Sustainable Financing Efficiency and Environmental Value in China’s Energy Conservation and Environmental Protection Industry under the Double Carbon Target

Are spatial imbalances in industrial structural change widening the common wealth gap?

The evolution of China's industrial structure from 2010 to 2021 is assessed based on the rationalization and sophistication of its industries. The Theil index quantifies spatial variability, while the Quadratic Assignment Procedure (QAP) investigates if changes in industrial structure imbalance will increase wealth disparity. The study's findings indicate a noticeable spatial imbalance in industrial structure change. The overall level of common wealth is low but steadily increasing, following a stepped-down structure of "east-center-west." Additionally, the north and south regions exhibit a pattern of "high in the north and low in the south." There is a pattern of higher values in the north and lower values in the south. In terms of common wealth and its dimensions, there is a ladder-like pattern with high values at the core decreasing towards the west. Between 2010 and 2021, the common wealth development shifted from a lower level to a higher one. Beijing, Jiangsu, and Shanghai constantly ranked in the top echelon, while Guangxi remained in the fifth echelon. The speed and difficulty of transitioning between echelons vary. Moving from the fourth echelon to the third echelon takes longer, while transitioning from the third echelon to higher echelons presents tougher challenges. Spatial imbalances in industrial structure changes widen the gap in common wealth. In particular, the impact of the gap in the advanced industrial structure on the common wealth gap is significantly higher than that of the gap in industrial rationalization. Reducing disparities in advanced industrial structure is more effective in reducing the overall wealth gap.

Incentive mechanism of multiple green innovation behaviors of equipment manufacturing enterprises: A managers, green coordination groups and employees perspective

Employees play a pivotal role in the implementing of green development strategies and the attainment of dual-carbon objectives within manufacturing enterprises. Effective motivation of employees, fostering consensus on environmental protection, increased engagement in environmental initiatives, and the cultivation of employee cohesion are all vital for fostering green development within these enterprises. This paper seeks to elucidate the roles of general managers, green coordination groups (GCG), and employees in actualizing green behaviors. Furthermore, it advocates for a double incentive model to be employed in the implementing of green strategies within manufacturing enterprises. The research reveals that multiple factors, including incentive intensity, green capability, effort cost, risk aversion, and green variance, significantly influence the formulation of incentive contracts for green behaviors. The motivation level of the general manager directly impacts the efforts of the GCG, the organization's green climate, the manager's individual efforts, and indirectly influences the motivation and efforts of employees towards green behaviors. Notably, the influence of the organization's green climate on employees surpasses than on the manager, underscoring the imperative for collaboration efforts between the general manager and GCG to instill green behaviors among employees. Hence, it is imperative for the general manager and GCG to collaborate not only on critical aspects of green strategy implementation but also in fostering green behaviors among employees. This collaboration will facilitate the development of a multi-layer incentive mechanism aimed at promoting and facilitating the adoption of green behaviors among employees, thus contributing to the advancement of theory regarding employees' green behaviors and offering practical guidance for effectively realizing dual-carbon targets and achieving high-quality development within enterprises.

Green credit policy and corporate excess cash holdings

Green credit is changing industrial structure and corporate behavior, but little attention has been paid to the relationship between green credit and corporate cash management behavior. Based on the typical fact that the allocation of traditional bank credit funds is biased towards heavily polluting industries and the exogenous impact event of green credit policy, this paper takes A-share listed companies in China's capital market from 2008 to 2015 as samples, and uses the DID model to investigate the impact of green credit policy on excess cash holdings of heavily polluting enterprises. The findings indicate that the green credit policy has reduced the excessive cash holdings of heavily polluting enterprises, suggesting that it can correct the issue and align their cash holdings with the requirements of normal production and operations. The mechanism test demonstrates that the green credit policy can alleviate agency conflicts and influence enterprise cash holdings. Moreover, a cross-sectional investigation reveals that the inhibitory effect of the green credit policy on cash holdings is more pronounced in large-scale and state-owned enterprises compared to small-scale and non-state-owned enterprises. Finally, an analysis of the economic consequences reveals that the green credit policy indirectly enhances corporate value by reducing excessive cash holdings. Based on this, banks and financial institutions continue to treat the credit granting of heavily polluting enterprises cautiously, optimize the structure of green financial products, fully consider the different types and nature of customers, and develop differentiated lending conditions and diversified evaluation mechanisms. This paper has enriched the research on the economic consequences of green credit and the influencing factors of corporate cash holdings, and provided policy enlightenment for regulators and listed companies to correctly understand and make full use of green credit policies to keep corporate cash stable through the crisis.

Threshold effect of technological innovation on carbon emission intensity based on multi-source heterogeneous data

It is of much importance to clarify the impact of technological innovation on carbon emission intensity for the low-carbon transformation of China's economy. This study, based on the panel data of 30 Chinese provinces and municipalities from 2010 to 2020, measures and analyzes the carbon emission intensity and the level of technological innovation, establishing a spatial econometric model to study the spatial spillover effect and a panel threshold model to analyze the nonlinear influence of technological innovation level on carbon emission intensity. The findings are as follows: First, the overall carbon emission intensity in China shows a decreasing trend from 2010 to 2020, with the average dropping from 3.09 in 2010 to 1.98 in 2020; Second, the spatial autocorrelation results reveal that the level of technological innovation and carbon emission intensity in China are obviously aggregated in the global spatial distribution pattern. Third, the regression results of the spatial econometric model show that the direct effect of technological innovation on carbon emission intensity is significantly negative at the level of 1%, that is, the improvement of the technological innovation in a certain area has a significant inhibitory effect on carbon emission intensity. Fourth, based on the level of economic development, there is a significant three-threshold effect of the level of technological innovation on carbon emission intensity in China, and the influence of the level of technological innovation on carbon emission intensity varies in the direction of existence and coefficient values within different threshold intervals. As economic development reaches the third interval, the technological innovation level has the most significant inhibition on carbon emission intensity. These findings enriches the research of the nonlinear relationship between technological innovation and carbon emission intensity, clarifies the spatial spillover effect and threshold effect between among them, and provides inspiration for better promote the low-carbon transformation of economy.

Effect of green value capture on the manufacturing firm performance considering green dynamic capabilities and profitability models

Ensuring and improving the green value acquisition of manufacturing enterprises is one of the critical issues to be solved for manufacturing enterprises to achieve green value and high-quality development. Based on the theory of enterprise value acquisition and dynamic capability theory, we explain the "black box" of the relationship between green value creation and enterprise performance of manufacturing enterprises. The logical thread of "green value creation-profit model-enterprise performance" is constructed, and a green value acquisition mechanism model is proposed. Based on 263 questionnaires from Chinese manufacturing enterprises, the model is empirically tested using multiple regression analysis. The results show that green value creation has a positive impact on corporate performance, while the profit model plays a mediating role between green value creation and corporate performance. Green dynamic capability plays a positive moderating role between green value creation and corporate performance, while green active ability plays a positive moderating role between value creation and profit model.

All roads lead to Rome? The impact of heterogeneous green finance on carbon reduction of Chinese manufacturing enterprises

Based on the system theory and Pareto efficiency theory, this paper, based on the data of listed companies in China's A-share manufacturing industry in 2011-2022, explores the impact of market-driven green finance and government-guided green finance on the carbon emission intensity of manufacturing enterprises, and analyzes the intermediary role of debt financing cost. A negative "U" relationship exists in market-driven green finance/government-guided green finance and the carbon emission intensity of manufacturing enterprises. Further research shows that under the higher debt financing cost, market-driven green finance played a weaker carbon reduction effect. The heterogeneity analysis found that market-driven green finance can have a significant non-linear impact of "promoting growth first and weakening later" on the carbon emissions of energy-saving and environmental protection enterprises, large enterprises, and enterprises with high human capital levels. Government-guided green finance has a significant non-linear impact on non-energy-saving and environmental protection enterprises and small enterprises. This paper provides the theoretical basis and practical inspiration for the government to formulate relevant low-carbon development policies and promote the innovation of green financial tools in the financial market.

Regional common prosperity level and its spatial relationship with carbon emission intensity in China

The characteristics of common prosperity include harmonious relationships between humans and the environment, as well as sustainable economic and social growth. The process of achieving common prosperity will necessarily have an impact on carbon emissions. In this article, panel statistics collected from 30 Chinese provinces and cities between the years 2006 and 2020 are utilized to assess the level of common prosperity and the intensity of carbon emissions in China. Then the SDM model is applied to explore the effects of the common prosperity level on the intensity of carbon emissions. The findings reveal that: (i) The common prosperity level in China has shown an increasing tendency. Between 2006 and 2020, the mean level of common prosperity increased from 0.254 to 0.486. From the regional perspective, eastern China has seen greater levels of common prosperity than central China, while central China has experienced greater levels of common prosperity than western China; regional disparities in the degree of common prosperity are substantial among Chinese provinces from 2006 to 2020; the common prosperity level is relatively high in economically developed provinces and relatively low in economically backward provinces. (ii) China's carbon emission intensity shows a continuous downward tendency. The annual average intensity of China's carbon emissions decreased from 4.458 in 2006 to 2.234 in 2020. From the regional perspective, the three main regions' carbon emission intensity likewise exhibits a decline in tendency between 2006 and 2020; still, western China continues to have the greatest carbon emission intensity, following central China, while eastern China has the smallest; however, certain provinces, notably Inner Mongolia and Shanxi, continue to have high carbon emission intensity. (iii) China's common prosperity level and carbon emission intensity both exhibit positive spatial autocorrelation at a 1% significant level under the adjacency matrix. The spatial agglomeration effect is significant, and adjacent provinces can affect each other. (iv) The SDM (Spatial Durbin Model) model test with fixed effects finds that the increase in the level of common prosperity suppresses the intensity of carbon emissions in the local area and neighboring regions. (v) The mediating effects model indicates that the process of common prosperity suppresses carbon emission intensity through high-quality economic development, narrowing the income disparity, and the development of a sharing economy.

Influences of the ongoing digital transformation of the Chinese Economy on innovation of sustainable green technologies

Green technology innovation (GI) is a key factor in reconciling environmental protection with sustainable economic development. Routinely, GI in private companies have been delayed due to suspicious of pitfalls investments, which result in low return rates. Nevertheless, the digital transformation of Nations' Economies (DE) might be sustainably sound in terms of natural resources demands and environmental pollution. Energy Conservation and Environmental Protection Enterprises (ECEPEs) database was analyzed from 2011 to 2019 at the municipality level to measure the effect and influence of DE on GI in Chinese ECEPEs. The results suggest that DE has a significant positive influence on GI of ECEPEs. Moreover, the influencing mechanism statistical tests reveal that DE can promote GI of ECEPEs by improving internal controls and financing opportunities. Heterogeneous statistical analysis, however, indicates that the promotion of DE on GI might be constrained over the country. In general, DE can promote both high- and low-quality GI but preferably the latter.