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As the global environmental crisis evolves, China’s traditional industries have serious problems of high energy consumption, high emission and low energy efficiency. Developing green industries has become an important direction of China’s industrial transformation and upgrading. This paper selects scientific innovation industry as a typical representative of green industry and studies its financing environment assessment. In order to solve the financing dilemma faced by the science and technology innovation industry, this paper puts forward the evaluation method of the financing environment of science and technology innovation industry based on Bayesian network from the Angle of industry particularity. In this paper, Netica software is used to construct a Bayesian network model of the financing environment of the science and technology innovation industry, and the financing environment of the science and technology innovation industry in 2016-2020 is inferred according to the annual probability distribution. Then, the sensitivity analysis is carried out, and the hierarchical policy simulation is used to simulate the conditional probability of the initial node and the intermediate node respectively, so as to determine the impact of each node on the financing environment, and finally obtain the optimization path. The research results can be of great value for improving the financing environment of scientific innovation industry and promoting the development of green industry. [ABSTRACT FROM AUTHOR]

Scientific and technological innovation and the sustainable development of new urbanization are the key factors to promote national economic growth, and have a very important role in promoting regional development and international competitiveness. Based on the panel data of 16 cities in Chengdu-Chongqing dual-city economic circle from 2015 to 2022, this paper uses entropy weight method to determine the weight of each index and constructs a coupling coordination model to explore the sustainable development of scientific and technological innovation and new urbanization, the Panel Vector Autoregression (PVAR) model was used to further verify the interaction between the two. The empirical results show that the coupling coordination degree of scientific and technological innovation and new urbanization in Chengdu-Chongqing economic circle is increasing year by year. There is a balanced relationship between scientific and technological innovation and new urbanization, and the two are two-way Granger causality. Therefore, the conclusion puts forward the practical enlightenment of increasing investment in scientific and technological innovation, guiding enterprises to carry out scientific and technological innovation to feedback new urbanization and accelerate the construction of new urbanization, and actively integrating with urban development. [ABSTRACT FROM AUTHOR]

Fragile ecosystems that are affected by erosion from high pollution environmental loads pose a serious threat to human health and well-being. The evaluation of regional environmental loads has become a major issue for eco-environmental conservation and management. As a key region in central China, Hubei Province relies on ecosystems and the environment, which offer an important foundation for sustainable development and continuous improvements in social productivity. For this study, seven influencing factors were selected, and a correlation degree model was applied to assess Hubei Province's environmental loads during the period from 1995-2019. The results show that the overall environmental loads exhibit a fluctuating decreasing trend in response to economic growth and development actions. Moreover, as eco-environmental pollution problems have been addressed and improved over time, the ecosystem operating status has been gradually optimized. Finally, the paper concludes with a proposal of specific measures designed to mitigate Hubei Province's ecological loading from the perspectives of industrial structure, public awareness and technological innovation. [ABSTRACT FROM AUTHOR]

Reasonable environmental regulation is beneficial to promote green innovation and sustainable development, but the current lack of research of environmental regulation and collaborative innovation intention. Based on this, this paper constructs an evolutionary game model of green collaborative innovation between enterprises and financial institutions from the perspective of enterprise information disclosure and financing constraints, and explores the specific effects of different types of environmental regulation through case analysis and numerical simulation. Case studies show that the cooperation between enterprises and financial institutions is conducive to the realization of green innovation, but there is still no effective restraint mechanism. The numerical simulation results show that the combination of market-incentive and command-controlled environmental regulation can better stimulate the willingness of collaborative innovation, but the former has more significant incentive effect. Further, for enterprises, the government's cost subsidy or revenue incentive coefficient positively affects the cooperative innovation willingness of both parties. Similarly, the improvement of the cost subsidy or income incentive or even punishment coefficient by the government to financial institutions also has the same effect; increasing the cost subsidy coefficient is more significant, and enterprises are more sensitive to this. This paper provides reference for Chinese government to make reasonable environmental policy. [ABSTRACT FROM AUTHOR]

This paper addresses the longstanding debate about whether institutional pressures enhance or suppress corporate green innovation. Grounded in institutional and sustainable development theories, this paper empirically tested the impact of institutional pressures on corporate green innovation by applying a fixed effect negative binomial regression model to a research sample of listed Chinese manufacturing companies from 2012 to 2017. It was found that regulatory, normative, and mimetic pressures had significant positive effects on corporate green innovation, and that under external environmental protection pressure, companies became involved in green innovation activities to maintain their legitimacy and competitive advantage. The moderating effect of the pollution intensity and marketization variables, both of which affect the green innovation resource efficiency, were only found to play a role under regulatory and mimetic pressures. These research findings provide strategic guidance for green innovation development in manufacturing enterprises and provide the basis for future government environmental protection policies. [ABSTRACT FROM AUTHOR]

The digital transformation is of great significance to green and high-quality development of logistics industry (L-GHD). This paper analyzes the theoretical mechanism of digitalization affecting the L-GHD. In the meantime, taking the urban data of China's Yellow River Basin as an example, a fixed effect model is established to empirically test the impact of digitalization on the L-GHD. The results show that: (1) digitalization can significantly promote the L-GHD. (2) Digitalization indirectly promotes the L-GHD through technological innovation input and output, optimized allocation of labor and capital elements. (3) The heterogeneity test of city types shows that the impact of digitalization on the L-GHD is more significant in non-resource-based cities. Urban location heterogeneity test shows that digitalization has a more significant impact on L-GHD in the middle and lower reaches of the Yellow River Basin. Finally, it puts forward suggestions to accelerate the healthy development of digitalization and help the L-GHD in the Yellow River Basin of China. [ABSTRACT FROM AUTHOR]

Based on the natural discontinuity method, kernel density estimation, Dagum Gini coefficient, exploratory spatial data analysis and other methods, this paper explores the temporal-spatial characteristics of China's urban carbon emissions from 2000 to 2017, and investigate the influencing factors of China's urban carbon emissions by using the decomposition model of the spatial Dubin model. The main conclusions are as follows: (1) China's urban carbon emissions are steadily rising, but the growth rate of carbon emissions is slowing down gradually; The two-level differentiation of carbon emission distribution in the eastern and central regions are obvious, while that in the western and northeastern regions are not obvious. (2) There is a significant spatial autocorrelation of China's urban carbon emissions, and the local agglomeration features are obvious, which are mainly "high-high agglomeration" and "low-low agglomeration". (3) In terms of carbon emission factors, technological innovation, foreign investment, and government intervention can reduce carbon emissions in the eastern region; Government intervention has a mitigation effect on carbon emissions in the central region; Infrastructure construction and technological innovation can reduce carbon emissions in the western region; The industrial structure has a mitigation effect on carbon emissions in the northeastern region. The main research values are as follows: It is helpful to comprehensively understand the dynamic distribution, regional differences and spatial agglomeration characteristics of China's urban carbon emissions, and then investigate the driving factors of carbon emissions in different regions, so as to provide a scientific basis for each region to further implement the "double carbon" strategy, promote the coordinated emission reduction of cities, and jointly build a green development path. [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]

The oil and gas industry is an important basic energy industry in China, and its development is closely related to the improvement of comprehensive national power and quality of life. However, it is also a high energy consumption and high pollution industry, and the continuous input of various energy sources is often accompanied by damage to the surrounding environment. Therefore, it is important to evaluate the energy eco-efficiency of oil and gas enterprises for sustainable economic and social development. Based on both static and dynamic perspectives, this paper measures the energy eco-efficiency of 60 listed oil and gas resource-based companies from 2011-2019 using the SBM model and the Malmquist-Luenberger (ML) index model. The Tobit model is constructed to explore the influencing factors of energy eco-efficiency. The results show that the energy eco-efficiency of oil and gas resource-based enterprises shows a trend of rising and then falling, and there is much room for improvement. Among them, the energy eco-efficiency in the western region is basically consistent with the national average; technological progress has a greater impact on the energy eco-efficiency efficiency of oil and gas resource-based enterprises, while the role of technical efficiency is not significant; economic development, enterprise scale and technological innovation are positively and significantly related to energy eco-efficiency, however, energy consumption is negatively related to energy eco-efficiency. [ABSTRACT FROM AUTHOR]

R&D internationalization is an important way for enterprises in emerging economies to achieve technology catch-up and maintain sustainable development. The direct relationship between R&D internationalization and innovation performance has been widely explored, but the research on the influence of the mechanism between these two elements above is relatively less. This paper takes China's knowledge-intensive listed enterprises from 2009 to 2015 as the research object and uses Poisson fixed effect regression, hierarchical regression, and bootstrap methods to study the mechanism of knowledge base between enterprise R&D internationalization and innovation performance and the moderating effects of institutional distance on the mechanism effect. The results show that: (1) Enterprises' innovation performance can be promoted with the increase of R&D internationalization degree and diversity. (2) Knowledge Base (scope and entropy) plays a mechanism function between R&D internationalization and innovation performance. (3) By negatively moderating the relationship between the knowledge base and innovation performance, the institutional distance between home and host country negatively moderates the knowledge base's mechanism function. [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]

Priority needs to be given to the green technology of saving resources, saving energy and reducing pollution by enterprises in the new era where green development needs promotion because humans and nature are the community of life. In essence, green technology is the innovation-driven development of enterprises under the background of green development. In order to sort out the research trend of Chinese scholars on green technology, 206 articles published during the period of 1994 to 2017 and their citations mainly from the Chinese Social Sciences Citation Index database were studied by means of bibliometrics and mapping knowledge domains, which reveals the trend of a number of Chinese green technology research papers published, the evolution path of the hot research topics, the research frontier and the knowledge base, drawing inspiration from them. The main conclusions are as follows: 1) The number of Chinese scholars' research on green technology shows an N-type upward trend and will continue to rise in the future. 2) Green technology, technological innovation and environmental protection have long been research hotspots of China's green technology research. 3) The frontiers of green technology research in China can be divided into three stages for germination (1994 to 2010), rapid growth (2010 to 2014)and depth advancement (2015 to present. 4) The knowledge base of green technology research in China is mainly composed of efficiency, the relationship between the environment and economics, green technological innovation, environmental regulation and intellectual property. [ABSTRACT FROM AUTHOR]