Environmental regulation, market demand, and green innovation: spatial perspective evidence from China

Information infrastructure and corporate green innovation quality incentive

We use a sample of Chinese firms from 2006 to 2020 to investigate the effect of information infrastructure on the quality of green innovation. Findings show that information infrastructure significantly improves corporate green innovation quality, and information infrastructure improves the pricing efficiency, improves valuation levels, accelerates the flow of innovation resources, and induces the growth effect of corporate innovation resources. Furthermore, we find that executive salary incentives, internal control quality, and market-oriented environmental regulation have adaptive incentives for information infrastructure to improve the quality of green innovation. Our findings provide justification to promote the construction of an information infrastructure and adopt market-oriented environmental regulations to improve corporate green innovation quality.

The impact of digital infrastructure on provincial green innovation efficiency-empirical evidence from China

In the epoch of the digital economy, technological innovation and energy conservation are significantly facilitated by digital infrastructure, leading to substantial improvements in green innovation efficiency at the provincial level. This study employed the feasible generalized least square (FGLS) method to examine the effects of digital infrastructure on the green innovation efficiency across 30 provinces in the Chinese mainland, utilizing panel data from 2011 to 2020. Additionally, this investigation delves into the intervening role of industrial structure upgrading and the amplifying effects of environmental regulation and human capital on the process. Findings indicate that, to begin with, digital infrastructure contributes to the meaningful enhancement of green innovation efficiency within provinces. Subsequently, the industrial structure upgrading partially mediates the impact of digital infrastructure on the efficiency of provincial green innovation. Lastly, both human capital and environmental regulations amplify the beneficial influence of digital infrastructure on the effectiveness of green innovation at the provincial level. This study provides valuable insights into the mechanisms through which digital infrastructure boosts green innovation efficiency, aiding policymakers in formulating appropriate policies to augment digital infrastructure, thereby promoting provincial green innovation efficiency.

The impacts of China's dual carbon policy on green innovation: Evidence from Chinese heavy-polluting enterprises

Encouraging enterprises to engage in green innovation is a potent strategy for reducing carbon emissions from production. As one of the largest carbon emitters, China has launched a series of policies to achieve carbon peaking and neutrality collectively referred to as China's dual carbon policy. However, existing research on the impact of China's dual carbon policy on green innovation by heavy-polluting enterprises is insufficient. To fill this gap, this study constructed a theoretical model to draw hypotheses about the impact of the dual carbon policy on enterprises' green innovation and verified this impact using a difference-in-differences model to conduct a quasi-natural experiment based on data from 2010 to 2022 from Chinese A-share-listed enterprises. The results indicate that the dual carbon policy had a significantly positive influence on green innovation in heavy-polluting enterprises. Moreover, environmental tax mediated this effect, while enterprises' total costs and subsidies positively moderated it. Additionally, the impact exhibited variations based on several key factors, including green patent type, carbon emissions, enterprise ownership structure, and Environmental, Social, and Governance ratings. This study supplements related research on the effects of environmental policy on green innovation and provides both theoretical and empirical support for adapting subsequent environmental policies.

Does green credit policy promote corporate green innovation? Evidence from China

Green innovation is an important strategy for companies to achieve sustainable development goals. In addition to helping companies create a green image and improve their competitive advantage, green innovation can reduce pollution and improve the ecological and social environment, with positive external effects. The green credit policy (GCP) is an addition to traditional environmental regulations. Taking the 2012 Green Credit Guidelines as a quasi-natural experiment, this study finds that GCP significantly reduces the quantity and quality of green innovation in green credit-restricted firms by discouraging enterprises' debt financing. Heterogeneity analysis showed that the negative impact was concentrated mainly on non-state-owned enterprises (non-SOEs). This study recommends diversifying financing channels to ease corporate debt financing constraints. The conclusions could enrich existing research on the economic consequences of environmental regulatory policies and provide a reference for the strategic planning of green innovation development in enterprises.

How does environmental regulation influence green technological innovation? Moderating effect of green finance

The main factor behind green economic development is green technology innovation (GTI). Environmental regulation and green finance (GF), as important ways to promote ecological civilization construction, run through the entire procedure of GTI. The purpose of this study is to investigate the influence of heterogeneous environmental regulation on GTI and the moderating effect of GF on GTI from both theoretical and empirical perspectives, to provide useful ideas for China's economic reform path selection and environmental governance system optimization. This paper uses information from 30 provinces between 2002 and 2019, and a bidirectional fixed model was constructed. The results show that: First, regulatory environmental regulation (ER₁), legal environmental regulation (ER₂), and economic environmental regulation (ER₃) all have greatly boosted the degree of GTI in each province. Second, GF acts as a highly effective moderator between heterogeneous environmental regulation and GTI. Finally, this article investigates how GF can act as a moderator in various circumstances. The beneficial moderating effect of it is found to be more pronounced in inland areas, areas with weak spending on research and development, and areas with high energy consumption. These research results provide valuable references for accelerating the green development process in China.

How does technological innovation affect carbon emission efficiency in the Yellow River Economic Belt: the moderating role of government support and marketization

The Yellow River Economic Belt (YREB) is a fundamental ecological protection barrier for China. Its carbon pollution issues are currently severe owing to the extensive energy consumption and unsatisfactory industrial constructions. In this context, this paper estimates carbon emission efficiency (CEE) based on the panel data from 56 cities in the YREB during the period 2006-2019 and analyzes its spatial distribution characteristics. Additionally, the spatial Durbin model (SDM) is utilized to examine the effect of technological innovation (TI) on CEE as a result of the moderating effects of government support (GS) and marketization (MA), respectively. The results indicated that (i) in the YREB, CEE exhibited significant spatial autocorrelation characteristics; (ii) TI negatively affected local CEE; (iii) the moderating effect of local GS on the relationship between TI and CEE in the local area was negative, but its spatial spillover effect was still not significant; (iv) the moderating effect of local MA on the relationship between TI and CEE in the local area was also negative, but positive in the surrounding areas. Based on the empirical analysis, a series of policy suggestions are proposed to improve the YREB's CEE.

The Heterogeneous Effects of Formal and Informal Environmental Regulation on Green Technology Innovation-An Empirical Study of 284 Cities in China

Promoting green technology innovation (GTI) through environmental regulation is a key measure in reducing the severity of environmental problems. However, the effects of formal environmental regulation (FER) and informal environmental regulation (IER) on GTI have not been clarified. Through theoretical analysis, this paper analyzes the effects of FER and IER on GTI based on OLS and GTWR models. The results show the following: (1) In all Chinese cities, both FER and IER have had a positive impact on GTI. The impact of FER has been much stronger than that of IER. They show a linkage effect, and their interaction (TER) has had a positive impact on GTI. (2) In terms of spatial heterogeneity, the impact of FER, IER, and TER on GTI has decreased across the east-west gradient and has been supplemented by a core-periphery structure. (3) In terms of urban heterogeneity, the impact of FER, IER, and TER has decreased with the size of the city. This study has the potential to strengthen the effect of environmental regulation on GTI. It can provide a decision-making reference for cities to coordinate FER and IER strategies, and provides evidence for adopting regionally differentiated environmental regulation strategies.

The Empirical Analysis of Environmental Regulation's Spatial Spillover Effects on Green Technology Innovation in China

Green technology innovation is one of the driving forces of industrial structure upgrading. This innovation is thought to be related to environmental regulation. The study uses panel data for 30 Chinese provinces and cities from 2009 to 2020 and presents a comprehensive research-based explanation of how environmental regulations impact green innovation. This study employs the spatial Durbin model to analyze the spillover effect of the region. The results show that the total impact of environmental regulations is 0.223%, of which the direct effect is 0.099%. This impact includes the effects of both formal and informal environmental regulation. It indicates that ecological regulations significantly enhance green technology innovation. Furthermore, the spatial spillover effect is significantly positive at the 1% level with a coefficient of 0.124. Such spillover effects represent a learning effect of regional environmental regulation. Based on the results, the study suggests a few policy measures based on the detailed outcomes.

Regional green innovation efficiency and dynamic evolution of Chinese industrial enterprises: a three-stage super-efficiency DEA method based on cooperative game

The level of development of industrial enterprises is related to a country's or region's overall competitiveness. It is critical to assess the green innovation efficiency of regional industrial enterprises scientifically and effectively in order to improve a country's overall green innovation capability. The green innovation system is divided into three sub-stages in this paper: technology development, economic transformation, and environmental protection. Based on the theory of innovation value chain, a three-stage super-efficiency DEA model of the cooperative game including shared inputs and undesirable outputs is constructed to calculate the overall efficiency, three sub-stages efficiency, and dynamic evolution of green innovation of industrial enterprises in China's provincial administrative regions and eight economic zones from 2015 to 2019 (divided by the time of ultimate output). The results indicate that (1) in terms of overall efficiency, the efficiency of green innovation is not high, and there are clear regional differences, as evidenced by the following states: the middle reaches of the Yangtze River economic zone > the eastern coastal economic zone > the southern coastal economic zone > the northern coastal economic zone > the northeastern economic zone > the northwestern economic zone > the middle reaches of the Yellow River economic zone, and the overall efficiency of the southwestern economic zone fluctuates around the average level of China; (2) from the standpoint of various stages, economic transformation stage efficiency > overall efficiency > technology development stage efficiency > environmental protection stage efficiency. The improvement of overall efficiency is largely dependent on the high efficiency of the economic transformation stage, but low efficiency in the environmental protection stage results in overall low efficiency; (3) from the perspective of the dynamic evolution trend, the overall efficiency and three sub-stages have been improved to varying degrees. However, due to the low efficiency of the environmental protection stage, there is still a long way to go to achieve the goal of innovation-driven development; (4) based on the classification analysis, it was determined that the green innovation efficiency of industrial enterprises in only a few regions belongs to the "three high innovation type," which must take targeted measures to improve the inefficient innovation process links.

China's logistics green competitiveness promotion path: a fuzzy-set qualitative comparative analysis approach

Increasingly serious environmental problems are forcing many industries to gradually turn to green development, and green competitiveness has become the vision of policymakers and industry practitioners. The impact of the development of the logistics industry on the environment cannot be ignored, but the promotion path of its green competitiveness has not been fully studied. Based on Porter's diamond model, this study uses fuzzy-set qualitative comparative analysis to explore the condition configuration of the logistics industry in 30 provincial regions in mainland China to enhance green competitiveness and effectively combine theory with practice. Factors considered include logistics technology innovation ability, logistics market demand, proportion of tertiary industry, management level of logistics enterprises, environmental regulation, and the internet. The results show that the green competitiveness of the logistics industry is influenced by many factors and cannot be sufficiently explained by a single factor. The findings point to three paths with equal authenticity to improve the green competitiveness of the logistics industry. By comparing the same types of high configuration and low configuration, this study finds that environmental regulation is an important external driving force for regions with low added value of output products, and for regions with certain geographical advantages and numerous logistics enterprises, in addition to the management level of logistics enterprises, support from the internet is also particularly important in improving the green competitiveness of logistics. These findings can provide a practical reference for the promotion of green competitiveness in the logistics industry in different regions.