Search Results (91)

As climate conditions become increasingly extreme, greater emphasis should be placed on environmental considerations in outward investment to achieve sustainable green development for Chinese enterprises. Therefore, based on panel data of Chinese listed enterprises from 2008 to 2023, this study examines the impact of Outward Foreign Direct Investment (OFDI) and climate policy uncertainty (CPU) on corporate green total factor productivity (GTFP). The findings indicate that OFDI significantly enhances GTFP, but CPU weakens this positive effect. Mechanism analysis reveals that OFDI improves corporate GTFP through promoting green management innovation, deepening digital transformation, and increasing green investment, while CPU exerts negative effects by undermining these mechanisms. Heterogeneity analysis shows that the effect of OFDI is more pronounced for enterprises in eastern regions, non-heavy-pollution enterprises, and low-carbon-intensity enterprises. Furthermore, spillover effect analysis demonstrates that OFDI’s impact on corporate GTFP exhibits significant spatial boundary characteristics and time-varying evolutionary patterns. Finally, external incentives (government environmental subsidies) and internal drivers (climate risk) can hedge against the negative effects of the interaction between CPU and OFDI. Full article

This study examines the impact of artificial intelligence (AI) technology adoption on green innovation using a sample of Chinese A-share listed automotive manufacturing firms from 2015 to 2023. We further investigate the mediating roles of digital transformation and total factor productivity (TFP). AI technology adoption and digital transformation are measured through textual analysis, and the empirical analysis is conducted using fixed-effects models. The results indicate that AI technology adoption significantly enhances green innovation among automotive manufacturing firms. This conclusion remains robust after addressing potential endogeneity concerns and conducting a series of robustness tests. Mediation analysis reveals that improvements in digital transformation and TFP serve as important channels through which AI technology adoption promotes corporate green innovation. Further heterogeneity analysis shows that the positive effect of AI technology adoption on green innovation is significantly weaker among firms located in eastern China than among those in non-eastern regions. These findings provide new insights for managers seeking to improve corporate green innovation performance through AI technology adoption. Full article

Under China’s dual-carbon goals, Green Finance Policy (GFP) and the Environmental Protection Tax Policy (ETP) are key tools for firm-level green transformation, yet their joint micro-effects remain underexplored. Using Shanghai and Shenzhen A-share listed firms from 2011–2022, this study treats the overlapping rollout of the Green Finance Reform and Innovation Pilot Zones and the Environmental Protection Tax reform as a staggered quasi-natural experiment and applies a multi-period DID to identify their synergistic effect on Corporate Green Technology Innovation. Results show that each policy alone promotes green innovation and that their coordination further strengthens the effect. The synergy operates mainly by easing financing constraints and increasing R&D investment. The effect is stronger among firms with better resources, governance, and digitalization, and in regions with stronger institutional environments; it is also more evident in non-heavy-polluting and non-manufacturing sectors. While the policy mix raises both innovation quantity and quality, it does not significantly improve total factor productivity, indicating a “weak Porter effect.” These findings provide micro-level evidence on GFP–ETP synergy and inform the refinement of green finance, environmental tax design, and firm-level green transition policies. Full article

This study investigates how supply chain co-innovation affects the high-quality development of SRDI enterprises, operationalized as total factor productivity (TFP) measured by the LP method. The mechanism remains unclear. Drawing on learning-by-doing theory, together with the resource-based view and stakeholder theory, we propose a sequential pathway: through repeated interactions and knowledge accumulation in collaborative innovation, SRDI enterprises improve their ESG performance, which in turn enhances TFP. Using a sample of listed “little giant” SRDI enterprises from 2018 to 2023, we find that supply chain co-innovation is significantly positively associated with TFP (coefficient 0.003), and the pattern is consistent with ESG performance playing a partial mediating role. Meanwhile, mechanistic analysis also reveals that this correlation is more pronounced in high-profitability enterprises and manufacturing enterprises. This research provides theoretical guidance for SRDI enterprises in choosing innovation models and managing supply chains, offering practical insights for improving total factor productivity. Full article

Green Total Factor Productivity (GTFP) serves as a pivotal indicator for balancing high-quality economic growth with increasingly stringent environmental regulations. However, empirical evidence regarding whether and how firm-level GTFP is associated with enhanced Environmental, Social, and Governance (ESG) performance in emerging markets remains limited. This study addresses this gap by examining the GTFP–ESG nexus within the macro-context of China’s “Dual-Carbon” goals (aiming for peak carbon emissions by 2030 and carbon neutrality by 2060). Utilizing an unbalanced panel dataset of Chinese A-share listed companies strictly covering the period from 2011 to 2022 (with 2010 data exclusively used for one-period lagged variables), we construct firm-level GTFP metrics using a non-radial SBM-DDF global Malmquist–Luenberger index—incorporating both desirable economic outputs and undesirable environmental emissions—and link them with Huazheng ESG ratings. To ensure robust empirical identification, we employ two-way fixed-effects models with lagged variables, propensity score matching (PSM), and an instrumental variable two-stage least squares (IV-2SLS) approach utilizing the leave-one-out provincial average GTFP as an instrument. The results indicate a significant positive association between GTFP and overall ESG performance, as well as its three sub-pillars. Specifically, a one-standard-deviation increase in GTFP corresponds to a 0.15-standard-deviation increase in the ESG score, a marginal effect of profound economic significance, providing robust associational insights via the IV estimates. Mechanism analyses reframe traditional mediation as descriptive associational pathways, revealing that digital transformation, green innovation, and information transparency serve as significant channels, theoretically demonstrating how resource efficiency translates into social legitimacy. Heterogeneity tests show that this association is more pronounced for non-state-owned enterprises, firms in eastern China, and those with lower financing constraints. These findings unpack the “black box” between technical efficiency and sustainability, providing empirical support for policymakers to align corporate productivity with international disclosure standards (such as the EU’s CSRD). Full article

In the context of China’s green transition, this study examines the impact of CEO green experience (CGE) on green total factor productivity (GTFP) of Chinese listed companies, and investigates the moderating roles of ESG fund holdings and CEO duality. Based on the panel data of Chinese A-share listed companies from 2015 to 2023, we use multiple regression models, robustness tests, endogeneity tests, and heterogeneity analyses to verify the research hypotheses. Our results demonstrate the following: (1) CGE significantly enhances corporate GTFP. (2) ESG fund holdings and CEO duality positively moderate the relationship between CGE and GTFP. (3) The improvement of green technological efficiency (GTE) and the promotion of green technological progress (GTP) are the two core channels for CGE to enhance GTFP. (4) The promotion effect of CGE on GTFP is more pronounced in non-state-owned enterprises and regions with advanced infrastructure, and reducing managerial myopia can amplify this positive effect. This study enriches research on executive heterogeneous traits and corporate green development and provides targeted, practical recommendations for corporate green talent governance and government green development policymaking. Full article

Green finance is an important policy for facilitating corporate environmental transformation and supporting sustainable economic development under China’s “dual-carbon” strategy. This study investigates how green financial policies influence a firm’s TFP. A DID framework is employed to estimate the policy effect and to further explore its transmission mechanisms and heterogeneous impacts across firms, applying the data of China’s A-share-listed companies from 2013 to 2024. It is found that green financial policies significantly improve a firm’s TFP. Specifically, firms located in pilot regions exhibit an average increase of 0.4509 in TFP. The results remain stable across multiple robustness checks. In addition, the policy improves TFP through three primary channels: alleviating financing constraints, stimulating green technological innovation, and promoting digital transformation. The mediation analysis based on Bootstrap resampling confirms the statistical significance of the identified transmission channels. Among them, digital transformation plays the most prominent role, contributing 20.62% to the overall mediating effect. Furthermore, the policy can enhance the TFP of non-state-owned enterprises and for firms operating in industries with lower pollution intensity. Finally, this study proposes further improving the green financial policy framework and strengthening support for green technological innovation and digital transformation, thereby better leveraging green finance to enhance firms’ TFP. Full article

Environmental tax is a key market-based instrument for promoting sustainability and reshaping corporate strategy. Using the panel data of Chinese listed firms from 2010 to 2023, this study employs text mining to measure digital transformation and examines the impact of environmental tax on corporate digitalization. The results show that environmental tax significantly promotes digital transformation. The mechanism analyses reveal that green technology innovation and ESG performance serve as important transmission channels. Furthermore, the effect is positively moderated by regional marketization, environmental information disclosure, and low-carbon city policies. The heterogeneity analyses indicate stronger effects in economically developed regions and firms with greater resource endowments. The additional analysis demonstrates that environmental tax enhances both total factor productivity and green governance performance through accelerating digital transformation, achieving a synergistic green–digital transition. This study provides empirical evidence on how market-based environmental policies can foster corporate digital transformation as a pathway toward sustainable development. Full article

Artificial intelligence (AI) is rapidly reshaping firms’ production and organisational processes, yet whether it can serve as a driving force for corporate green transformation remains an open question. Using a sample of Chinese listed manufacturing firms from 2012 to 2023, this study systematically examines the relationship between AI and firms’ green total factor productivity (GTFP), and explores potential underlying mechanisms. At the theoretical level, drawing on the task-driven nature of AI as a form of technological innovation, this study proposes that AI may enhance GTFP through two channels, namely the structural labour reallocation effect and the managerial dissipation reduction effect. The empirical results show the following: (1) Firms’ AI technical level is significantly associated with improvements in GTFP. (2) Mechanism tests indicate that AI is significantly related to an increasing share of creative task employees and a declining share of structural task employees, thereby providing empirical evidence for the structural labour reallocation effect. Moreover, from four dimensions, including information dissipation, resource allocation dissipation, process coordination dissipation, and incentive and learning dissipation, this study provides supportive evidence that AI is linked to reduced managerial dissipation. (3) Heterogeneity analysis suggests that this association is more pronounced among firms with greater scope for green improvement, such as non-heavily polluting firms and those characterised by managerial myopia. Overall, this study deepens the understanding of the relationship between AI and GTFP from the perspectives of labour structure and corporate organisation, and emphasises that AI’s contribution to firms’ GTFP is more likely to arise as a systemic facilitation embedded in production and organisational processes, rather than through the direct substitution of specialised green technologies. Full article

Drawing on data from Chinese A-share listed companies between 2011 and 2020, this paper explores how corporate digital transformation shapes Green Total Factor Productivity (GTFP) and its underlying components. The findings suggest that digital transformation promotes GTFP by enhancing innovation capability and accounting transparency, while simultaneously reducing financing frictions. However, stricter environmental regulation attenuates these positive effects, particularly with respect to Green Technological Efficiency Change (GTEC). Non-state-owned enterprises, industrial firms, and high-carbon emitters can more effectively leverage digital transformation to enhance their GTFP; however, the negative impact of environmental regulations is also more pronounced among these entities. The interaction between digital transformation and GTFP elevates corporate market value, with this value effect primarily stemming from improvements in GTEC. By decomposing GTFP into Green Technological Change (GTC) and GTEC, this study clarifies the operational pathways of digital transformation and environmental regulations, enriching the theoretical framework for green productivity research. It reveals the channel-specific effects of environmental regulations—namely, their primary modulation of digital transformation’s green enabling role through influencing GTEC rather than GTC—and systematically integrates multiple pathways for enhancing green productivity via digital transformation, green innovation, information transparency, and financing mechanisms. This provides mechanistic guidance for corporate green development strategies. The research highlights digital transformation’s pivotal role in advancing corporate green development, offering practical insights for policymakers and business managers in promoting sustainable development and formulating environmental policies. Full article

Despite stringent environmental regulations, the divergence between private costs and social benefits frequently induces symbolic rather than substantive firm compliance. This study investigates Executive Green Cognition (EGC) as an internal mechanism to mitigate this distortion. Using a text-based index derived from Management Discussion and Analysis (MD&A) disclosures of Chinese listed firms (2010–2024), we demonstrate that higher EGC significantly facilitates corporate green transition by enhancing both green innovation output and Total Factor Productivity. Supporting the micro-foundations of the Porter Hypothesis, we find that these productivity gains coincide with reduced Carbon Emission Intensity (CEI), thereby ruling out scale expansion effects. Mechanism tests indicate that EGC reduces agency costs by reallocating resources from non-productive defensive expenditures to substantive green investments. Furthermore, digital transformation positively moderates this relationship by lowering implementation costs. These findings highlight EGC as a critical micro-foundation for shifting firms from passive compliance to endogenous sustainable development. Full article

China’s dual pursuit of a “Digital China” and its carbon-neutral goals has driven a coordinated strategy of digitalization and green transformation. Yet the extent to which firms have realized this synergy—and its effect on total factor productivity (TFP)—remains underexplored. Using panel data from 2011 to 2025 on all A-share listed companies, we construct a composite index of digital–green coordination and estimate firm-level TFP via the Levinsohn–Petrin method. Employing fixed-effects panel regressions and mediation analyses, we find the following: (1) the digital–green synergy significantly enhances TFP growth, with robustness confirmed across alternative measures, propensity score matching, city fixed effects, and instrumental variable approaches; (2) this effect is stronger for non-SOEs and firms with higher baseline TFP and exhibited an “inverted-U” pattern over China’s 13th and 14th Five-Year Plans; (3) corporate social responsibility (CSR), cost stickiness reduction, and green technological innovation each mediate this relationship—CSR and cost stickiness play larger roles in SOEs, while green innovation mediates across all firm types and TFP levels, also showing an “inverted-U” temporal trend; and (4) over time, CSR’s mediating effect wanes in the 14th Five-Year period, cost stickiness mediation gradually declines, and green innovation mediation is continually strengthened. These findings provide evidence of the association between digital–green alignment and firm productivity in China, using an index that summarizes the joint orientation toward digitalization and greening. Full article

Against the backdrop of global energy transition and sustainable development, advancing the new energy industry has become a critical pathway for optimizing energy structures and achieving the dual carbon goals. However, while China’s new energy sector has experienced rapid growth, it has also exposed a series of challenges, including insufficient innovation momentum, irrational resource allocation, and low conversion rates of R&D outcomes. To delve into the root causes and propose improvement pathways, this study selected 76 listed new energy enterprises from 2021 to 2023 as samples. It comprehensively employed the DEA-BCC model, Malmquist productivity index, and Tobit regression model to conduct empirical analysis across three dimensions: static, dynamic, and influencing factors. The findings revealed: firstly, during the study period, overall static efficiency remained low, with only about 32.90% of enterprises operating efficiently. Efficiency decomposition indicated that low and unstable pure technical efficiency constrained overall efficiency gains. In contrast, while scale efficiency was relatively high, its growth was sluggish, and some enterprises exhibited significant scale irrelevance. Secondly, dynamic total factor productivity exhibited fluctuating growth primarily driven by technological progress. However, declining technical efficiency—particularly the deterioration of scale efficiency—indicated that while the new energy industry advanced technologically and expanded in scale, its management capabilities had not kept pace. This mismatch among the three factors trapped the industry in a “high investment, low efficiency” dilemma. Thirdly, regression analysis of influencing factors indicated that corporate governance and market competitiveness were pivotal to innovation efficiency: the proportion of independent directors and revenue growth rate exerted significant positive impacts, while equity concentration showed a significant negative effect. Firm size had a weaker influence, and government support did not demonstrate a significant positive impact. Accordingly, this paper proposes pathways to enhance innovation efficiency in new energy enterprises, including optimizing corporate governance structures, formulating differentiated subsidy policies, and improving the innovation ecosystem. The findings of this study not only provide empirical references for the innovative development of the new energy industry but also offer theoretical support for relevant policy formulation. Full article

Against the dual demands of green transformation and digital integration in the manufacturing industry, green value co-creation has become a core pathway for enterprises to achieve sustainable development. However, the role of artificial intelligence (AI) in driving green value co-creation remains under explored, especially in the context of Chinese manufacturing. To enrich this research, this study aims to investigate the impact of AI development on corporate green value co-creation and its intrinsic mechanism. This study draws on panel data of listed manufacturing enterprises listed on China’s Shanghai and Shenzhen A share markets spanning the period 2015–2024, and employs multiple regression and negative binomial regression as research methodologies to empirically examine the impact of AI development on corporate green value co-creation and its underlying mechanisms. The results demonstrate that: AI development exerts a significantly positive effect on manufacturing enterprises’ green value co-creation, which is achieved by enhancing firms’ technological spillover capacity and total factor productivity (TFP); financing constraints negatively moderate the aforementioned relationship, while corporate influence plays a positive moderating role; heterogeneity analysis reveals that this impact is more pronounced for enterprises under voluntary regulation, state-owned enterprises (SOEs), and high-pollution enterprises. This study elucidates AI’s role and mechanism in corporate green development at the micro level, provides empirical evidence for related research, and offers practical insights to promote enterprise AI advancement and green value co-creation. Full article

We investigate the effect of financial openness on corporate resilience. Corporate resilience metrics refer to the processes through which firms respond to crises, encompassing the capabilities developed during adaptation, absorption, innovation, recovery, and development. Using dynamic difference-in-differences (DID) models and panel data on Chinese A-share listed firms from 2009 to 2022, we found that firms included in the Shanghai-Hong Kong and Shenzhen-Hong Kong Stock Connect (SSHK) lists exhibited higher levels of corporate resilience after the openness. Introducing foreign ownership and improving the quality of information disclosure are two plausible pathways through which financial openness can promote corporate resilience. At the same time, the degree of industry competition and level of external financing dependence moderate the results. Importantly, corporate resilience moderates the positive long-term effect of financial openness on firms’ total factor productivity (TFP). These findings highlight that fostering corporate resilience is not merely an outcome but a critical condition for translating financial integration into sustainable productivity gains, enlightening resilience-oriented policymaking in emerging markets undergoing reform. Full article