on carbon dioxide discharges in a panel set of hundred countries ranked in order of arrival of tourists over 1995 to 2014, under the background of EKC (Environmental Kuznets Curve) postulate. A multivariate model is adopted grounded on the "Kaya Identity" where the long-run relation concerning the arrival of tourists and carbon dioxide released into the atmosphere are examined through the linkages of economic growth (proxied through new night light data sets), energy intensity use, physical capital formation and human capital formation. The results based on the panel cointegration corroborates the long-run equilibrating association across the set of observations. The methodology of FMOLS, the mean group estimates, DOLS estimation and the Correlated Effects Mean Group estimate enumerate the long-run estimates. Further the results confirm the following causality relationships: tourism-driven emission; economic growth led emission; tourism-driven growth of the economy and gross capital in fixed terms leading the growth of the economy in the short run, built on the Granger causality Wald test. The paper concludes that proper policy direction towards sustainable tourism can reduce emission from tourism in the long run. R and D should focus on the development of green technology and cleaner technology in the tourism ancillary industries. [ABSTRACT FROM AUTHOR]

As people continue to pay attention to environmental issues, the concept of green consumption has emerged. In order to study the effects of the guidance information on green consumption behavior, this paper chose two common situations in social life: "household electricity-saving" and "carton recycling," and designed an inter-group experiment of 2 (Message Framing: Gain framing/Loss framing) × 2 (Language Intensity: Assertive language/Nonassertive language) × 2 (Self-construction: Interdependent self-construal/Independent self-construal), based on the Self-construal Theory. It aimed to examine the influence of different message strategies on the green consumption behavior willingness of information receivers. It was found that for interdependent individuals, the gain framing message has more positive influence on the intention of green consumption behavior, while the loss framing can better promote independent individuals' willingness. Nonassertive message had a positive impact on the intention of green consumption behavior of both types of individuals. Besides, when the message is nonassertive, gaining framing and losing framing message has a more significant role in promoting the green consumption behavior willingness of interdependent individuals and independent individuals, respectively. [ABSTRACT FROM AUTHOR]

Based on emergy theory, this paper calculates the agricultural green GDP of China and its provincial units from 2003 to 2018. Following this, the spatial distribution characteristics and influencing factors of the economic growth of green agriculture in China are studied using the spatial analysis method. The results show that: (1) Compared with the traditional GDP derived from agriculture, the per capita green agriculture GDP growth in China is relatively slow, and the proportion of green agriculture GDP to the traditional GDP from agriculture is between 85 and 91%, which shows a downward trend. (2) The economic growth of China's green agriculture manifests significant spatial agglomeration, with gradually growing effects. (3) The per capita GDP of green agriculture has not broken the overall pattern of high economic growth in China's eastern regions and low growth in the western. According to the results, the major cause of this spatial pattern lay in the higher efficiency of agricultural production in the eastern, economically more developed areas, and the relatively less efficient mode of production in the western areas. (4) A region's level of economic development, technological innovation, infrastructure investment and openness were found to have a positive impact on the growth of green agriculture within it. In previous research, emergy methods have not been applied to study the economic sectors in China, the largest developing country in the world, especially in the agricultural sector. Only few studies report on the analysis of spatial characteristics and factors influencing the growth of green agriculture. The agricultural green GDP was calculated based on the emergy analysis method. The temporal and spatial characteristics, as well as the driving factors of green agriculture GDP, were analyzed under the full consideration of the spatial correlation, which contributes to the theoretical explanation of spatial agglomeration of economic factors in spatial economic theory. The conclusions provide a theoretical and practical basis for accurate evaluation of the green growth of China's agricultural economy, optimization of the spatial structure of the country's green agricultural economy and coordination of the development of green agriculture in different regions. [ABSTRACT FROM AUTHOR]

Green technology innovation (GTI) and environmental regulation (ER) hold the key to promoting the transformation of industrial structure. Based on the regional panel data of China, this is the first study to explore the impact of GTI on the optimization of industrial structure (OIS) and rationalization of industrial structure (RIS) under various ERs. The results suggest that the influence of GTI on OIS and RIS features both heterogeneous environmental regulation effects and regional heterogeneity. Furthermore, command-controlled environmental regulation (CER) has a significant inhibitory effect on OIS. The threshold effects of ERs on OIS and RIS turn out to be significantly different when the panel threshold models are introduced, which also shows heterogeneity. Specifically, there are double and single threshold effects of MER and public participation environmental regulation (PER) on OIS, respectively. In comparison, there are single and double threshold effects of GTI on RIS under CER and PER, respectively. The results indicate that OIS and RIS are significantly correlated with GTI and the type and intensity of ERs. Therefore, it is necessary to strengthen GTI to promote regional coordination and cooperation for green industrial transformation. [ABSTRACT FROM AUTHOR]

In today's world, businesses and organizations should behave appropriately for the environment in order to make a contribution to welfare benefits while also gaining business opportunities and economic development. Green practice's adoption could assist businesses to start saving mineral wealth, and power, avoid environmental damage and even result in the long development of businesses. This study examined the correlation between external environmental factors and green product innovation, as well as the impact of green product innovation on the environmental and financial performance of 400 manufacturing SMEs in Vietnam's primary industrial units. Customer pressure, government pressure, government support, and market changes all had a beneficial effect on green product innovation, according to the findings. Furthermore, this study found a strong positive relationship between green product innovation and environmental and financial performance. Based on the research findings of this research, SME administrators can effectively adapt their business strategies to attain greater financial results and a comparative position in the market while utilizing green initiatives to grow their businesses and preserve the natural environment in a sustainable manner. [ABSTRACT FROM AUTHOR]

Green technology is the solution to address the dichotomy between environmental conservation and economic growth. How to stimulate the expansion of green technology innovation output is an essential agenda highlighted by firms, governments, and environmental non-governmental organizations. This research investigates the impact of stock liquidity on green technology innovation and its mechanism, using the data of listed new energy green firms in China from 2007 to 2019. The empirical findings reveal that the enhancement of stock liquidity considerably supports the green technology innovation of new energy firms. Whereas expanding R&D investment and decreasing financial risk are two economic mechanisms that stock liquidity promotes green technology innovation of new energy firms. In addition, our study demonstrates that both government subsidies and analyst attention may strengthen the impact of stock liquidity in supporting the green innovation output of new energy enterprises. The conclusion of this article might give reference to green economic development and structural transformation of emerging economies. [ABSTRACT FROM AUTHOR]

The abnormity of climate change poses environmental concerns and indirectly promotes the development of low-carbon economic growth pattern. Climate change mitigation technology innovations contribute significantly to achieve environmental goals in China, and thus, technological cooperation has become a strategic choice for the Chinese provinces to achieve technological breakthroughs. Based on 3, 280, 808 patents, this study uses social network analysis (SNA) method and similarity measurement to discuss the evolution process and structural features of the spatial correlation network to analyze the patent data from 1985 to 2020. The process for the research is as follows. First, a form solution of the correlation problem to calculate the minimum Euclidean distance is available in the field of social network. Second, the European distance is used to measure the similarity between provinces, and then, SNA is used to construct the spatial correlation network. Finally, the similarity of growth trend of provincial patent applications in different years from a nonlinear perspective is described, so as to calculate the potential provincial linkage strength. The results demonstrate that low-carbon technology innovation in China takes the form of a network structure. The network exhibits significant characteristics of regional agglomeration, and several central provinces exert the role of mediation and transmission, such as Tianjin, Hubei, and Henan. The study contributes by illustrating the current situation of green technology innovation and provides a critical theoretical foundation for the government when formulating future low-carbon economy development policies. [ABSTRACT FROM AUTHOR]

This study constructs a Cournot model with multiple enterprises considering the environmental tax, emission reduction technology research and development (R&D), and technology sharing. First, the solution of R&D and sharing boundaries of emission reduction technology are presented. Next, the effects of technology R&D, technology sharing, and environmental tax rates are analyzed. We also reveal the quantitative boundaries of enterprises participating in technology-sharing. The study finds that enterprise decision-making on emission reduction technology R&D and sharing is affected by factors such as the environmental tax rate, R&D cost, and technology sharing fee. Technology R&D and sharing can increase enterprise profits but reduce consumer surplus. Appropriate environmental tax policies contribute to the improvement of social welfare. Technology R&D helps reduce environmental damage and technology sharing can also achieve this under the influence of various factors such as environmental tax. Environmental tax rates affect consumers, enterprises, and social welfare. Consequently, an optimal tax rate is introduced that maximizes social welfare. Excessive environmental tax rates inevitably damage environmental and social welfare. An optimal number of shared enterprises exist in an enterprise's competition process. [ABSTRACT FROM AUTHOR]

Carbon reduction in marine fisheries plays a role in realizing the "dual carbon" goal. In this study, we measured the marine fishery carbon emission efficiency in the eastern coastal provinces of China from 2008 to 2020. We analyzed the spatial–temporal variation characteristics of marine fishery carbon emission efficiency based on a violin plot and standard deviation ellipse. Additionally, we used ridge regression and fuzzy-set qualitative comparative analysis to study the influencing factors and improvement paths of marine fishery carbon emission efficiency. The results demonstrate that the overall marine fishery carbon emission efficiency in coastal provinces increased from 2008 to 2020. The violin plot evolves from a "double peak" to a "single peak" and the carbon emission efficiency transitions from a low-value range to a high-value range. There is room to improve the carbon emission efficiency of provinces to different degrees. Additionally, the area of standard deviation ellipse of marine fishery carbon emission efficiency fluctuated from 1.46 million km2 in 2008 to 1.45 million km2 in 2020, and the spatial distribution range showed a concentrated trend. The spatial distribution center of carbon emission efficiency mainly moved northward before 2014 and southward after 2014. Regarding the influencing factors, the industrial structure did not pass the significance level, and the employment structure exhibited a negative correlation with the marine fishery carbon emission efficiency with a ridge regression coefficient of − 0.217. The level of economic development, carbon sink capacity, and educational level of technical extension personnel exhibited a positive correlation with the carbon emission efficiency, with ridge regression coefficients 0.034, 0.049, and 0.028, respectively. Furthermore, there were different paths for the low-carbon and green development of marine fisheries in coastal provinces. The individual and combined effects of influencing factors varied according to coastal provinces. Based on the influencing factors, three paths were determined. This study provides relevant recommendations to improve carbon emission efficiency and sustainably develop marine fisheries in China. [ABSTRACT FROM AUTHOR]

Public demand for environmental protection and environmental governance has a profound impact on enterprises' innovation behavior. Based on the panel data of 30 provinces in China from 2001 to 2018, this study uses a unit root to co-integration approach and the Panel Data Vector Autoregression model to empirically test the two-way dynamic relationship among green technology innovation, public environmental demands, and government environmental governance. The results show that both public environmental demands and environmental governance stimulate enterprises' green technology innovation; the estimated coefficient of government environmental governance and public environmental demands is 0.6681 and 0.0337, respectively. The incentive effect of environmental governance was more significant than that of public demands. Public environmental demands and green technology innovation have a bidirectional link, while environmental governance and green technology innovation share a two-way causality; meanwhile, environmental governance and public environmental demands share a unidirectional causal link. This study uses Impulse Response Function and Variance Decomposition to validate the outcomes, which shows that environmental governance's positive effect is more direct, while the effect of public demand has a time-lag impact, and the relationship among the three main variables is stable after the tenth period. The largest contribution to green technology innovation is environmental governance, with an explanation degree of 22.01%, followed by institutional quality (13.30%), and then public environmental demands (4.8%). These conclusions are not only significant for China to deal with the relationship among the public, government, and enterprises in the process of environmental governance, but also a valuable reference for other countries. [ABSTRACT FROM AUTHOR]

Sustainable Development Goals (SDGs) are enforced by a set of instruments, among which environmental regulations, green innovation, and carbon taxes play a central part. This article aims to investigate the mitigation capacity of the above-mentioned elements using a sample of 15 European countries. This study takes CO2 and greenhouse gas emissions (GHG) into account to ensure the consistency and accuracy of the findings. Augmented Dickey–Fuller and CIPS unit root tests, Pesaran CD, Bias-corrected scaled LM are employed to check the cross-sectional dependence. The panel effect is tested using error correction-based modeling along with dynamic approaches, while the Granger causality technique employs country-related outcomes. The results show that innovation and environmental policies help in reducing emissions both in the long and the short run. In addition to this, carbon pricing mitigates emissions in the regions although its effect is more country-specific. We find evidence of both unidirectional and bidirectional causality among the variables. However, in a few cases, they are too a country-specific artifact. As a general conclusion, carbon pricing is an efficient short-run tool to achieve SDGs. At the same time, long-run sustainability relies on green innovation and environmental policy stringency in the region. [ABSTRACT FROM AUTHOR]

In this study, taking the field of new energy vehicles as an example, the green patent data have been obtained from the smart bud patent database, and 243 organizations have been selected as the research samples based on their technical convergence and lack of data of their patents. From the perspective of technology convergence, five factors, including its degree of convergence, influence, knowledge maturity, experience, and originality, have been selected, and the fuzzy-set qualitative comparative analysis technology has been employed for conducting a configuration analysis. It has been found that there are three high green technological innovation paths, namely, the 'high convergence-high cognitive legitimacy' type, the 'high convergence-high influence' type, and the 'high convergence-high quality' type. In addition, five low green technological innovation paths have been obtained, which can be divided into three types, including the 'low convergence-high impact' type, the 'high convergence-low experience' type, and the 'high convergence-low quality' type. Depending on the low green technological innovation paths, the steps of configuring the specific conditions of the included samples and matching them with the most suitable upgrade path should be performed in order to achieve a quick and efficient improvement in the green technology innovation level of an enterprise. [ABSTRACT FROM AUTHOR]

China's innovation development relies heavily on government and enterprises' large investments in R&D activities, but regional sustainable innovation efficiency (RSIE) remains low in most areas of China. The economic and social development in China is facing continuously strengthened constraints of energy and environment. Sustainable innovation is an efficient way to achieve green development of economy, energy and environment. Previous studies on innovation efficiency did not pay attention to the undesirable outputs and did not study the convergence of innovation efficiency. This research empirically evaluates the sustainable innovation efficiency on regional level based on a slack-based measurement (SBM) model considering energy consumption and environmental pollutions. Furthermore, this research analyses the convergence of regional sustainable innovation efficiency. Results show that sustainable innovation efficiency in central, western regions and the entire country is slowly increasing. Provinces with high levels of technological innovation and environmental protection, pollutant emissions reduction and energy consumption have higher sustainable innovation efficiency. In addition, obvious δ and absolute β convergence trends exist in sustainable innovation efficiency, indicating that the regional differences among the three regions are shrinking. Regions with backward technological innovation are catching up with advanced regions. Controlled variables have a significant influence on the β convergence, whereas the convergence factors in the eastern, central and western regions are different. [ABSTRACT FROM AUTHOR]

This study examines the sustainability and green banking performance of Indonesian banking sectors from their disclosures in sustainability reports covering a period of nine consecutive years. The findings elucidate that sustainability and green-banking disclosures are still dynamic year to year. Economic disclosures are the most widely disclosed information, while environmental disclosures are the lowest. Applying a content analysis method, this study uses the sustainability disclosure guidelines from the global reporting initiatives (GRI) and Measuring Green Banking Practices guidelines developed by Shaumya and Arulrajah (2016). Combining these two measurements provided a more comprehensive disclosure list as guidance. This study is important, as it will contribute to the literature on green banking, which is scarce in the extant literature. Given the lack of standardization in sustainability, this study develops an indicator database to advance research on sustainability measurement and reporting in relation to green banking. The managerial implications for banks implementing sustainability they require sustainability governance as a platform to evaluate and monitor the sustainable finance action plan and build a sustainability strategy. This will enable banks to manage not only economic, but also environmental, social, and governance (ESG) risk. [ABSTRACT FROM AUTHOR]

This research is one of the very few studies that seeks to examine the association between China's industrial development and its energy sustainability. It does so by discussing the impact of industrialization on energy security in the new era, during which the focuses of industrialization and energy security in China have changed. The former has shifted from quantity-based expansion to quality-based growth, while the latter has shifted from supply security to comprehensive security, including matching security. Since researchers have paid little attention to evaluations of industrialization and energy security from the perspective of the new era, this study aims to address this gap. An empirical study on the impact of industrialization on energy security is conducted, taking 30 provinces in China as research objects. The findings show that China's energy supply security and consumption security have improved but that its matching security has deteriorated, which will eventually lead to an overall deterioration in energy security. Industrialization, however, can improve levels of energy security, supply security, and consumption security. Moreover, green technology efficiency and the capital–labor ratio both can improve levels of energy security and supply security, the former can also improve the level of consumption security and the latter can also improve the level of matching security. In contrast, an increase in GDP per capita inhibits energy security, supply security, consumption security, and matching security. This study will be helpful for policymakers seeking to resolve the issue of energy sustainability in the context of industrialization in China's new era. [ABSTRACT FROM AUTHOR]

Environmental research and development (R&D) is an effective means to coordinate firms' sustainable development and environmental protection. This study investigates the impact of media coverage on environmental R&D with the Environmental Protection Law's exogenous shock in 2015 in China. The results show that both media coverage and the Environmental Protection Law significantly promote firms' environmental R&D. Moreover, the Environmental Protection Law strengthens the positive effect of media coverage on firms' environmental R&D, and the strengthening effect is more significant for firms with low internal control quality and in high-competition industry. Further researches suggest that environmental R&D fully mediates the relationship between media coverage and environmental technology innovation, while the Environment Protection Law has no significant effect on environmental technology innovation. The results demonstrate external supervision or regulations are conducive to environmental R&D, which conforms to Porter Hypothesis. This study has certain enlightening significance to firms' environmental R&D, environmental technology innovation, and sustainable development in developing economies. [ABSTRACT FROM AUTHOR]

Green innovation is the key to solve increasingly serious environmental problems. Previous studies mainly focus on the effects of environmental regulations (ERs) on local green innovation while little research has paid attention to the effects of ERs in neighborhood, and the impact mechanism remains unclear. Actually, the green innovation in a region may depend on the superposition effects of local and neighboring ERs. This study proposes a theoretical framework of local-neighborhood effects of ERs on green innovation, and empirically tests the effects and mechanisms based on an examination of 274 prefecture level cities of China, with different ERs and regions taken into consideration. The results show regional differences in the local-neighborhood effects of different ERs on green innovation and further identify the optimum regional ERs intensity. Moreover, it is also discovered that areas with high intensity of ERs will foster the regional transfer of industries and human capital, and further affect green innovation in neighboring areas. Both command and control regulation and market-based regulation restrain green innovation in neighborhood through industrial transfer with the peak at 400 and 600 km economic urban circles, respectively. And the human capital is found significantly negative in neighborhood effect of market-based regulation within the 600 km scope. This study fills a gap in the literature of local-neighborhood effects of different ERs on green innovation, which is an extending of Porter Hypothesis and will be of great significance for regionally coordinated green innovation promotion. [ABSTRACT FROM AUTHOR]

Over recent years, there was a substantial rise globally in the importance of the environmental agenda for SMEs. The customer becomes now conscious of their consumer choices' environmental consequences. This research has also identified obstacles to introducing green business activities in small- and medium-sized enterprises and increase sustainable development. The green innovation barriers refer to green products, processes, and management; therefore, it is important to minimize restrictions on clean technology implementation in small- and medium-sized enterprises. This study uses an integrated decision process to define primary barriers, sub-obstacles, and approaches to addressing those obstacles to Saudi Arabia's green innovation practices. Through extensive literature review and twelve experts' opinions, six key barriers, twenty-five sub-barriers, and plans to reduce obstacles were identified. Using the fuzzy analytical hierarchy process (FAHP), key barriers and sub-barriers are assessed. The methodology used to rank strategies is the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). Five Saudi Arabia SMEs are involved in the study of the proposed integrated decision model. The FAHP reports that the key obstacles to introducing green practices in SMEs are "political obstacles" The FTOPSIS, therefore suggesting that "developing research methods to deliver green innovation in small- and medium-sized enterprises" is the best approach to addressing barriers in green innovation adoption in SMEs. [ABSTRACT FROM AUTHOR]

The development of information and communication technologies (ICT) positively contributes to economic growth; however, their environmental implications cannot be ignored. Therefore, it is imperative to investigate the impact of ICT, energy consumption, economic growth, and financial development on the air quality in Pakistan. Drawing on the data set from 1976 to 2018, we employed Nonlinear Autoregressive Distributed Lag model. The results revealed that there is a substantial presence of asymmetric cointegration between ICT and CO2 emissions. The empirical results unfold that positive shocks in ICT negatively affect CO2 emissions, implying that an increase in ICT brings a decrease in CO2 emission; negative shocks in ICT publicized a negative association with CO2 emissions, inferring that a decrease in ICT will bring an upsurge in CO2 emissions. Moreover, on the dark side, energy consumption and financial development degrade the environmental quality by increasing the CO2 emissions in Pakistan. Additionally, the existence of the Environmental Kuznets Curve hypothesis in Pakistan was confirmed. Our key findings emphasize the importance of ICT development and several environmental implications in attaining the sustainable development goal. [ABSTRACT FROM AUTHOR]

Energy-saving performance of green technology for building projects has become the research hot spot. Using three reference simulation models of multi-story residential buildings designed located in Guangzhou city with hot summer and warm winter, this study simulated and identified critical energy-influencing factors in a traditional design. Green (renovation) technologies design were presented to enhance the conventional technique's energy-saving performances. DesignBuilder software, Pareto rule, and assessment index were used to analyze and identify the proper green technology for multi-story residential buildings in Guangzhou city. The results show that residential buildings' energy consumption in Guangzhou city mainly comes from five critical factors. The energy-saving performance from changing an envelope structure measures is the largest, reaching total sensitivities of 52.95% for 4-story frame structure, 54.06% for 3-story frame structure, and 60.59% for 2-story frame structure and reaching 16.14% of the total contribution for 4-story frame structure, 16.76% for 3-story frame structure, and 17.89% for 2-story frame structure, respectively. Based on this study, the managerial implications for decision-makers are presented. In a green energy-saving renovation technologies design of multi-story residential buildings in Guangzhou city with hot summer and warm winter, priority should be given to the passive technologies. Then enhance the energy-saving performance combined with appropriate active technologies. This case study research results guide decision-makers to improve multi-story residential buildings' energy-saving performance in similar regions with hot summer and warm winter. [ABSTRACT FROM AUTHOR]

Sustainability in business is a buzzword in the modern era which promptly became the target for small and medium firms to remain profitable in the long run. Small and medium fish firms can attain sustainability by successfully adopting blue technology by showing a new way of doing things. This study examined the influence of institutional activities in fisheries (IAF) on perception of blue technology adoption (BTA) and the sustainability of small and medium fish firms (SF). This study also examined how the components of 'Blue Technology' influence the sustainability of small- and medium-scale fisheries in Bangladesh. The data were collected from 101 small and medium fish farmers with self-administered questionnaire using direct field survey. The research found that BTA has strong and positive relationship with SF, while the IAF has weak but positive relationship with BTA and SF. It is also found that fish farmers intended to adopt blue technologies if they see profitability in it. Governmental policy and government's influence on the farmers were found less effective though farmers' expectation from government was high. [ABSTRACT FROM AUTHOR]