Search Results (66)

In this study, we examine the impact of mergers and acquisitions (M&As) on firm environmental performance, aiming to address the gap in research and guide firms, investors, and policymakers toward more environmentally conscious decision-making in M&A. Using panel data from Chinese A-share listed firms (2008–2022), we estimate a two-way fixed effect model. The Propensity Score Matching and the instrumental variable method address potential endogeneity concerns, and robustness checks validate the findings. We found that M&As have a significantly positive effect on firm environmental performance, with heterogeneous impacts across regions, industries, and M&A types. The environmental benefits are most pronounced in heavily polluting industries and hybrid M&A deals. Eastern China shows more modest improvements. The results of mechanism tests revealed that M&As enhance environmental performance primarily by boosting total factor productivity and fostering innovation. This study offers a novel perspective by linking M&A activities to environmental sustainability, enriching the literature on both M&As and corporate environmental performance. We show that even conventional M&A deals (not sustainability-focused) can improve environmental performance through operational synergies. Expanding beyond polluting industries, we reveal how sector characteristics shape M&A’s environmental impacts. We identify practical mechanisms through which standard M&A activities can advance sustainability goals, helping firms balance economic and environmental objectives. It provides empirical evidence from China, an emerging market with distinct institutional and regulatory contexts. The findings offer guidance for firms engaging in M&A to strategically improve sustainability performance. Policymakers can leverage these insights to design incentives for M&A in pollution-intensive industries, aligning economic growth with environmental goals. By demonstrating that M&As can enhance environmental outcomes, this study supports the potential for market-driven mechanisms to contribute to broader societal sustainability objectives, such as reduced industrial pollution and greener production practices. Full article

It is increasingly recognized that the twin transitions of digitalization and green transformation are pivotal to achieving sustainable development. This study examines how digital trade affects corporate green total factor productivity (GTFP), using panel data from Chinese A-share listed firms and 287 prefecture-level cities in Mainland China from 2012 to 2022. The results demonstrate that digital trade exerts a significant positive impact on GTFP, primarily through improvements in technical efficiency, with heterogeneous effects across different stages of the corporate life cycle. Endogeneity concerns are carefully addressed through instrumental variable estimation and quasi-experimental designs, and robustness checks confirm the reliability of the findings. Mechanism analyses further reveal that digital trade enhances GTFP by stimulating green technological innovation and optimizing supply chain management. Importantly, threshold regression reveals non-linear effects. Both the level of digital trade and institutional factors, such as environmental regulation, intellectual property protection, and market integration, moderate the relationship between digital trade and GTFP in U-shaped, N-shaped, and other positive non-linear patterns. These insights enhance the understanding of how digitalization interacts with institutional contexts to drive sustainable productivity growth, providing practical implications for policymakers seeking to optimize digital trade strategies and complementary regulatory frameworks. Full article

As participants in sustainable development, corporations face the important and controversial issue of whether they can promote corporate sustainability through environmental, social, and governance (ESG) practices. To address this issue, we examine the relationship between ESG performance and corporate sustainability, measured by green total factor productivity (GTFP). Using a panel dataset of 17,559 firm-year observations from non-financial firms listed on the Shanghai and Shenzhen stock exchanges in China between 2011 and 2019, we employ fixed-effects regression models and two-stage least squares (2SLS) with instrumental variables to empirically test the impact of ESG ratings on GTFP, identify the underlying mechanisms, and examine potential heterogeneity across firms. The results show that higher ESG ratings are significantly associated with increased GTFP. Mediation analysis further reveals that this positive relationship operates through reduced financing constraints and enhanced green innovation. Notably, the mediating role of financing constraints is more pronounced for firms with greater reliance on external capital. Heterogeneity analysis indicates that ESG ratings exert stronger effects in eastern regions, pollution-intensive sectors, and state-owned enterprises. These findings provide empirical support for the role of ESG performance as an effective mechanism to advance corporate sustainability through ethics-driven financial access and innovation capability. Full article

This study examines the impact of capital market openness on corporate green total factor productivity (GTFP) using a quasi-natural experiment based on the Shanghai-Hong Kong and Shenzhen-Hong Kong Stock Connect policies. Employing a multi-period difference-in-differences (DID) approach, the findings reveal that capital market openness significantly enhances corporate GTFP through two primary mechanisms: strengthening firms’ green financial resources and technological innovation (green “hard strength”) and improving corporate environmental governance, green information disclosure, and managerial green expertise (green “soft strength”). Further heterogeneity analysis suggests that firms with greater institutional investor engagement, higher market competition, and non-state ownership exhibit stronger responses. These results provide policy insights into leveraging financial liberalization to drive corporate sustainability and green economic growth. This study highlights the role of financial markets in supporting global carbon neutrality and sustainable development goals. Full article

Against global carbon neutrality goals and China’s “dual carbon” strategy, this study examines how green technology innovation shapes corporate carbon performance through a dual-path mechanism—improving enterprises’ resource utilization efficiency and environmental governance capabilities. Leveraging data from Chinese A-share listed firms (2007–2022) and methods including fixed effects, instrumental variables, and Heckman two-stage models, key findings include: (1) Green technology innovation significantly improves carbon performance. (2) This effect operates through two pathways: enhancing total factor productivity (TFP) and strengthening environmental governance. (3) Green media and investor attention amplify the positive impact of green innovation on carbon performance. (4) The effect remains significant but shows diminishing marginal returns over 1–4 future periods. (5) Non-state-owned enterprises and non-high-carbon industries exhibit more pronounced improvements. This research provides micro-level evidence for “technology-driven low-carbon transformation”, offering theoretical support for policy differentiation and corporate green technology strategies, with practical implications for achieving China’s “dual carbon” objectives. Full article

Corporate environmental, social, and governance (ESG) performance has become an increasingly critical driver of sustainable development. Investigating the impact of ESG performance on corporate green development is of great significance for achieving green transformation and sustainability goals. This study examines the effects and underlying mechanisms of ESG performance on the green development of Chinese A-share listed companies in the agricultural and forestry sectors from 2013 to 2023. The empirical results show that higher ESG performance significantly promotes corporate green development. Further heterogeneity analysis reveals that this effect varies markedly across ownership structures, geographic regions, and levels of ESG rating uncertainty. Mechanism testing indicates that ESG performance fosters green development primarily through three pathways: stimulating green innovation, improving resource allocation efficiency, and enhancing the structure of human capital. In addition, by decomposing green total factor productivity, this study further quantifies the contribution of ESG performance to green growth. These findings offer new insights into the ESG–green development nexus and provide valuable policy implications for the green transformation and sustainable development of agricultural and forestry enterprises. Full article

Firm value reflects a company’s market competitiveness, while ESG controversies indicate its ESG risks. This study aims to examine the impact of ESG controversies on firm value and its underlying mechanisms. Using a panel dataset of 851 non-financial firms listed in China’s A-share market between 2010 and 2022, this study investigates the relationship between ESG controversies and firm value using a two-way fixed-effects model. The analysis shows that ESG controversies impair firm value. This relationship remains robust after conducting the Heckman test, 2SLS methods, and heteroskedasticity tests. Further mediation analysis indicates that ESG controversies negatively affect firm value through lower levels of green innovation, total factor productivity, and financing constraints. In addition, the study examines the moderating effects of social performance, environmental performance, and analyst forecast bias. Finally, a heterogeneity analysis was conducted. These findings provide new perspectives for understanding the complex dynamics between ESG controversies and firm value, essential for strengthening the ESG rating framework and promoting sustainable corporate development. Full article

Based on the quasi-natural experiment of “the pilot policy of combining science and technology with finance” (Sci-Tech Finance pilot policy) carried out in China in recent years, this paper constructs a multi-stage difference-in-differences model to explore its impact on corporate ESG performance and the influence mechanisms. The main research findings of this paper are as follows: (1) The Sci-Tech Finance pilot policy significantly enhances corporate ESG performance, a finding that remains consistent after conducting parallel trends testing, propensity score matching, and placebo tests. (2) The policy promotes the corporate ESG performance through three intermediary channels, namely alleviating financial constraints, improving total factor productivity, and enhancing green technology innovation. Notably, the first two intermediary channels exhibit the most prominent effects. (3) The impact of the pilot policy on the corporate ESG performance exhibits heterogeneity at both the regional and corporate levels; it demonstrates a more pronounced impact on corporates located in the Eastern Region, within high digital economic zones, and among high-tech, capital-intensive, heavily polluting, and state-owned corporates. (4) The policy has apparent spatial spillover effects on corporate ESG performance, accounting for about 8% of the direct effect in the pilot areas. This study enriches the literature on the impacts of Sci-Tech Finance on corporate behaviors, providing insights for government regulatory authorities to leverage Sci-Tech Finance policies to promote corporate ESG performance and sustainable development. Full article

Total factor productivity serves as a critical indicator of high-quality corporate development. This study systematically examines the impact of ESG performance on TFP using panel data from Shanghai and Shenzhen A-share listed firms spanning 2009 to 2023. The findings reveal three key insights: first, corporate ESG performance significantly enhances TFP, with regression analysis demonstrating a statistically robust positive correlation (1% significance level) and high explanatory power (R² > 0.8). Second, under environmental uncertainty, ESG-driven total factor productivity improvements operate through dual mechanisms: energy conservation and resource allocation optimisation. Third, heterogeneity analysis highlights that non-state-owned enterprises exhibit a more pronounced relationship compared to state-owned counterparts, particularly in high-environmental-uncertainty scenarios. Beyond enriching academic discourse on ESG metrics, this research elucidates the intrinsic linkage between ESG practices and TFP under dynamic environmental conditions, offering actionable strategies for firms to align sustainability goals with productivity growth. For international stakeholders, this study provides empirical evidence from China—the world’s second-largest economy—to inform global ESG policy design and cross-border investment decisions, emphasising the role of institutional contexts in sustainability-driven value creation. The insights are pivotal for investors, policymakers, and multinational corporations seeking to navigate ESG complexities while advancing sustainable development goals in emerging markets. Full article

The rapid development and widespread application of artificial intelligence (AI) and robots have profoundly impacted the economy, society, and the environment. This article focuses on the relationship between industrial robots and green sustainable transformation in high-energy-consuming industries. Through the Poisson distribution fixed effect, the negative binomial fixed-effect model, and the two-way fixed-effect model, we found that the penetration of industrial robots in high-energy-consuming enterprises (HEEs) has a significant and positive effect on green innovation. In particular, we verified that total factor productivity and ESG, included in the zero-inflation model, have a breakthrough-accelerating role in the application of industrial robots to promote green sustainable transformation. Further analysis indicated that the adoption of industrial robots is also positively correlated with the improvement of corporate green sustainable transformation in non-state-owned enterprises, but state-owned enterprises are not sensitive. In the classification of segmented industries, only the metallurgical industry demonstrates the empowering role of green sustainable transformation. This article provides a new avenue for reshaping the low-carbon green sustainable transformation strategy of HEEs, as well as useful insights, supporting the achievement of carbon peak and carbon neutrality by promoting the application of industrial robots and further improving total factor productivity and ESG performance. Full article

Green total factor productivity (GTFP) is a key factor for achieving sustainable development and enhancing economic competitiveness. Environmental information disclosure plays a significant role in improving the corporate GTFP. Using A-share-listed company data in China from 2009 to 2019, this study employs the Ambient Air Quality Standards (GB3095-2012) promulgated by China in 2012 as a quasi-natural experiment. This study employs difference-in-differences (DID) to examine the impact of environmental information disclosure on corporate GTFP. The findings reveal that on average, environmental information disclosure positively affects firms’ GTFP. Mechanism analyses show that environmental information disclosure promotes GTFP by increasing total corporate costs, alleviating corporate financing constraints, and promoting green technological innovation. Environmental information disclosure mainly affects non-state-owned smaller, and young enterprises. These conclusions provide theoretical support and empirical evidence for governments to leverage environmental information disclosure to promote green and sustainable development, thereby achieving high-quality economic growth. Full article

The long-term development of the manufacturing industry relies on sustainable tax management, which plays a key role in optimizing production costs. While artificial intelligence models have been applied to tax-related predictions, research on their application for predicting tax management levels is quite limited, with no studies focused on the manufacturing industry in China. To enhance digital innovation in corporate management, this study applies interpretable artificial intelligence models to predict the tax management level, which helps decision-makers maintain it within a sustainable range. The ratio of total tax expense to total profits (ETR) is used to represent the tax management level, which is predicted using decision trees, random forests, linear regression, support vector regression, and artificial neural networks with eight input features. Comparisons among the developed models indicate that the random forest model exhibits the best performance in terms of prediction accuracy and generalization capability. Additionally, the Shapley additive explanations (SHAP) technique is integrated with the developed model to enhance the interpretability of its predictions. The SHAP results reveal the importance of the input features and also highlight the dominance of certain features. The results show that the ETR from the previous year holds the greatest importance, being more than twice as significant as the second most important factor, whereas the effect of board size is negligible. Moreover, benefiting from the local interpretations using SHAP values, this approach aids managers in making rational tax management decisions. Full article

This study investigates the impact of local government debt levels on the behavior of individual firms, which is crucial for understanding the systemic risks associated with local government debt and fostering economic vitality. Using data from publicly listed companies on the Shanghai and Shenzhen stock exchanges between 2013 and 2022, this study empirically examines the effect of local government debt on corporate innovation quality. The findings demonstrate that local government debt expansion has a significant negative impact on corporate innovation quality. The negative impact remains robust across endogeneity tests and multiple robustness checks. Channel analysis indicates that as local government debt increases, innovation subsidies and procurement funding led toward firms’ decline, while both tax and non-tax revenue demands indicated firm increases. This resource reallocation contributes to the observed decline in corporate innovation quality. Further heterogeneity analysis reveals that regions with lower levels of government intervention and fiscal pressure exhibit a smaller negative effect of local government debt on innovation quality. Finally, examining the economic outcomes reveals that the decline in innovation quality, resulting from current local debt expansion, significantly reduces total factor productivity and firm value in the subsequent year, posing challenges for sustainable corporate development. Full article

Total factor productivity (TFP) is pivotal to driving sustainable economic growth. This study examines the relationship between fiscal policy uncertainty (FPU) and firms’ TFP with the least squares method. We measure FPU at the provincial level using government work reports from various provinces in China with text analysis and find that a higher degree of FPU is negatively associated with local firms’ TFP. This effect is more significant for firms from regions with lower levels of marketization and government fiscal transparency and those with higher managerial myopia than for other firms. The channel tests show that FPU reduces local firms’ TFP by inhibiting corporate expansionary and research and development investments, and this effect is supported by the intensified financing constraints. Overall, our results suggest that FPU impairs local firms’ production efficiency. Full article

Global environmental issues are becoming increasingly prominent and environmental, social and governance (ESG) ratings may play a key role in green development by stimulating informal environmental regulation from stakeholders. As a pivotal criterion for measuring green development, green total factor productivity (GTFP) refers to maximizing output while minimizing the environmental pollution for the required input production factors. Existing research neglects the impact of ESG ratings on GTFP that indicates the balance between economic growth and ecological protection. This study examines the impact of ESG ratings and mechanisms on GTFP using a sample of Chinese A-share listed manufacturing firms between 2010 and 2021. The findings indicate that ESG ratings promote corporate GTFP, a result which remains robust after a series of robustness tests. The mechanism analysis reveals that ESG ratings improve corporate GTFP by alleviating financial constraints, mitigating managerial myopia, and enhancing supply chain efficiency. A moderating analysis verified that managerial power weakens the positive impact of ESG ratings on corporate GTFP. The positive effect of ESG ratings on GTFP is more pronounced among non-state-owned firms and firms in non-heavily polluting and highly competitive industries. This study confirms that ESG ratings can achieve the benefits of productivity growth, energy conservation, and pollution reduction at the micro-enterprise level, offering a policy foundation for promoting ESG disclosure and achieving green development. Full article