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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

• 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]

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]

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]

The pilot program of low-carbon cities is of great significance for China's overall economic and social development. The construction of low-carbon cities contributes to adjusting the industrial structure, optimizing the energy structure and accelerating institutional reforms. Using the panel data of 285 prefecture-level cities during 2006–2015, this paper takes the pilot program of low-carbon cities as a quasi-natural experiment to detect the impact of the pilot program on industrial structure upgrading and its possible mechanism. The results reveal that the construction of low-carbon cities displays a positive impact on industrial structure supererogation while it has little effect on industrial structure rationalization. Ventilation coefficient is regarded as an instrumental variable to address endogenous problems. The conclusions are still tenable after a series of robustness tests. Mechanism analysis shows that the pilot program can bolster industrial structure supererogation via technological innovation and the reduction of the proportion of high-carbon industries. The regional heterogeneity analysis indicates that the influence of the pilot program on the industrial structure supererogation in the central and western areas is more positive than that in the eastern area, whereas the impact of the pilot program on the industrial structure rationalization is not significant in the three areas. The heterogeneity analysis of environmental law enforcement indicates that the pilot program can more obviously bump up the industrial structure supererogation in cities with strong law enforcement intensity. The impact on the industrial structure rationalization is not evident in cities with weak law enforcement intensity, but the industrial structure rationalization is significantly improved in cities with strong law enforcement intensity. This paper provides insights for realizing the integrated development of low-carbon cities and industrial structure upgrading. • The objective is to optimize the program of low-carbon and facilitate the upgrading of industrial structure. • Industrial structure supererogation and rationalization are considered. • We analyzed the impact mechanism. • The construction of low-carbon cities displays a positive effect on industrial structure supererogation. • The construction of low-carbon cities has little effect on industrial structure rationalization. [ABSTRACT FROM AUTHOR]

[Display omitted] • China's air pollution mainly presents a spatial pattern of high-high agglomeration and low-low agglomeration. • New-type urbanization significantly reduces local air pollution. • Industrial structure, technological innovation and energy structure are important transmission mechanisms. • The impact of new-type urbanization on air pollution has regional heterogeneity. To alleviate the ecological and environmental problems caused by rapid urban development, China has formulated and implemented the new-type urbanization strategy. However, there is insufficient empirical research on the specific relationship between new-type urbanization and air pollution. Therefore, based on the panel data of 30 provinces in China from 2005 to 2018, this paper constructs a comprehensive evaluation index system of new-type urbanization using the five dimensions of population, economy, space, society, and green. The spatial Durbin model and the spatial mediating model are used to discuss the spatial effect, transmission mechanism, and regional heterogeneity of new-type urbanization on air pollution. The results show that China's air pollution mainly presents a spatial pattern of high-high agglomeration and low-low agglomeration, and there are spatial fluctuations. The construction of new-type urbanization significantly reduces local air pollution, and the industrial structure optimization, technological innovation, and energy structure adjustment are considered as important transmission mechanisms. However, under the fiscal decentralization and political tournament system in China, the policy implementation deviation may weaken the emission reduction effect of new-type urbanization, which is not conducive to regional environmental governance. From the sub-regional level, the impact of new-type urbanization on air pollution has regional heterogeneity. A robustness test confirms the reliability of our research conclusions. This study also proposes some policy suggestions that the government can utilize in grasping the policy focus of new-type urbanization construction to discover effective ways of controlling air pollution. [ABSTRACT FROM AUTHOR]

The growth effect of collaborative agglomeration of manufacturing and producer service industries is receiving increasing attention from scholars. However, few studies have explored whether and how collaborative agglomeration of manufacturing and producer service industries affects green innovation. To bridge this gap, using the methods of the system generalized method of moments, the moderating effect, and the threshold effect, and employing the panel data of 30 provinces of China for 2003–2017, this paper studies the effect of industrial collaborative agglomeration on green innovation and how this influence fluctuates when marketization is included. The main findings are as follows: (1) During the sample period, industrial collaborative agglomeration generally had a blocking effect on China's green innovation. A 1% increase in industrial collaborative agglomeration indicated a 0.461% decrease in green innovation efficiency. (2) Marketization can be an essential and efficient factor to correct the negative impact of industrial collaborative agglomeration through a moderating effect. (3) With the improvement of marketization, industrial collaborative agglomeration exhibits a U-shaped effect on green innovation, with the turning point occurring when the marketization index is 6.21. (4) As of 2017, 21 provinces have successfully exceeded the threshold of marketization, indicating that the current industrial collaborative agglomeration has been able to effectively improve China's green innovation efficiency. However, the other nine provinces still trail behind them in marketization reforms, with industrial collaborative agglomeration continuing to negatively affect green innovation. (5) This paper concludes with recommendations to improve green innovation through industrial collaborative agglomeration and market reform. Image 1 • Our research model links marketization, green innovation and industrial collaborative agglomeration. • We explore whether and how industrial collaborative agglomeration affects the green innovation. • Marketization moderates and promotes industrial collaborative agglomeration's influence on green innovation. • As marketization deepens, industrial collaborative agglomeration's effect on green innovation shows a U-shaped curve. [ABSTRACT FROM AUTHOR]

Environmental regulation not only has a direct impact on environmental pollution, but also has an indirect impact on air pollution. This paper collects the panel data of 253 prefecture-level cities in China between 2004 and 2016. First, we used the Two-Stage Least Squares (2SLS) method to empirically analyze the direct and indirect effects of environmental regulation on environmental pollution. Second, this paper uses the panel threshold regression model to explore the non-linear effects of environmental regulation on environmental pollution. The results of our analysis indicate: (1) environmental regulation can directly alleviate environmental pollution. Additionally, technology innovation and industrial structure adjustment due to environmental regulation are also conducive to improving China's environmental situation. The direct effects of environmental regulation are greater than the indirect effects; (2) the influence of environmental regulation on environmental pollution has a single threshold characteristic; (3) we also found that some control variables can significantly impact environmental pollution. The innovation of this article is mainly to explore the direct and indirect effects of environmental regulation on environmental pollution. • The effect of environmental regulation on environmental pollution is studied. • The Two-Stage Least Squares (2SLS) method is used in this paper. • The panel threshold regression model is used to explore the non-linear effects. [ABSTRACT FROM AUTHOR]

Although green growth has become the economic development strategy of many countries in the world, and studies have analyzed the influencing factors of green growth from multiple angles, there are few literatures devoted to the impact of fintech and green finance on green growth. From the perspective of fintech development, this paper tries to construct a comprehensive index to evaluate the green growth of regional economy based on the in-depth analysis of the influence mechanism of green finance on green growth. At the same time, China's provincial panel data from 2011 to 2018 are selected to test the impact of fintech innovation and green finance on green growth, and its mechanism. It turns out that fintech and green finance significantly promotes green economic growth. At the same time, the impact of fintech and green finance on green growth has obvious regional heterogeneity, that is, the impact in eastern China is significantly stronger than that in central and western China. Further research shows that fintech innovation mainly promotes green economic growth through green credit and green investment. Therefore, fintech innovation can promote green economic growth by improving the development level of green finance, which has great reference significance for most countries. [ABSTRACT FROM AUTHOR]

Governments often turn to subsidies to boost enterprises' innovation activities, which gives subsidized enterprises room for allocating the subsidies among different innovation activities. Taking insights from institutional logic theory, this paper proposes that enterprises exhibit different subsidy-allocation behaviors between nongreen and green innovations and that the positive effect of subsidies on nongreen innovation is greater than that on green innovation due to the double-spillover problem that is pertinent to green innovation. Further, this paper argues that innovation intensity varies from privately-owned enterprises to local and central state-owned enterprises and that the underlying reason for this phenomenon is that enterprises with different ownership structures behave with different institutional logics, face different environmental and innovation pressures, and hold different innovative resource and capability endowments. We test these hypotheses by using longitudinal data (2010–2015) on 175 publicly-traded firms in the pharmaceutical industry in China. Overall, the results support most of the hypotheses. • The effects of governmental subsidies on green and nongreen innovations were examined. • The moderating role of ownership types between innovation subsidies and green/nongreen innovation was examined. • Five-year panel data from 175 publicly traded Chinese pharmaceutical firms were used to test the hypotheses. [ABSTRACT FROM AUTHOR]

Conventional finance has many deficiencies in promoting green technology innovation (GTI) and energy-environmental performance (EEP). The emerging digital finance is filling the gaps left by conventional finance with the support of information technology. Using panel data from 2011 to 2017, the paper explores the impact of digital finance on energy-environmental performance in China. The results show that digital finance significantly improves China's energy-environmental performance, which remains robust after a series of tests. Green technology innovation is the transmission path through which digital finance affects energy-environmental performance. The impact mechanism test proves that digital finance affects pure technical efficiency rather than scale efficiency. Furthermore, we also find that digital finance has a greater stimulus effect on energy-environmental performance where credit and capital markets are more immature. Financial supervision and environmental regulation from the Chinese government can reinforce the role of digital finance in promoting energy-environmental performance. Our study suggests that China should accelerate digitization in the financial markets, particularly in pursuit of its energy-saving and emission-reduction effects. • Digital finance can improve energy-environmental performance significantly. • The green technology innovation is the primary mechanism for the improvement of energy-environmental performance. • Instrumental variable, Semiparametric, DID models are employed to exclude endogeneity. • Credit and capital markets, financial and environmental supervision can reinforce the role of digital finance. [ABSTRACT FROM AUTHOR]

To achieve sustainable economic development, many developing countries have continuously tightened their environmental regulations; for example, the Chinese government revised some policies to protect the environment, such as the Environmental Protection Law, and levied environmental taxes. Will these regulatory tools affect the growth of the industrial economy? What are the differences in the influence of various types of environmental regulations? Based on city-level panel data from China, this paper applied a difference-in-difference (DID) model and a bootstrap panel Granger causality test to investigate the relationship between two types of environmental regulations (command-and-control environmental regulation and market-Based incentive environmental regulation) and industrial growth. The results show that (1) Command-and-control environmental regulation (CAC) has a significant inhibitory effect on industrial growth. (2) In most regions, there is no significant Granger causality between market-based incentive environmental regulation (MBI) and industrial growth. (3) Compared with command-and-control environmental regulation, market-based incentive environmental regulation allows more flexibility for enterprises, which is more beneficial for technological innovation. Meanwhile, market-based incentive environmental regulation does little to suppress industrial growth. • Environmental regulation are subdivided into the MBI(Market-Based Incentive) and the CAC(Command and Control). • We reflect the influence of the CAC environmental regulation on overall industrial performance to the industrial growth. • It investigates the relationship between the two types of environmental regulations and industrial growth respectively. [ABSTRACT FROM AUTHOR]

This paper utilizes SBM-undesirable model and Malmquist index to examine the urban eco-efficiency in China and analyzes the regional heterogeneity. Through the panel data of 273 prefecture-level cities during 2007–2017 in China, the spatial Durbin model is used to examine the influencing factors of urban eco-efficiency associated with technological innovations. The results show that the average values of urban eco-efficiency of the East, Central, and West regions are 0.93, 0.88, and 0.90, respectively. The Moran's I of eco-efficiency is around 0.8, which shows a strong spatial heterogeneity. It is found that higher innovative ability can increase urban eco-efficiency. Education investment and innovation talents have a U-shape relationship with urban eco-efficiency, while capital investment and innovation performance have an inverted U-shape relationship with it. This research outlines the relationship between technological innovations and urban eco-efficiency, offering policy implications for China's eco-construction and sustainable urban development. • Exploring the trend of eco-efficiency of different urban types in China. • Significant spatial autocorrelation and heterogeneity of eco-efficiency are found. • Spatial Durbin model is used to analyze how innovations affect urban eco-efficiency. • The drivers of eco-efficiency in terms of technological innovation are obtained. [ABSTRACT FROM AUTHOR]

Environmental pollution and income inequality have become two salient issues in China. To achieve a green economic transformation, China urgently needs to develop renewable energy technologies to reduce carbon dioxide (CO 2) emissions. However, the relationship among income inequality, renewable energy technological innovation (RETI) and CO 2 emissions has not received sufficient attention in the current literature. Based on Chinese provincial panel data from 2000 to 2015, this paper adopts a panel fixed effect regression model and a panel threshold model to perform an analysis on the nonlinear relationship among these factors. The results show that (1) RETI is conducive to reducing per capita CO 2 emissions (PCE). However, with an increase in income inequality, the abatement effect of RETI on per capita CO 2 emissions will be hindered, and RETI will even positively contribute to PCE. (2) The panel threshold model shows that the impact of RETI on PCE has a significant single-threshold effect with regard to income inequality. When income inequality is lower than the threshold value, the impact of RETI on PCE is not significant. However, above the threshold value, that is, within the interval of higher income inequality, an increase in RETI will positively contribute to PCE. Finally, from the perspectives of income inequality and RETI , relevant policy implications are put forward for achieving the transformation of a low-carbon economy. • The carbon abatement effect of renewable energy technological innovation (RETI) in China is investigated. • A significant single threshold effect regarding income inequality is found. • The RETI will increase carbon emissions in high income inequality interval. • Measures to alleviate income inequality can help to further reduce CO 2 emissions. [ABSTRACT FROM AUTHOR]

Liu, W.; Ye, B., and Liu, Y., 2020. Marine finance and marine science–tech innovation: An industrial panel data-based analysis. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 276–280. Coconut Creek (Florida), ISSN 0749-0208. To resolve the weakness in the marine economy, China has set up the strategy of revitalizing the ocean through science and technology. The experience of developed coastal countries and regions shows that marine finance is an important pillar for marine science and technology innovation and industrial development. This paper discusses how marine finance influences marine science and technology innovation. It makes up for the shortage of previous quantitative research, especially the shortage of marine finance research in subdivided industries. This study takes on the analysis of the quantitative impact of marine finance on marine scientific and technology innovation by gathering data from marine scientific research institutions involved in 13 industries from 2006 to 2016. By using the panel data, this research supports the important role of marine finance in science and technology innovation in the marine economy. [ABSTRACT FROM AUTHOR]

How to rely on market mechanism for achieving industrial sustainable development is an important issue both to current scholars and policymakers. Technological innovation is regarded as a mediator to construct a driving mechanism that flexible environmental policy affects sustainable development from the "narrow" perspective of Porter's hypothesis. Meanwhile, environment regulatory enforcement is introduced as a moderator to explore the institutional scenario that drives sustainable development of China's industry. Then we have adopted industrial panel data of 30 provinces in 2006–2015 and employed the sys-GMM method for empirical test. The findings show that: (1) flexible environmental policy can significantly facilitate industrial sustainable development. (2) Flexible environmental policy has a significantly positive impact on technological innovation. Meanwhile, technological innovation is significantly and positively related to industrial sustainable development, and technological innovation partially mediates the relationship between flexible environmental policy and industrial sustainable development. (3) Environment regulatory enforcement positively moderates the relationship between flexible environmental policy and technological innovation. However, it has a potentially positive but not significant moderating impact on the relationship between technological innovation and industrial sustainable development, indicating that there is still an "implementation gap". (4) From a regional point of view, technological innovation has partly mediating effects between flexible environmental policy and industrial sustainable development in the eastern and western regions, and environmental regulatory enforcement can positively moderate the role of flexible environmental policy in promoting technological innovation in the eastern region. Finally, this paper puts forward the policy implications. • Flexible environmental policy can significantly spur industrial sustainable development. • Technological innovation can significantly spur industrial sustainable development. • Technological innovation partly mediates the relationship between flexible environmental policy and industrial sustainable development. • Environment regulatory enforcement plays a positive moderating role between flexible environmental policy and technological innovation. [ABSTRACT FROM AUTHOR]

Green technology innovation is the main driving force for sustainable development of China's strategic emerging industries. Improving the efficiency of green technology innovation is an effective way to achieve this developmental goal. The correct approach to measuring the efficiency of green technology innovation is a hot issue. Based on the panel data of China's 21 subdivided industries of strategic emerging industries over the period from 2004 to 2015, this paper applies the Malmquist index and data envelopment analysis to evaluate the efficiency of green technology innovation in strategic emerging industries. The empirical results show that changes in trends of technology innovation efficiency of strategic emerging industries are increasing, due mainly to technological progress and promotion of technology efficiency. Promotion of technology efficiency results from the joint action of pure technology efficiency increasing (0.1%) and scale efficiency increasing (0.2%). The change index of green technology innovation efficiency varies greatly in different industries, being highest (1.379) in communications switching equipment manufacturers and lowest (0.775) among office equipment manufacturers. There are three obvious troughs in the change index of green technology innovation efficiency over the period from 2004 to 2015. These troughs are declines of 19.5% in 2005, 16% in 2009, and 45.4% in 2012. • Construct the panel data by division of independent and imitative innovation input. • Establish Malmquist-DEA index to evaluate green technology innovation efficiency. • Analyze the key factors influencing green technology innovation efficiency empirically. [ABSTRACT FROM AUTHOR]