Search

Green technology innovation plays an important role in achieving high-quality economic development in China. It is of great theoretical value and practical significance to study the effect of the Energy-consuming Right Trading Policy (ERTP) on green technology innovation. Based on the panel data of 279 cities in China from 2006 to 2020, this paper analyzes the effect of the ERTR on urban green technology innovation capacity (GTIC) by using the difference-in-differences (DID) model. The study shows that the ERTR can significantly improve urban GTIC and validates the “Weak Porter Hypothesis”. After a series of robustness tests, this conclusion still holds. Furthermore, the mechanism analysis shows that the ERTP can promote urban GTIC through industrial structure upgrading. In addition, the heterogeneity analysis indicates that the ERTR can significantly improve the GTIC of eastern cities and non-resource cities. This paper fills the gap of related studies and provides an important reference for improving the ERTP. [ABSTRACT FROM AUTHOR]

China is currently at a critical stage in transitioning from a large petrochemical country to a powerful one. To clarify the relationship between the development of the petrochemical industry and local ecological economy and explore the scientific development path for the industry, this paper analyzes the influence of petrochemical industry agglomeration on local ecological efficiency. By using panel data from 30 provincial units between 2012 and 2021, the study also investigates the mediating effect of green technology innovation on this relationship. Results show that the agglomeration of China's petrochemical industry positively affects local ecological efficiency. However, given some issues such as separation of production and innovation activities within the industry, a negative correlation exists between the agglomeration level of the petrochemical industry in China and the level of green technology innovation. Consequently, the agglomeration of China's petrochemical industry cannot enhance ecological efficiency through the mediating effect of green technology innovation level. The substantial resource consumption by green technology innovation has not translated into effective ecological economic benefits, which has increased the burden on ecological functions and resulted in a negative effect on ecological efficiency. The research conclusions and proposed measures hold significant implications for the scientific planning of the development of China's petrochemical industry, as well as for promoting regional economic growth and ecological construction. [ABSTRACT FROM AUTHOR]

The cultural diversity brought by migrants has attracted widespread interest in recent years. This paper investigates the relationship between migrant cultural diversity and regional innovation by constructing panel data of provincial migrant cultural diversity and combining them with invention applications data from China's State Intellectual Property Office. The empirical results show that the migrant cultural diversity, measured by migrant's hukou and dialect respectively, has a positive impact on regional innovation. The effect still holds after a series of robustness tests and addressing endogeneity issues. Furthermore, the further analysis implies that the effects of the migrant cultural diversity in workers aged from 30 to 50, engaged in an innovative occupation, working in high market‐competitiveness or inclusive provinces are more pronounced. Our study supplements the current research on the relationship between migrant cultural diversity and regional innovation. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2011 to 2019, this paper uses a two-stage DEA model to measure regional innovation efficiency, then non-parametric test is used to examine the impact of innovation network structure and government R&D investment on regional innovation efficiency. The results show that, at the provincial level, innovation efficiency of regional R&D is not necessarily in direct proportion to the innovation efficiency in the commercialization stage. Commercialization efficiency is not necessarily high in provinces with high technical R&D efficiency. At the national level, the innovation efficiency gap between our country's R&D and commercialization stage is small, indicating that the development of the national innovation efficiency is more and more balanced. Innovation network structure can promote the R&D efficiency, but has no significant effect on the commercialization efficiency. Government R&D investment helps to improve the R&D efficiency, but it is not conducive to the improvement of commercialization efficiency. The interaction between innovation network structure and government R&D investment will have compound effects on regional innovation efficiency; the region with underdeveloped innovation network structure can increase the government R&D investment to make it have a higher level of R&D. This paper provides insights into how to improve innovation efficiency in different social networks and policy environments. [ABSTRACT FROM AUTHOR]

Chinese governments at all levels have been using various policies to encourage innovation by firms. However, few studies considered the superimposed effects of multilevel innovation policies. Based on the panel data of 443 Chinese innovation–oriented firms from 2008 to 2011, this study investigates the complementarities between national and local science and technology programmes. The heterogeneous effects across stages of the innovation process are also considered. Results show that the national science and technology (S&T) programmes significantly increase firms' external research and development (R&D) expenditure but inhibit the commercialisation. In addition, the national and local S&T programmes complement each other in promoting external R&D expenditure while presenting substitutive in increasing patent outputs. This paper further finds that national and local programmes are more likely to be complementary at high subsidy intensity. This study contributes to the development of policy mix theory and has manifold implications for designing pertinent innovation policy systems [ABSTRACT FROM AUTHOR]

With the continuous promotion of China's innovation-driven development strategy, the role of technological innovation on economic development has become increasingly important. In this context, the support of R&D capital investment for technological innovation also becomes non-negligible. This leads to the question of whether the allocation of R&D capital is reasonable and whether there is room for further improvement. This paper is based on inter-provincial panel data from 2009 to 2020, which are classified based on China's National Bureau of Statistics for R&D funding sources in high-tech industries and incorporated into an overall discussion framework. Using STATA16 statistical software, the R&D innovation output of high-tech industries is inves-tigated by building a PVAR model with the perspective of funding sources of R&D input intensity. The study results show that (1) the increase in the intensity of enterprises' own capital investment has a positive impact on innovation output because it can generate a financial "reservoir" effect to support technological innovation. (2) the increase in the intensity of government capital invest-ment has a positive impact on innovation output because it can alleviate the loss of income of en-terprises due to "R&D spillover" and will send a positive signal to the market. (3) the foreign in-vestment intensity has a positive impact on the innovation output of enterprises due to the com-bined effect of "spillover effect" and "crowding out effect". (4) the increase of other capital in-vestment intensity also has a neutral effect on the increase of innovation output under the current financial market environment. Finally, based on the above findings, corresponding policy impli-cations are drawn. This study will help to improve the understanding of R&D capital allocation imbalance and R&D input and output issues in developing countries and provide a reference for policy makers. [ABSTRACT FROM AUTHOR]

• The relationship between industrial agglomeration and air pollution is explored. • The mediating effect of technological innovation on air pollution is explored. • The dynamic spatial panel Durbin model and mediation effect model is used. Based on the panel data of 277 prefecture-level cities in China, this paper empirically analyzes the relationship between industrial agglomeration and air pollution, and the mediating effect of technological innovation by using dynamic spatial panel Durbin model and mediation effect model. The results show that: (1) there is a typical N-shape curve relationship between industrial agglomeration and air pollution, that is, there is a moderate agglomeration interval in which industrial agglomeration can restrain air pollution. (2) Technological innovation is a mediator variable of industrial agglomeration affecting air pollution. Industrial agglomeration not only has a direct impact on air pollution, but also has an indirect impact on air pollution through technological innovation. The non-linear mediating effect is reflected in the typical U-shape curve relationship between technological innovation and air pollution. (3) Air pollution and technological innovation have strong time-space dependent effects. [ABSTRACT FROM AUTHOR]

Based on the instrumental variable method and a fixed-effects model, this paper uses panel data from 283 prefecture-level cities in China from 2004 to 2016 to analyse the impact of environmental regulation on the international competitiveness of China. The results suggest that (1) the strengthening of environmental regulation hinders the international competitiveness of Chinese cities; (2) technological innovation, resource allocation and government intervention all have partial mediating effects between the intensity of environmental regulation and the international competitiveness of Chinese cities. Nevertheless, if reasonable environmental policies can be formulated to enable the organic coordination of technological innovation, resource allocation and government intervention, it is possible to achieve a win-win situation between environmental regulation and the international competitiveness of Chinese cities. [ABSTRACT FROM AUTHOR]

Land is the spatial carrier and basic condition for guaranteeing regional development, and its regulation effects tend to affect the direction of long-term development and innovation potential of cities. This paper constructed an evaluation index system of land regulation in line with China' s national conditions from the perspective of the land system with Chinese characteristics. In addition, based on panel data for 280 prefecture-level cities in China from 2008 to 2019, this study used the spatial Durbin model and parallel multiple mediation model to empirically estimate the effects and mechanisms of land regulation and its spatial strategy interaction on city innovation. The results showed that: ① The impact of land regulation on city innovation was dynamic and multiplied. In terms of direct effects, land regulation and city innovation presented a typical U-shaped curve relationship with an inflection point of 4.833. Specifically, low-level land regulation significantly reduced city innovation, while high-level land regulation that exceeded the threshold could promote city innovation. ② Due to the strategic interactions of local governments, the impact of land regulation on city innovation had a significant spatial spillover effect. The relationship between adjacent urban land regulation and local city innovation followed a similar U-shaped curve to the direct effect. ③ In terms of indirect effects, the relationship between land regulation and local industrial structure showed an inverted U-shaped curve with an inflection point of 6.214. The spatial spillover effect of land regulation on industrial structures in neighboring cities had the same inverted U-shaped trend. During the study period, the level of land regulation in China had not reached the threshold, and the imbalance of the industrial structure inhibited city innovation. ④ There was an obvious Ushaped curve relationship between land regulation and local industrial agglomeration, and the inflection point value was 5.750. The spatial spillover effect was the same U-shaped trend. During the study period, industrial agglomeration promoted city innovation in China. ⑤ Land regulation had effects on urban innovation through industrial structure changes and industrial agglomeration. The relationship was affected by the multiple effects of mediating variables. Under the mediating effect, land regulation and city innovation showed a Ushaped direct relationship, and the inflection point value was 4.167. The promoting effect of land regulation on city innovation could be realized more quickly through the intermediary mechanism. In order to strengthen the supporting role of land regulation on city innovation, the scope and degree of land management and industrial guidance should be reasonably determined according to the land regulation threshold. At the same time, attention should be paid to spatial interaction and to the co-governance mode across the cities. [ABSTRACT FROM AUTHOR]

This paper uses panel data on renewable energy in China. Thus, the current analysis fills the gaps by examining the relationship between green technology innovation and renewable energy and CO 2 emissions from 1990 to 2018. The current study examines all concerns connected to panel data analysis with advanced panel estimators, such as cross-sectional dependence, stationarity, variation in slope parameters, and structural break. Our findings show that test results reveal that green technology innovation and renewable energy have a negative and considerable influence on CO2 emissions in the long run. Moreover, the short-run relationship of green technology innovation, on the other hand, is not significant—as evidenced by the findings of robustness tests such as AMG and CCEMG. Other empirical results revealed that GTI, REN and NEN significantly reduced local CO 2 emission, while POP and PI had no obvious reduction effects on CO 2 emissions. Different GTIs had the same spatial "symbiotic effects" on CO 2 emission reduction in the short term, showing positive spatial spillover reduction effects. Lastly, we conclude that the use of green technology innovation has positive externalities. Some policies to assist green innovation technologies and renewable energy resources have been suggested for the Chinese government to enact. • This paper uses panel data on renewable energy in China. • The current study examines all concerns connected to panel data analysis with advanced panel estimators. • The short-run relationship of green technology innovation is not significant. • We conclude that the use of green technology innovation has positive externalities. [ABSTRACT FROM AUTHOR]

As an important means of environmental regulation, environmental punishment lacks in empirical evidence on its impact on regional green technology innovation in China. Based on panel data of 30 provinces in China from 2010 to 2020, this paper systematically examines the relationship between environmental punishment and regional green technology innovation. It is found that environmental punishment has the quantity and quality enhancing effects on regional green technology innovation, and the quantity enhancing effect is greater than the quality enhancing effect. There is no significant effect difference between monetary punishment and non monetary punishment on green technology innovation effect, but the effect of punishment on institutions is obviously greater than that of punishment on individuals. And the performance of ecological provinces and provinces with better legal environment is also relatively better. Environmental punishment enhances the quantity and quality of green technology innovation through pressure, and improves the quality of green technology innovation through deterrence. Besides, in China, deterrence promotes regional green technology innovation together with the Central Government's environmental protection inspection, the national green manufacturing strategies and other policies concerned. [ABSTRACT FROM AUTHOR]

The development of the digital economy in China facilitates the transformation of old and new growth drivers. It can greatly promote the upgrading of technological innovation capacity, realize economies of scale and scope, and constantly promote the generation of new industries and new forms of business with the deep integration of digital economy and traditional industries, thereby promoting the high-quality development of China's economy. This paper uses inter-provincial panel data from 2013 to 2020 and a dynamic spatial Durbin model to quantify the impact of the digital economy on regional technological innovation capability (RTIC). The results show that: (1) the digital economy has positive spatial spillover effect and can boost the province's and neighboring provinces' regional technological innovation capability; (2) regional technological innovation capability has obvious spatial and temporal aggregation effects; (3) the impact of the digital economy on RTIC is mainly short-term effects, and there is regional heterogeneity, with the western region experiencing the highest effects and the eastern region experiencing less. Therefore, it is urgent to accelerate the development speed of the digital economy, grasp the law of dynamic economic development, identify the regional heterogeneity of the digital economy development, and deepen inter-regional digital technology cooperation to comprehensively drive the improvement of regional technological innovation capability. [ABSTRACT FROM AUTHOR]

The new energy industry helps to meet the challenges of energy exhaustion and environmental pollution. Based on the panel data from 2015 to 2021, this paper uses the BCC model and Tobit model to construct the empirical measurement of technology innovation efficiency of listed new energy enterprises with three-stage DEA technology and uses the convergence model to test the efficiency difference. The results show that: (1) Using the traditional BCC model, the technical innovation level of new energy enterprises is insufficient, and the overall comprehensive efficiency and pure technical efficiency are 0.220 and 0.302 respectively, which need to be improved. (2) The three-stage DEA model was used to control environmental factors and statistical errors, and the overall efficiency of technological innovation of new energy enterprises increased. The comprehensive efficiency and scale efficiency increased to 0.541 and 0.896 respectively. (3) The technological innovation efficiency of new energy enterprises presents temporal and spatial heterogeneity. The coefficient of variation of technological innovation efficiency of new energy enterprises ranged from 0.084 to 1.000 with significant differences. The technological innovation efficiency of new energy enterprises in eastern, central and western China shows a U-shaped fluctuation. [ABSTRACT FROM AUTHOR]

By adopting a set of panel data from thirty provinces in China from 2007 to 2017, this paper examines how regional innovation efficiency is influenced by different types of innovation policies from a specific long-range plan ('National Medium- and Long-Term Science and Technology Development Plan (2006–20)'). We incorporate public direct research and development (R&D) grants, R&D tax credits, and intellectual property rights (IPR) protection into our research. We also explore the heterogeneous influences of these factors at different stages in regional innovation development. The results indicate that public direct R&D grants have a significantly negative influence, especially in innovation-catching-up regions. Conversely, the R&D tax credit has a considerably positive impact on innovation-catching-up regions. IPR protection plays various roles according to different innovation development stages. Specifically, IPR protection has a positive impact on innovation-leading regions, while it negatively influences regional innovation efficiency in innovation-catching-up regions. [ABSTRACT FROM AUTHOR]

This paper aims at identifying the causal relationship between the reform of the cultural system and the upgrading of industrial structure, revealing the causal relationship between the reform of the cultural system and the upgrading of industrial structure, which is of great significance for promoting the reform of the cultural system and the upgrading of industrial structure. The impact of cultural administrative reform on industrial structure upgrading is empirically tested using panel data from 261 prefecture-level cities in China from 2001 to 2017. The double difference model and PSM-DID method are used. This includes conducting placebo tests and examining the robustness of empirical findings using other methods. The findings indicated that (1) the influence coefficient of the cultural administrative system reform on industrial structure upgrading is positive and passed the significance level test, indicating that the cultural administrative system reform significantly promoted industrial structure upgrading, and on average, it can improve the level of the urban industrial structure by 11.81 percent. (2) Theoretical analysis of the mechanism demonstrates that the innovation level acts as a link between cultural administrative system reform and industrial structure upgrading, implying that cultural administrative system reform promotes industrial structure upgrading by stimulating the innovation level of cultural enterprises. (3) The results of the heterogeneity analysis indicate that the influence of cultural administrative reform on industrial structure upgrading is highly regionally and economically differentiated. The higher the economic level of the local community, the more effective the promotion effect on industrial structure upgrading. The reform of the cultural administrative system has a greater impact on industrial structure upgrading in the eastern region than in the central and western regions. On the basis of the foregoing research findings, this paper makes some policy recommendations for releasing the overall system reform dividend based on the cultural system and promoting regional industrial structure upgrading. [ABSTRACT FROM AUTHOR]

Due to externalities and market failure, innovation activities are facing insufficient investment. Venture capital guidance funds (VCGFs) are an important policy implemented by China's government to guide private capital to participate in innovation and entrepreneurship activities, and it can have an important impact on scientific and technological innovation. Based on the panel data of 285 cities in China, this paper empirically analyzed the impact of VCGFs on innovation and its mechanism. VCGFs can significantly promote urban innovation and this role is sustained for three years following VCGF establishment. Further research shows that VCGFs do not have a direct impact on innovation but promote innovation by promoting the accumulation of innovative talent and capital, and the capital accumulation effect of VCGFs is the main path through which they promote urban innovation. Corruption is also a factor that restricts the effectiveness of an innovation policy. Thus, China's top‐down anticorruption campaigns can strengthen the ability of VCGFs to promote urban innovation. This paper opens the black box to show the mechanism through which VCGFs impact urban innovation, affirms the important role of the government in the regional innovation system, and clarifies the debate on government innovation policy. [ABSTRACT FROM AUTHOR]

As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pressure. Therefore, this paper takes the panel data of 30 provinces in China from 2005 to 2016 as the research sample, on the basis of using DEA Global-Malmquist index to measure the innovation efficiency of high-tech industries, it constructs three spatial weight matrices, by including spatial geography, spatial economic geography nesting and innovation, and then it uses Spatial Durbin Model to empirically analyze the effect of innovation efficiency of high-tech industry on CO2 emissions in China from spatial perspective. The results indicate: firstly, in China, CO2 emissions gradually increase from 2006 to 2012, however, some provinces have declined after 2012. And CO2 emissions present a descending trend from eastern coastal area to central and western region. Secondly, affected by "warning effect", CO2 emissions show a significant negative spatial spillover effect. Thirdly, the overall level of innovation efficiency of high-tech industries in China is not high, and its impact on CO2 emissions is not a simple linear relationship, but shows an "inverted N–shaped" curvilinear relation, and its decomposition index EC and TC also have similar characteristics. Obviously, the research in this paper provides a necessary theoretical support for China and some emerging developing countries to rational formulating and effective implementing the energy conservation and emission reduction policies. [ABSTRACT FROM AUTHOR]

Technological innovation and industrial structure upgrading have become two strategic initiatives to realize a green economic development in the new development model of China. Exploring the relationship between green economic efficiency and the coupling degree of technological innovation and industrial structure upgrading is essential to achieve the visionary goal of green economic development and socialist modernization. This paper measures the coupling degree of technological innovation and industrial structure upgrading, classifies the coupling types based on the panel data of 30 provinces in China from 2012-2019, and measures the green economic efficiency of 30 provinces in China using the super-efficient model (SBM), based on a spatial econometric model to study the relationship between green economic efficiency and the coupling degree of technological innovation and industrial structure upgrading. The research results show that there is a significant positive effect on green economic efficiency among regions; the coupling degree of technological innovation and industrial structure upgrading has a significant direct effect and a spatial spillover effect on green economic efficiency, the spatial spillover effect plays a major role. The heterogeneity analysis reveals that in the regions with higher development and coordination degrees of technological innovation and industrial structure upgrading, the coupling degree of technological innovation and industrial structure upgrading has a significant effect on the green economic efficiency of the region, and in the regions with lower development and coordination degrees of technological innovation and industrial structure upgrading, the coupling degree of technological innovation and industrial structure upgrading has a significant positive effect on the green economic efficiency of the region and neighboring areas. [ABSTRACT FROM AUTHOR]

Under the research background of ecological environment protection and "double carbon" goal, this paper applies panel data on the logistics industry from 2010 to 2019 in 12 provinces of China's new western land-sea corridor to statically measure the logistics industry's technical efficiency after taking into account the impact of different environmental elements and to analyze the dynamics trends of total factor productivity in the logistics sector. It is measured by using the three-stage SBM model and the Malmquist–Luenberger productivity index, which considers undesirable output. The findings indicate the following: (1) In the context of "double carbon," the overall technical efficiency of the logistics sector in the new western land-sea corridor seems to be relatively low; however, the average technical efficiency of the logistics sector in the southern portion of the new western land-sea corridor does seem to be higher than that of the northern part. (2) The logistics industry's technical efficiency varies greatly by region, with locations near central China having much higher technical efficiency than remote inland areas. (3) The fundamental reason for the improvement of technical efficiency in the logistics industry is pure technical efficiency, and the driving force behind the increase in total factor productivity is technological advancement. (4) Economic development, informatization development, industrial market scale, and import and export all have a substantial influence on the logistics industry's technical efficiency. Finally, depending on the findings, policy recommendations are offered. [ABSTRACT FROM AUTHOR]

Based on the perspective of the innovation value chain, sci-tech innovation is divided into two stages: R&D and achievement transformation. This paper uses panel data from 25 provinces in China as the sample. We utilize a two-way fixed effect model, spatial Dubin model, and panel threshold model to discuss the impact of two-stage innovation efficiency on the value of the green brand, the spatial effect of this impact, and the threshold role of intellectual property protection in the process. The results indicate that: (1) the two stages of innovation efficiency have a positive impact on the value of green brands, and the effect of the eastern region is significantly better than that of the central and western regions. (2) The spatial spillover effect of the two stages of regional innovation efficiency on the value of green brands is evident, especially in the eastern region. (3) The innovation value chain has a pronounced spillover effect. (4) The single threshold effect of intellectual property protection is significant. When the threshold is crossed, the positive impact of the two stages of innovation efficiency on the value of green brands is significantly enhanced. (5) The influence of economic development level, openness, market size, and marketization degree on the value of green brands shows remarkable regional differences. In conclusion, this study contributes to understanding green brands' growth and provides important implications for developing independent brands in various regions of China. [ABSTRACT FROM AUTHOR]

China still faces relatively serious energy poverty, and technological innovation is considered effective at alleviating this issue. This paper empirically investigates the impact of regional technological innovation on energy poverty based on panel data from 30 provinces in China from 2001 to 2020. This paper explores the effect of industrial structure distortion in the process of technological innovation on energy poverty. This paper conducts asymmetry analysis and investigates the heterogeneous impact of technological innovation on energy poverty in different areas. The research conclusions are as follows: (1) Regional technological innovation can effectively alleviate energy poverty. (2) Industrial structure distortion moderates the impact of technological innovation on energy poverty, and it weakens the effect of technological innovation in alleviating energy poverty, although the moderating effect is not significant in coal-producing regions. (3) The effect of technological innovation on alleviating energy poverty is more obvious in regions where energy poverty is prominent. (4) The role of technological innovation in alleviating energy poverty shows spatial heterogeneity, and this alleviation effect is more obvious in the western and non-coal producing regions. We also propose several policy implications for alleviating energy poverty. • Regional technological innovation can effectively alleviate energy poverty. • Industrial structure distortion moderates the impact of technological innovation on energy poverty. • Industrial structure distortion hinders the ability of technological innovation to alleviate energy poverty. • Technological innovation is more effective in alleviating energy poverty in regions where energy poverty is severe. • Technological innovation is more effective at alleviating energy poverty in the west and non-coal-producing regions. [ABSTRACT FROM AUTHOR]

As important carriers of local innovation activities, innovative industrial clusters are attracting increasing attention. Therefore, several countries have started promotion policies for innovative industrial clusters. However, there are few empirical studies on relevant policies. This paper investigates the impact of China's "innovative industrial cluster pilot" (IICP) policy on regional innovation. Taking the implementation of IICP policy as a quasi-natural experiment and using the panel data of 266 prefecture-level cities in China in 2008-2019, this paper provides strong evidence that IICP policy promotes regional innovation. The conclusion still holds after a battery of robustness checks. The heterogeneity test shows that the promoting effect of IICP policy on innovation is more significant in central and western region than in eastern region. Moreover, the lower the city administrative level and the lower the dependence on natural resource, the more prominent the innovation effect of IICP policy. Further, the mechanism test shows that the IICP policy can promote regional innovation indirectly by strengthening government support for innovation and attracting the agglomeration of science and technological talents, but the mediation effect of industrial structure has not been verified. [ABSTRACT FROM AUTHOR]

Market integration is an important tool for China's regionally coordinated economic development. At the same time, China is implementing an innovation-driven development strategy. Therefore, the way the market integration affects regional innovation is of great significance to analyze this problem. The panel data of 27 cities in the Yangtze River Delta region in China with the highest degree of economic integration from 2009 to 2018 are used to investigate the impact of market integration (MI) on regional innovation (RI). The main findings are as follows: the first-order lag term of RI is significantly positive, and RI has certain path dependence. In this regard, MI has a positive impact on RI and promotes RI. The estimated coefficient of MI is significantly positive and has a positive impact on RI and promotes RI. This provides a reference for promoting RI through MI. The contributions of the paper are threefold: (1) This paper examines the impact of MI on RI to provide policy implications for the coordinated development of innovation between regions. (2) The relative price method is adopted to measure the MI, which covers 16 kinds of commodities, covering a wider range than does the traditional method. (3) This paper uses the generalized method of moments (GMM) to test the effect of MI on RI for the first time. [ABSTRACT FROM AUTHOR]

The governments need beforehand to perceive the innovative relationship risk because they are one of the innovation subjects in those industry collaborative innovation alliances. However, it is difficult for innovation subjects to quantify the risks for industry collaborative innovation alliances due to the complexity, nonlinear, and dynamic condition. This paper firstly constructs an ordered logistic model, uses the following as independent variables: the collaborative degree, the ratio of science technology expenditure to GDP, the ratio of education expenditure to GDP, the ratio of finances to GDP, and uses the levels of risk as the dependent variable. Then, this paper uses the panel data of 30 provinces in China (Hainan is not included) from 2010 to 2018 to fit the model. Based on the fitting results, the research has gained the relationship risk prewarning model in industry collaborative innovation alliances by using the collaborative degree as an independent variable. The governments at all levels can use this relationship risk prewarning model to percept risk levels and reckon the corresponding probability which exists in industry collaborative innovation alliances. Furthermore, there are regional influences existing in the prewarning relationship risk levels in industry collaborative alliances. The east and middle areas have significant regional influence, but it does not exist among west areas and others. The governments at all levels may consider the regional differences. [ABSTRACT FROM AUTHOR]

Existing studies mainly focus on exploring the ‘inclusive effect’ of digital finance in the process of technological innovation, but generally ignore the ‘network effect’ of digital finance empowerment. Based on China’s inter-provincial panel data and threshold regression technology, this paper empirically examined the nonlinear empowerment mechanism of digital finance to promote the development of green innovation. The results of this study showed that: during the study period, digital finance significantly drove China ’s green innovation and the empowerment effect of the eastern and central regions was much higher than that of the western regions, indicating that the ‘inclusive effect’ of digital finance was significant; the empowerment effect of digital finance on green innovation had a positive dynamic evolution process from weak to strong, but this kind of ‘network effect’ characteristic mainly appeared in the eastern and western regions, while the central region showed a positive ‘U’-shape nonlinear pattern; and the nonlinear empowerment effect of digital finance on green innovation had a heterogeneous and strengthened adjustment mechanism. It had positive and increasing marginal efficiency characteristics under the adjustment of urbanization, fiscal transparency, and residents’ income level. It was manifested under the constraints of urban-rural income gap and economic growth targets. Under the influence of technology introduction, it presented a positive inverted a ‘U’-shaped characteristic. At present, only by continuously improving fiscal transparency, residents’ income, and urbanization level, continuously narrowing the urban-rural income gap, and keeping the economic growth target and technology introduction at a reasonable level, can we maximize the green innovation effect empowered by digital finance. This article has discovered the coexistence of the ‘inclusive effect’ and ‘network effect’ of digital finance empowerment in the process of green innovation. The relevant conclusions may provide local governments with a ‘Digital Finance Express’ during the 14th Five-Year Plan period to accelerate the development of green innovation. [ABSTRACT FROM AUTHOR]

⑴ Background——Green credit is the main part of China’s green finance system. The interaction between green credit and technology innovation is an important driving force for the transformation and upgrading of the forestry industry structure, and also an important means to realize the high-quality development of modern forestry. To discuss the specific effects of green credit and technology innovation on China’s forestry industry structure can provide a theoretical basis for the high-quality development of modern forestry. ⑵ Methods——This paper proposes the research hypotheses by analyzing the potential impact mechanism of green credit (hpc) and forestry technology innovation (tepscore) on the forestry industry structure (nfishc）. Based on the panel data of 28 provinces (municipalities and autonomous regions) from 2008 to 2019,the static FGLS fixed effects model of C-D production function is used to explore the interaction effects of green credit and technology innovation on the forestry industry structure. Meanwhile, in order to solve the possible endogeneity problem of the model and analyze the influence of interaction terms on the interrelation between green credit and technology innovation, the lagged terms of the explained variables are added and the dynamic system GMM model is used to estimate the interaction of green credit and technology innovation on the forestry industry structure. ⑶ Results——Firstly, green credit and forestry technology innovation both play a significant role in promoting the forestry industry structure. Among them, every 1% increase in the level of green credit will increase the forestry industry structure by 0. 126%,every 1% increase in the level of forestry technology innovation will increase the forestry industry structure by 0. 114%. Secondly, the interaction between green credit and forestry technology innovation can indeed enhance their effects of promoting the optimization of forestry industry structure, what’s more, green credit and forestry technology innovation are threshold variables to each other and both of them have a single threshold effect on forestry industry structure. In particular, when the proportion of high energy-consuming interest expenditure is less than 3. 914,there will be a certain scale effect and agglomeration effect. Every 1% increase in the level of forestry technology innovation, the forestry industry structure will significantly increase by 0. 249%. However, when the effect of interaction terms on green credit and forestry technology innovation is further examined, it is found that the development of green credit is not conducive to forestry technology innovation and forestry technology innovation also has a significant negative impact on green credit. Finally, the analysis of the effect of control variables on the forestry industry structure shows that in the process of forestry production, only increasing labor input (fen) has a little effect on the forestry industry, and the effect is not significant. Excessive financial intervention (finf) is not conducive to the transformation of forestry structure. Urbanization level (urban), opening degree (op) and forest coverage rate (fcr) may not only promote the consumption and trade of the forest products, but also adversely affect the forestry industry economy. ⑷ Conclusions and Discussions——First, constantly optimize the investment environment of green credit and give full play to the role of financial regulatory departments in guiding and encouraging banks to develop green credit. Banks should actively implement green credit policies, taking credit scale, structures and efficiency into accounts to lead the development of forestry green enterprises. Second, based on the development status of forestry enterprises, continue to increase the cultivation of the innovative subjects, improve the level of human capital in forestry, promote the upgrading of forestry industry structure. Third, increase the investment in forestry research and development and education of forestry talents, improve the conversion rate of forestry technology patents, and pay attention to the deep integration of forestry technology innovation and forestry green credit to realize the high-quality development of forestry economy. [ABSTRACT FROM AUTHOR]

With the growth and development of Construction 4.0, new technologies such as BIM, Big Data, and the Internet of Things are commonly used. These digital technologies play a critical role in fostering firm innovation and also have a major impact on firm performance. Based on panel data of 33 listed construction firms in China's construction industry from 2015 to 2020, this paper uses regression analysis and mediation analysis methods to empirically examine the relationship between Construction 4.0, technological innovation capabilities, and firm performance. The results demonstrate that Construction 4.0 has a significant positive promotional effect on the firm performance, while technological innovation capabilities mediate between Construction 4.0 and the firm performance. Based on these findings, it is suggested that construction firms should pay attention to the new technologies brought by Construction 4.0, increase investment in research and development, actively cultivate technological innovation capabilities, and build technological innovation networks, so as to promote digital transformation of construction firms. [ABSTRACT FROM AUTHOR]

As an influential economic entity, China's economic growth pattern is changing. The traditional way brought high-speed growth as well as caused environmental damage. The concept of environmental innovation, which combines the advantage of technology innovation and environmental consideration, has become a vital means to achieve sustainable development. Due to the double externality characteristic of environmental innovation, the government plays an important role in its development. Based on provincial panel data from 2008 to 2017, this paper first examines the distinct influences of various economic incentive instruments on environmental innovation. Then, the moderation role of marketization is explored. The results show that governments' direct financial expenditure on environmental protection has a positive impact on environmental innovation, while the effect of the environmental tax is not significant. In addition, the impact is negatively moderated by marketization. [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has delivered significant benefits, such as sustainable development and economic growth. We explore the relationship between digital finance and green total factor energy efficiency (GTFEE) for the first time, filling a gap in the existing literature. This paper uses dynamic panel models to explore digital finance's impact on GTFEE at the Chinese city-level panel data from 2011 to 2018. The results show that digital finance can significantly improve urban GTFEE, and the findings remain robust with various tests. Second, the mechanism analysis indicates that digital finance can improve GTFEE by promoting urban green technology innovation and industrial structure upgrading. Further study shows that digital finance has a better effect on the improvement of GTFEE in central and western cities, small cities and non-resource-based cities, but has no significant or small impact on GTFEE in eastern cities, large cities and resource-based cities, reflecting the inclusiveness of digital finance. [ABSTRACT FROM AUTHOR]

At present, the development of China's economy is inseparable from the promotion of innovation and entrepreneurship. However, there are huge differences in the level of entrepreneurship in different regions, so it is urgent to analyze the influencing factors of entrepreneurship. This paper uses panel data of 31 provinces in 2008–2017 to test the impact of urban unemployment rate, regional financial development level, market scale, agglomeration effect, entrepreneurial cost, scientific and technological innovation level, government support and other factors on entrepreneurial level. To solve the issue of factors influencing the enterprises, we utilised an effective way of fuzzy logic along with decision estimation strategy. The empirical results show that regional financial development level, agglomeration effect, technological innovation ability, government support and so on have a positive role in promoting the level of entrepreneurship, while urban unemployment rate has no significant effect on the level of entrepreneurship. Based on the empirical conclusion, the paper puts forward some policy suggestions. [ABSTRACT FROM AUTHOR]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

Universities are important parts of innovation ecosystems, and university technology transfer (UTT), which aims for the sustainable commercialization of sci-tech achievements, is closely related to other actors in the ecosystem. Based on the panel data of 31 provinces in mainland China, this paper empirically analyzes the spatiotemporal distribution characteristics of UTT levels from 2011 to 2019 and estimates the influencing factors using the spatial Durbin model (SDM) with an economic spatial weighting matrix from the perspective of innovation ecosystems. The results are presented as follows: (1) Although the overall level of UTT in China is low, it shows an upward trend in most provinces. In addition, the interprovincial gap is obvious, forming a ladder distribution of UTT levels increasing from west to east. (2) There is a significant spatial autocorrelation between UTT levels in the provinces. (3) Industry, economy, and informatization play significant roles in promoting UTT, while financial institutes and openness have significant inhibitory effects. The economy has a significant spatial spillover effect on UTT, while government, industry and informatization have a significant inhibitory effect on UTT in neighboring regions. (4) The direct and indirect effects of influencing factors in the Eastern Region and other regions show significant spatial heterogeneity. [ABSTRACT FROM AUTHOR]

Environmental regulation has obvious externality on technological innovation. How to protect the environment without exerting negative effects on technological innovation activities carried out by enterprises is an important realistic proposition in economic development. Taking the panel data of 21 cities in Guangdong Province from 2005 to 2018 as the research object, the paper empirically studies the impact of environmental regulation on technological innovation, as well as the moderating effect and threshold effect of the industrial structure upgrading on the relationship between them. The results show that there is an inverted U-shaped effect of environmental regulation on technological innovation, and a moderate intensity of environmental regulation is conducive to promoting the development of technological innovation. The industrial structure upgrading plays a significant negative moderating effect in the inverted U-shaped relationship on the whole, causing the curve of the inverted U-shaped relationship to move to the left. Furthermore, through the threshold regression model, we find that the moderating effect of industrial structure upgrading has significant nonlinear characteristics. The level of upgrading lower than the first threshold or higher than the second threshold is not conducive to the effect of environmental regulation on technological innovation. In the implementation process of environmental regulation, more attention should be paid to promoting the rationalization of industrial structure in combination with industrial policies. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2009 to 2017, the Super-SBM model with undesirable output is used to measure the green innovation efficiency (GIE) of Chinese industrial enterprises, and the Moran's I is used to analyze the spatial correlation. Then, spatialtemporal distribution characteristics are analyzed. Finally, the spatial panel model is used to examine the influencing factors of GIE. The results show that the GIE of Chinese industrial enterprises is at a low level, but it shows an upward trend in the time dimension. The changing trends of industrial enterprise's GIE in various regions are different. The GIE of industrial enterprises in eastern China is changing in a wave-like manner. The central and western are on an upward trend, which is consistent with the overall. Spatially, the GIE of industrial enterprises decreases from east to west. Most of the areas where the GIE of industrial enterprises is above the mid-high level are located in the southeast coast. The green innovation efficiency of industrial enterprises in various provinces has an obvious positive spatial correlation, but it has weakened in recent years. The level of economic development, environmental regulations, opening to the outside world, and technological innovation environment have a positive impact on the green innovation efficiency of industrial enterprises, while the level of urbanization has a significant negative impact on it. At last, this paper presents recommendations for the development of green innovation efficiency of Chinese industrial enterprises according to the findings. [ABSTRACT FROM AUTHOR]

Renewable energy is not only an efficient way to ensure energy independence and security but also supports the transition to a low carbon economy and society. The progress of renewable energy technological innovation is an important factor that influences the development of renewable energy. An in-depth analysis of the driving factors that influence this progress is crucial to China's energy transition. Based on Chinese provincial data over 2000–2015 and panel data models, this paper regards the CO 2 emissions as climate change and explores the response of renewable energy technological innovation to intensive CO 2 emissions. We also analyze the effect of the driving factors such as energy price and R&D investment on this innovation process. The main conclusions drawn are: (1) There are significant differences in technological innovation levels across China's provinces. (2) We observe that the intensive CO 2 emissions have promoted renewable energy technological innovation level, meaning that innovation process responds actively to climate changes. (3) R&D investment from government and enterprise both are conducive for promoting the innovation level. (4) Energy price has an insignificant effect on innovation in renewable energy technologies and we attribute this to the unreasonable energy price mechanism. This paper provides clear evidence for understanding the role of innovation on climate change. • The drivers of the renewable energy technological innovation are explored. • There are significant differences in technological innovation across provinces. • Renewable energy technological innovation responds actively to climate changes. • R&D investment is conducive for promoting the technological innovation levels. • The government should give full play to the role of the energy price mechanism. [ABSTRACT FROM AUTHOR]

International openness can affect regional innovation through more export opportunities, enhanced import competition and the spillover effects of foreign direct investment. Many studies have been conducted based on different countries for capturing the determinants of regional innovation, but very little literature is available with contradictory findings for the case of China. Based on 19 years' panel data of 31 Chinese provinces, this paper analyzes the impact of international openness on regional innovation measured by the number of patent grants. The positive effects of overall trade and a higher proportion of exports and imports to GDP are significant and robust across different model specifications, indicating that an increase in international openness can promote regional innovating activities in China. The causal relationship of all the variables depicted by path analysis matches the results of the system GMM model. Higher intellectual property protection provides each region with the opportunity to obtain economic benefits from innovation and then make a higher investment in R&D activities. Besides, the lag effect of regional innovation capability can also explain a large part of local innovating activities. In our subsample regressions, the positive effect of trade openness on innovation is majorly manifested in developed areas like eastern provinces. [ABSTRACT FROM AUTHOR]

China facing the challenge of coordinated development of "ecology, economy, and well-being". Scholars have conducted some research on the relationship between enviromental regulation and employment, but there is less research on the role of clean technology innovation in the employment effect of environmental regulation, which is the purpose of this paper. Using the panel data of 22 industrial sectors in China, the paper uses the number of clean technology patents to measure the level of clean technology innovation, and examines the moderating effect of clean technology innovation in the employment effect of environmental regulations. The results show that: (1) With the gradual improvement of environmental regulation, the impact of environmental regulation on employment presents the characteristics of inhibition first and then promotion. (2) Clean technology innovation has a moderating effect on the employment effect of environmental regulation. It should encourage the green upgrading of traditional technologies, support the development and optimization of private enterprises in various industries, so as to promote enterprises to effectively reduce pollution emissions and create jobs through green technology upgrading at the initial stage. [Display omitted] [ABSTRACT FROM AUTHOR]

As the core element of technological innovation, financial resources can play the role of financial support, risk sharing, service guidance, and other aspects, thereby enhancing the efficiency of sci‐tech innovation (STIE). Whether there is a complex nonlinear economic threshold effect of financial development (FD) on STIE in different regional context is worth further discussion. This paper selects the Yangtze River Economic Belt (YREB) of China as the research object, based on the panel data of 110 cities, uses the Hansen threshold model to test the nonlinear "economic threshold effect" of FD on STIE. The results show that under different development scenarios in different regions, FD has a nonlinear "economic threshold effect" on STIE. This study extends the research sample to the cities of river basin, and elucidating the importance of regional context to the nonlinear "economic threshold effect" of FD on STIE further proposes that the sole focus of promoting the quantity of technology innovation by taking advantage of FD do not guarantee a positive effect on the development of STIE. Instead, the diverse, multiple financial policy instruments and stimulating the driving force of FD should be adopted towards the improvement of STIE in a phased and context specific manner. [ABSTRACT FROM AUTHOR]

• The co-agglomeration accentuates haze pollution. • Co-agglomeration has obvious spatial effects on haze pollution. • The pollution effect of co-agglomeration is weakened with the improvement of the economic level. • Technological innovation has an inhibitory effect on the pollution effect of co-agglomeration. The issue of haze in the middle reaches of the Yangtze River urban agglomeration has significant implications for China. Concurrently, co-agglomeration and technological innovation are key factors influencing haze pollution. Using the panel data composed of PM2.5 concentration and other data from 27cities in the middle reaches of the Yangtze River urban agglomeration between 2010 and 2020, this paper empirically investigates the impact of co-agglomeration and technological innovation on haze pollution. From this rigorous analysis, several conclusions crystallize: (1)the co-agglomeration of productive services and manufacturing accentuates haze pollution, showcasing notable regional variances;(2)the haze pollution has a significant positive correlation with the co-agglomeration levels in local and neighboring regions;(3)the negative consequences of co-agglomeration on environments reduce as the agglomeration of productive services and economic development increases;(4)technological innovation significantly moderates the pollution effects of co-agglomeration. [ABSTRACT FROM AUTHOR]

Based on data of 31 provinces in China for the period 2007–2017, this paper establishes spatial models by means of a transcendental logarithmic production function and analyzes the impact of regional credit and technological innovation on regional economic growth. The Jenks natural breaks method, kernel density function, and Moran index are introduced for spatial statistical analysis. Spatial weight matrices are constructed from two aspects of geographical characteristics and innovative input characteristics. The empirical results show significant spatial heterogeneity and spatial autocorrelation in economic growth, regional credit, and technological innovation. Both regional credit and technological innovation are important impacts to economic growth, whereas the interaction of regional credit and technological innovation has a negative effect on provincial economic growth. Therefore, we argue that China should rationally allocate regional credit resources, strengthen technological innovation capabilities, and boost the integrated development of regional credit and technological innovation. It is a particularly important way to facilitate regional economic integration and sustainable development. [ABSTRACT FROM AUTHOR]

Given the regionally differentiated environmental regulatory means, this paper evaluates the contribution of firms' R&D investment to economic growth with interprovincial panel data on 30 provinces in China from 2009 to 2016, which is based on the time-varying threshold model. Additionally, the coupling coordination degree model (CCDM) is used to measure the effects of technological innovation through enterprise collaboration for R&D input and investment-focused environment regulations. We then explore the inter-regional technology transfer path with different cooperation effects in areas and find: (i) The economic performance of the R&D investments of regional enterprises shows a downward trend with the strengthening of cost-focused ER while an inverted 'U'-shaped relationship that first strengthens and then weakens is presented with the strengthening of investment-focused ER. (ii) The degree of coupling calculated by CCDM is generally low, and synergies are improving from the west to the east, from a geographic perspective. [ABSTRACT FROM AUTHOR]

Considering time lag and accumulation of inputs and outputs, this paper adopts the superefficiency data envelopment analysis (DEA) model to study the technological innovation efficiency of high patent-intensive industries using panel data from 2007 to 2017. Given the characteristics and the actual circumstances of the industries, the innovation process is divided into two stages, and an input-output indicator system is established. The results show that the overall innovation efficiency level of high patent-intensive industries in China is increasing. However, the R&D achievements in technology are not quickly applied or sufficiently transformed. [ABSTRACT FROM AUTHOR]

The innovation value chain is an effective tool for analysing innovation activities and reflects the process of value creation and increase in innovation activities. From the perspective of innovation value chains, we divided patent innovation activities into three stages: knowledge innovation stage, applied research stage and patent commercialization stage. The panel data from 64 universities directly managed by the Ministry of Education from 2009 to 2017 were used and several conclusions were drawn: 1) In the initial stage of knowledge innovation, the fundamental research fund plays a crucial promoting role, and knowledge innovation achievements are mainly published academic papers. 2) In the applied research stage, the knowledge innovation in the early stage and the fund investment in R&D activities have a significant positive effect on the patent output of universities, but the personnel investment has a negative effect. 3) In the final stage of patent commercialization, preliminary research results have a positive impact on patent commercialization, whose marginal effect depends on the industry-university-research relationship, external competition and reputation of the university. The evidence showed that there is a feedback channel between university patent commercialization and knowledge innovation, and new knowledge generated by the interaction with the outside world in the process of patent commercialization was transmitted to the subject of knowledge innovation through this channel, forming a virtuous dynamic cycle. By analysing the driving factors of the value chain of patent innovation in colleges and universities, we provided empirical evidence for the operation mechanism and policy formulation of college patents in China. [ABSTRACT FROM AUTHOR]

Science and technology innovation is the core power of economic development, but the influence mechanism effect of science and technology innovation and economic development is still a theoretical blind spot to be elucidated. The input of science and technology innovation factors leads to the multiplier effect of economic development through three levels of diffusion to realize high external economic benefits under low capital input. Through theoretical analysis and empirical research, this paper proves that: In terms of research samples of six coastal provinces and cities from 2000 to 2017, science and technology innovation factors have a strong multiplier effect on regional economic development; the input of new type of practical patent significantly improves the regional economic level in the current period and the lag phase effect is further improved; the input of R and D investment significantly improves the regional economic level in the current period, and the promotion effect is slightly decreased in the lag phase. At present, China's economic development is gradually moving towards marketzation. We should synchronously use ''visible hands'' to give policy incentives to regions with high capital stock for science and technology innovation and develop the multiplier effect of science and technology innovation in economic development through various paths. [ABSTRACT FROM AUTHOR]

Based on China's provincial panel data from 2011 to 2019, this paper examines the complex impact of new energy industry agglomeration on green innovation efficiency from the perspective of spatial mismatch of research and development (R&D) resources. The super slack-based measured directional distance function (super-SBM-DDF) is applied to measure the green innovation efficiency, while the least square dummy variable model (LSDV) is implemented to evaluate the mismatch of R&D resources in the new energy industry. Based on the generalized method of moment (GMM), the moderating effect model, and the dynamic threshold model are employed to investigate the threshold effect of new energy industry agglomeration on green innovation efficiency and the moderating effect of spatial mismatch of R&D resources. We come to the following findings. First, the agglomeration of China's new energy industry exhibits a "west-east-central" gradient distribution. In the meantime, there is a widespread insufficient mismatch of R&D resources in the majority of regions. Second, the agglomeration of the new energy industry can significantly boost the efficiency of green innovation. Moderate agglomeration can have a marginally enhancing effect, whereas excessive agglomeration will obscure the green innovation effect of new energy industry agglomeration. Third, the relationship between the new energy industry agglomeration and green innovation efficiency is negatively moderated by the mismatch of R&D resources, while the moderating effect is amplified by the mismatch of innovation financial resources. Fourth, there are two inflection points in the positive impact of new energy industry agglomeration on green innovation efficiency when the innovation resource mismatch is assigned as the threshold variable. [Display omitted] • The relationship among industry agglomeration, R&D resources mismatch and green innovation efficiency is investigated. • The mismatch of R&D resources is calculated by LSDV. The green innovation efficiency is measured by super-SBM-DDF. • The new energy industry presents a gradient distribution of "west-east-central" and there is a mismatch of R&D resources. • R&D resources mismatch hinders the positive effect of new energy industry agglomeration on green innovation efficiency. • Dynamic threshold panel model reveals the nonlinear relationship between agglomeration and green innovation efficiency. [ABSTRACT FROM AUTHOR]

The digital economy has demonstrated strong resilience and great potential, under the interwoven influence of the global pandemic and severe environmental concerns across the world. Therefore, there is a need to focus on the value of green economic growth in the digital economy. This paper constructs an evaluation index system and adopts the SEEA (System of Environmental and Economic Accounting) method to measure the digitalization level (Digi) and green economy growth level (GEG) of China. The internal mechanism and linear relationship between digitalization and green economy growth are examined based on the panel data from 2013 to 2019. Moreover, this study explores the spatial spillover effect. The major study findings are as follows: (1) Digitalization and green economy growth represent a steady growth trend, and the former as a whole significantly promotes the latter, with a marginal effect of 1.648. (2) The mechanism analysis indicates the intermediary effects' size of three crucial intermediaries: green technology innovation > advanced industrial structure > the rationalization of industrial structure. (3) Both the "local effect" (0.556; 0.574) and "neighboring effect" (1.382; 1.415) of digitalization on green economy growth are positive under the two weight matrices and display "simultaneous resonance" characteristics based on the spatial perspective. (4) There exists obvious regional spatial heterogeneity and resource endowment heterogeneity. Finally, this study put forward corresponding policy implications, such as construction of new digital infrastructures and guiding green-energy consumption. • The green economic growth (GEG) level is measured by the SEEA method. • The linear relationship shows digitalization (Digi) can significantly promote GEG. • The spatial effect of Digi on GEG shows "positive simultaneous resonance". • Three crucial intermedia's effects are compared. • The heterogeneous impact is explored from different dimensions. [ABSTRACT FROM AUTHOR]

The importance of dealing with the relationship between foreign direct investment (FDI) and green innovation for sustainable development is being highlighted. However, since FDI can have both positive and negative effects on sustainable development, coupled with regional differences and different development conditions, there is uncertainty about the relationship between FDI and green innovation. Based on the panel data of 30 provinces in China from 2007 to 2018, this paper uses the two-tier stochastic frontier model to decompose the positive and negative effects of FDI on green innovation in different time periods and provinces, and considers the role of regional conditions that lead to regional differences in the green innovation effects of FDI, in order to better provide precise research findings for analyzing the relationship between FDI and green innovation in different provinces in China. First, empirical research shows that the inhibition effect of FDI on green innovation efficiency is smaller than the promotion effect, which makes the combined effect not obviously positive. The average inhibition effect of FDI on green innovation efficiency is 0.0041 and the average promoting effect is 0.0047, which makes the combined effect averaged 0.0006. Second, there are regional differences in the driving effect of FDI on green technology innovation. The western region's FDI has a greater drive effect on the efficiency of green innovation than the central and eastern regions. Third, the promoting effect character of FDI on green innovation efficiency is a "U" type with 70% percentile of the environmental regulation intensity as the inflection point. Due to the imperfection of China's economic structure at this stage, China's relatively developed regions have not yet established the market and industrial structure advantages to fully release the green innovation effect of FDI. Based on the research conclusions, to better promote green innovation efficiency, it is necessary to overcome the disadvantages of the green innovation process dominated by the central government, cultivate and develop green innovation markets, adopt incentive initiatives for foreign enterprises with green technology spillover effects, implement policies to address regional differences, and strengthen the interaction mechanism between FDI and green technology innovation in home countries. • Analyze the bilateral effects of FDI on green innovation efficiency. • FDI not only promotes but also restrains the efficiency of green innovation. • The inhibition effect of FDI is smaller than the promotion effect. • The combined effect of western regions is greater than eastern regions in China. [ABSTRACT FROM AUTHOR]

Based on various quasi-natural experimental high-speed rail scenarios in China, this paper both selects the panel data of 285 cities from 2003 to 2018 and adopts the Multi-time Difference-in-Differences method to analyze the impact of high-speed rail on urban carbon emission efficiency. Following this, the possible transmission mechanisms are explored. The results show that high-speed rail can significantly improve urban carbon emission efficiency with the conclusion still valid after conducting a series of robustness tests. The heterogeneity results indicate that the promoting effects of high-speed rail on urban carbon emission efficiency are more significant in non-resource-based cities and large cities. Further analyses of the transmission mechanisms show that high-speed rail may improve urban carbon emission efficiency through technological innovation, structural optimization, a strengthening of environmental regulations and a weakening of market segmentation. • We analyze the impact of HR on urban carbon emission efficiency. • We use the NDDF of super efficiency and the meta-frontier method to estimate the CEE. • High-speed rail can significantly improve urban carbon emission efficiency. • Technological, structural, regulation and market effects are recognized as mechanisms. [ABSTRACT FROM AUTHOR]

With the deterioration of China's ecological environment, technological innovation (TI) has become an important method of green transformation and upgrading Chinese steel enterprises (CSEs) under the constraint of environmental regulation (ER). Based on environmental protection panel data of 86 CSEs from 2005 to 2014, this paper first analyzes the direct effects of heterogeneous environmental regulation (HER) on TI and then studies the indirect effects of HER on TI through factors such as enterprise size, human capital, enterprise profit margin and executive environmental awareness. Based on a high-dimensional fixed effects model, the results show that (1) command-control environmental regulation (CCER) and voluntary environmental regulation (VER) have direct and positive effects on the TI of CSEs, while market-incentive environmental regulation (MIER) does not; and (2) the indirect effect of human capital is positively regulated by CCER and VER and that of enterprise size is negatively regulated by MIER, while all of the types of HER regulate the negative indirect effect of profit margin and the positive indirect effect of executive environmental awareness. It is necessary that combined and unified policy tools be implemented in the iron and steel industry (ISI) nationwide to coordinate the effects of HER. • This paper analyzed the dual effect of HER on TI of 86 CSEs with a high-dimensional fixed effects model. • Only CCER had the direct and positive effect on TI, whileMIER did not. • CCER had the indirect effect on TI through human capital, enterprise profits, and executive environmental awareness. • MIER had the indirect effect on TI through enterprise size, enterprise profits, and executive environmental awareness. • The robustness test by SYS-GMM verified the above results. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth understanding of the mechanisms of green finance on green innovation, focusing on their spatial and non-linear relationships. Using panel data of 30 provinces of China during the period of 2009–2017, a green finance index is constructed, and the spatial Durbin model and panel threshold model are used. The results reveal that: (1) Green finance and green innovation had significant positive autocorrelation, and the development of green finance in provinces of central and western China were still in the lower-level range. (2) The coefficients of the direct effect and indirect effect of green finance on green innovation were significantly positive, which indicated that green finance was conducive to enhancing green innovation in local and adjacent provinces during the research period. (3) Double threshold effects of green finance on green innovation were observed, which demonstrated that the driving effect of green finance was decreased with the raising of intensity of environmental regulation. The implication of these results is that government should make full use of the radiation and trickle-down functions of green finance and green innovation to narrow regional gaps in sustainable development while maintaining a moderate intensity of environmental regulation. • A green finance index of 30 provinces of China during the period of 2009 to 2017 was constructed on the basis of green credit, green securities, green insurance, and green investment. • The heterogeneity of region and time for green finance were analyzed employing the spatial exploratory analysis, which manifested that the spatial evolution of green finance in China presents a gradient decreasing pattern from east to west. • The impact of green finance on green innovation was explored by the spatial Durbin model, which proved that the direct effect and the spatial spillover effect were significantly positive. • Moderate intensity of environmental regulation helps green finance promote green innovation and this value should not exceed a maximum of 0.935. [ABSTRACT FROM AUTHOR]