Search Results (91)

China’s national strategies emphasize both achieving carbon peaking and neutrality (“dual carbon” objectives) and fostering high-quality economic development. This dual focus highlights the critical importance of the Green and Low-Carbon Transition (GLCT) of the economy and the development of New Quality Productive Forces (NQPF). Firms are central actors in this transformation, prompting the core research question: How does corporate engagement in GLCT contribute to the formation of NQPF? We investigate this relationship using panel data comprising 33,768 firm-year observations for A-share listed companies across diverse industries in China from 2012 to 2022. Corporate GLCT is measured via textual analysis of annual reports, while an NQPF index, incorporating both tangible and intangible dimensions, is constructed using the entropy method. Our empirical analysis relies primarily on fixed-effects regressions, supplemented by various robustness checks and alternative econometric specifications. The results demonstrate a significantly positive relationship: corporate GLCT robustly promotes the development of NQPF, with dynamic lag structures suggesting delayed productivity realization. Mechanism analysis reveals that this effect operates through three primary channels: improved access to financing, stimulated collaborative innovation and enhanced resource-allocation efficiency. Heterogeneity analysis indicates that the positive impact of GLCT on NQPF is more pronounced for state-owned enterprises (SOEs), firms operating in high-emission sectors, those in energy-efficient or environmentally friendly industries, technology-intensive sectors, non-heavily polluting industries and companies situated in China’s eastern regions. Overall, our findings suggest that corporate GLCT enhances NQPF by improving resource-utilization efficiency and fostering innovation, with these effects amplified by specific regional advantages and firm characteristics. This study offers implications for corporate strategy, highlighting how aligning GLCT initiatives with core business objectives can drive NQPF, and provides evidence relevant for policymakers aiming to optimize environmental governance and foster sustainable economic pathways. Full article

As inevitable outcomes of the digital economy’s low-carbon development, green data centers play a crucial role in environmental impact and underlying mechanisms. This study focuses on green data center establishment as a representative practice, utilizing Chinese A-share listed companies and urban data from 2009 to 2023 to construct a multi-period difference-in-differences model. From a supply chain perspective, we investigate the impact of green data centers on corporate carbon emissions and their mechanisms. The results demonstrate that regional establishment of green data centers significantly promotes corporate carbon emission reduction, with conclusions remaining robust after a series of comprehensive robustness and endogeneity tests. This process primarily operates through two channels: green total factor energy efficiency and green attention. Green data center establishment significantly enhances green total factor energy efficiency and corporate green attention. The more developed the regional digital infrastructure and the higher the computing power development levels, the stronger the incentive effect on corporate carbon reduction. Heterogeneity analysis reveals that green data centers have more significant promoting effects on carbon emission reduction in state-owned enterprises and high-tech enterprises. This research contributes to a deeper understanding of the effects, mechanisms, and regional variations related to green data centers in facilitating corporate carbon emission reduction. Full article

In the era of low-carbon economy, green mergers and acquisitions (green M&As) have emerged as a pivotal strategic pathway for heavily polluting enterprises to not only carve out a competitive edge in the market but also contribute significantly to the achievement of Sustainable Development Goal 12 (SDG 12)—Responsible Consumption and Production. Based on the data of China’s heavily polluting enterprises listed on the Shanghai and Shenzhen A-share markets from 2010 to 2022, this study applies the multi-temporal difference-in-differences method to analyze the impact of green M&As on the market power of heavily polluting enterprises. The findings suggest that the adoption of green M&As by heavily polluting enterprises in China can enhance market power, and this conclusion remains valid after a series of robustness tests. The mediation effect analysis shows that green M&As promote the market power of heavily polluting enterprises by increasing green total factor productivity, optimizing human capital structure and enhancing brand capital. Meanwhile, according to the heterogeneity study conducted, the implementation of green M&As by non-state-owned heavily polluting enterprises and heavily polluting enterprises within the growth period has a more pronounced effect on market power promotion. In addition, domestic green M&As have a stronger effect on the market power of heavily polluting enterprises. By bridging the theoretical gap between green M&As and the driving mechanisms of market power, this study not only enriches the academic literature but also provides actionable insights for heavily polluting enterprises seeking to enhance their market competitiveness while adhering to sustainable development principles. Full article

This paper examines the impact of carbon capture and storage (CCS) deployment on national carbon intensity (CI) across 43 countries from 2010 to 2020. Using a dynamic common correlated effects (DCCE) log–log panel, we estimate the elasticity of CI with respect to sectoral CCS facility counts within four income-group panels and the full sample. In the high-income panel, CCS in direct air capture, cement, iron and steel, power and heat, and natural gas processing sectors produces statistically significant CI declines of 0.15%, 0.13%, 0.095%, 0.092%, and 0.087% per 1% increase in facilities, respectively (all p < 0.05). Upper-middle-income countries exhibit strong CI reductions in direct air capture (–0.22%) and cement (–0.21%) but mixed results in other sectors. Lower-middle- and low-income panels show attenuated or positive elasticities—reflecting early-stage CCS adoption and infrastructure barriers. Robustness checks confirm these patterns both before and after the 2015 Paris Agreement and between emerging and developed economy panels. Spatial analysis reveals that the United States and United Kingdom achieved 30–40% CI reductions over the decade, whereas China, India, and Indonesia realized only 10–20% declines (relative to a 2010 baseline), highlighting regional deployment gaps. Drawing on these detailed income-group insights, we propose tailored policy pathways: in high-income settings, expand tax credits and public–private infrastructure partnerships; in upper-middle-income regions, utilize blended finance and technology-transfer programs; and in lower-income contexts, establish pilot CCS hubs with international support and shared storage networks. We further recommend measures to manage CCS’s energy and water penalties, implement rigorous monitoring to mitigate leakage risks, and design risk-sharing contracts to address economic uncertainties. Full article

Accurate carbon market price prediction is crucial for promoting a low-carbon economy and sustainable engineering. Traditional models often face challenges in effectively capturing the multifractality inherent in carbon market prices. Inspired by the self-similarity and scale invariance inherent in fractal structures, this study proposes a novel multifractal-aware model, MF-Transformer-DEC, for carbon market price prediction. The multi-scale convolution (MSC) module employs multi-layer dilated convolutions constrained by shared convolution kernel weights to construct a scale-invariant convolutional network. By projecting and reconstructing time series data within a multi-scale fractal space, MSC enhances the model’s ability to adapt to complex nonlinear fluctuations while significantly suppressing noise interference. The fractal attention (FA) module calculates similarity matrices within a multi-scale feature space through multi-head attention, adaptively integrating multifractal market dynamics and implicit associations. The dynamic error correction (DEC) module models error commonality through variational autoencoder (VAE), and uncertainty-guided dynamic weighting achieves robust error correction. The proposed model achieved an average R² of 0.9777 and 0.9942 for 7-step ahead predictions on the Shanghai and Guangdong carbon price datasets, respectively. This study pioneers the interdisciplinary integration of fractal theory and artificial intelligence methods for complex engineering analysis, enhancing the accuracy of carbon market price prediction. The proposed technical pathway of “multi-scale deconstruction and similarity mining” offers a valuable reference for AI-driven fractal modeling. Full article

Urgency and severity of climate change impacts have become increasingly prominent, making the enhancement of corporate climate risk disclosure (CCRD) a shared demand among regulators, investors, and the general public. From the perspective of irrational behavioral traits, this paper utilizes a sample of A-share-listed companies in China from 2008 to 2022 to empirically examine the impact of executives’ overseas experiences on CCRD and its underlying mechanisms. To measure firm-level climate risk disclosure, we employ machine learning-based textual analysis techniques and match the constructed disclosure indicators with firms’ financial data. The results demonstrate that executives with overseas experience significantly enhance the level of CCRD, and this effect remains consistent after a series of robustness tests. This effect operates through the dual paths of “climate attention allocation enhancement” and “management myopia mitigation”. Moreover, the positive impact of overseas experience is more pronounced among firms in climate-sensitive industries and regions with lower climate awareness. A further analysis of executive overseas experience characteristics shows that executives with experience in developed economies and those with international educational backgrounds exhibit a stronger influence in promoting CCRD. Additionally, an investigation into the economic consequences demonstrates that executives with overseas experiences not only improve firms’ ESG performances but also help reduce ESG rating discrepancies, reinforcing the beneficial role of overseas exposure in corporate governance. The findings not only provided micro-level empirical evidence for the effectiveness of talent recruitment policies in emerging economies but also yielded critical policy implications for regulatory bodies to refine climate disclosure frameworks and enable enterprises to leverage opportunities in low-carbon transition. Full article

Farmer professional cooperatives are the focus objects of agricultural carbon emission reduction; with the use of the advantages of scale economy and technology, one can promote the development of low-carbon agriculture. In order to study the influencing factors of agricultural carbon emission reduction on farmer professional cooperatives, we explore the interaction effects of carbon emission reduction behavior between farmer professional cooperatives and farmers under government interventions. This paper introduces a carbon transaction mechanism as well as reward and punishment polices into a tripartite evolutionary game model between farmer professional cooperatives, governments, and farmers. Based on the model, we identify a stable evolution strategy and perform simulation analysis. The results indicate that the carbon transaction mechanism can effectively suppress the negative effect of increased costs through higher revenues of the carbon transaction, and carbon prices above 60 CNY/ton enable cooperatives to reduce regional emissions. Higher revenues can promote positive carbon emission reduction behaviors of farmer professional cooperatives and farmers. The sharing ratio increases from 20% to 80%, and farmers gain additional benefits by cooperating in the farmer professional cooperative practices to reduce emissions. Rational regulation of carbon transaction price and quota can promote the participation of farmer professional cooperatives in carbon emission reduction practices and promote the farmers’ inclusion into farmer professional cooperatives. Full article

Under the dual transformation background of global digital economy and low-carbon development, the synergistic promotion of enterprise digital transformation and green upgrading has become an important path to realizing high-quality development. Based on the coupling coordination degree model, this paper constructs the enterprise “digital-green” dual transformation synergy measurement index system, and empirically analyzes the panel data of China’s A-share-listed companies from 2017 to 2022 using the entropy weight-coupling coordination degree model and the fixed effect model. This study finds that, firstly, the synergy degree of the eastern region is significantly higher than that of the inland, less-developed provinces, but the regional gap is narrowing and the spatial pattern is evolving from the “central collapse type” to the low-level equilibrium type. Second, there is a significant positive driving effect of digital finance on the collaborative transformation of enterprises’ digitalization and greening, and the path of its action includes the effect of alleviating financing constraints, the empowerment of information transparency, and the effect of moderating and amplifying entrepreneurship. Third, the driving efficacy of digital finance in state-owned enterprises is more prominent than that in private enterprises. Fourth, digital finance significantly affects the degree of synergy, but there is a threshold effect. This study reveals the catalytic role of digital finance in the coupling process of digital transformation and greening upgrading, which not only expands the analytical dimension of transition economy theory but also provides a quantitative basis for policymakers to optimize the allocation of financial resources and for enterprises to design transformation paths. Full article

This study provides a comparative analysis of the environmental and economic performance of Oman, Egypt, and Morocco, focusing on the critical interplay between their economic structures, governance frameworks, and energy policies. Morocco stands out as a regional leader in renewable energy, driven by significant investments in solar, wind, and hydroelectric projects, positioning itself as a model for clean energy transition. Egypt, despite its rapid industrialization and urbanization, faces mounting environmental pressures that challenge its economic diversification efforts. Oman, heavily dependent on hydrocarbons, confronts significant sustainability risks due to its reliance on fossil fuels, despite the political stability that could support renewable integration. The research underscores that while these nations share common challenges, including regulatory weaknesses and energy policy inconsistencies, their distinct economic contexts demand tailored approaches. Morocco’s path to energy leadership must focus on integrating renewables across all sectors, enhancing grid infrastructure, and expanding green technology innovations to maintain momentum. Egypt should prioritize scaling up renewable infrastructure, reducing dependency on fossil fuels, and investing in clean technology to address its carbon footprint. For Oman, the strategic diversification of its economy, combined with aggressive renewable energy integration, is critical to reducing CO₂ emissions and mitigating climate impacts. This study contributes novel insights by highlighting the role of political stability, institutional quality, and policy coherence as critical enablers of long-term sustainability. It also identifies the importance of regional cooperation and knowledge sharing to overcome shared challenges like data limitations, geopolitical complexities, and methodological gaps in sustainability assessments. The findings advocate for a multi-method approach, integrating economic modeling, life-cycle analysis, and policy evaluation, to guide future sustainability efforts and foster resilient, low-carbon economies in the MENA region. Full article

China is presently placing significant emphasis on sustainable urbanization as a means to facilitate the shift towards high-quality economic development. The concept of sustainable urbanization has gained added intricacy and depth within the framework of ‘carbon peak and carbon neutrality’. A primary concern among practitioners is that while carbon emissions adhere to specific standards, the term sustainable urbanization remains vaguely defined, encompassing multifaceted objectives. The absence of a well-defined evaluative standard for sustainable urbanization creates challenges in driving comprehensive progress. Additionally, owing to the spatially heterogeneous nature of urbanization, its influence on carbon emissions can vary across different cities. This study delves into the shared factors influencing the performance of sustainable urbanization, introducing a Principal Component Analysis (PCA)-based evaluation system to gauge sustainable urbanization performance. Furthermore, we employ spatial regression analyses to explore the spatial differences in the impact of these factors on carbon emissions. Our investigation centers on data from nine cities in the Pearl River Delta, allowing for the ranking of these cities based on their sustainability performance. The outcomes reveal that the key factors influencing carbon emissions differ among cities due to variations in sustainable urbanization characteristics. Notably, our research integrates sustainable urbanization with the parameters of a low-carbon economy. In the realm of policymaking, we offer a quantifiable approach for assessing sustainable urbanization. Furthermore, we assert that cities at distinct stages of sustainable urbanization should prioritize different factors to attain carbon neutrality. Full article

In the digital and low-carbon economy context, climate policy uncertainty’s (CPU) influence on corporate technological innovation has attracted increasing attention. However, prior studies mainly focused on the negative cost effects or singular incentive impacts of CPU on corporate innovation, with limited exploration of its non-linear effects, especially in the new scenario of the integrated development of digital and low-carbon economies. This study fills this gap by using a comprehensive dataset of China’s A-share listed companies from 2007 to 2023 and employing a fixed-effects model. It investigates how CPU impacts corporate technological innovation through the lens of digital peer effects within the same industry and region. The findings reveal a dual “inverted U-shaped” effect of CPU on corporate innovation capabilities: moderate CPU stimulates innovation via increased government subsidies, while excessive uncertainty exacerbates financing constraints, inhibiting innovation. The present study also identifies the significant moderating role of digital peer effects in mitigating the negative impacts of CPU, enhancing innovation compensation, and bolstering firms’ climate risk resilience. Notably, state-owned enterprises and manufacturing firms demonstrate superior innovation capabilities and risk resistance. This study provides new insights into understanding CPU’s impact on corporate innovation and offers valuable references for policy formulation and corporate strategy development. Full article

Nigeria is among the countries highly vulnerable to climate change impact. Thus, there has been growing emphasis on the pursuit of decarbonization and net-zero (net-zero transition) strategies. The aim of this work is to review major concepts in research publications associated with climate change mitigation in Nigeria. The literature search was conducted on the Scopus database using relevant keyword operators. Mixed methods were adopted to conduct bibliometric, text mining and content analysis. Bibliometric software (VOSviewer) was used. The research objectives were to identify how net-zero transition research has evolved in Nigeria; their important research themes and trends in Nigeria, and potential directions for future research on achieving them in Nigeria. The results show that the number of publications in the field has been increasing, with 87% of the articles included in the dataset published between 2016 and 2024. Through data clustering, eight clusters of articles were identified, namely (i) the renewable energy, economic growth and emission reduction nexus (ii) energy transition in the Nigerian power system, (iii) policy drivers (socio-technical and economic) for a cleaner energy system, (iv) energy transition governance, (v) hybrid renewable energy systems, (vi) low-carbon transition, (vii) energy efficiency and low-carbon growth and others. By checking through the keywords used by authors, it appears that the most popular keywords are carbon neutrality, hydrogen, biomass, circular economy, and electric vehicles. These keywords further highlight areas of research interests. Some of the potential future directions identified include the need for effective research communication and strong cooperation between academia and relevant CC policy-making bodies to translate scientific research into evidence-based policies and actionable frameworks; tiered subsidies or tax rebates to low-income households to promote CC mitigating technologies and align CC objectives with social equity; and others. Although this work focuses solely on Nigeria, the country shares similar characteristics with many sub-Saharan African countries, and some others in the global South. Accordingly, the findings will be relevant to those areas, with some unique adaptations. Full article

As the world accelerates efforts to combat climate change and transition toward a green, low-carbon economy, the new energy vehicle (NEV) industry has become a key driver of carbon reduction. Its ability to innovate efficiently is critical to long-term sustainable development. This study builds on the innovation value chain theory and introduces an evaluation framework that accounts for undesirable outputs such as energy consumption and pollutant emissions. Using a super-efficiency network SBM–Malmquist model and Tobit regression, we analyze the technological innovation efficiency of 272 A-share listed NEV enterprises in China from 2016 to 2023. Expanding beyond traditional overall assessments, we examine efficiency at different stages of the industry chain and find that: (a) overall technological innovation efficiency has declined, mainly due to weak pure technical efficiency, underscoring the need for better R&D management and resource allocation; (b) efficiency varies across the industry chain, with midstream firms performing better than those upstream and downstream, reflecting differences in technological accumulation and market conditions; (c) R&D tax deductions and market competition significantly boost innovation efficiency by creating pressure-driven incentives, while mismatched labor skills, the “welfare dependence” effect of tax incentives and financing constraints hinder progress. By introducing a two-stage innovation efficiency evaluation framework, this study not only pinpoints where efficiency losses occur along the industry chain but also provides empirical insights to guide targeted policy decisions, offering valuable implications for the sustainable growth of the global NEV industry. Full article

Environmental accounting information disclosure is crucial for heavily polluting enterprises to strengthen environmental governance and realize sustainable development. However, some enterprises still suffer from weak disclosure awareness and low disclosure quality. Therefore, improving the quality of environmental accounting information disclosure in the digital era has become an urgent task to achieve China’s goal of a green and low-carbon economy. Using data from Shanghai and Shenzhen A-share listed companies in China’s polluting industries from 2013 to 2022, this study explores the impact and channels of influence of digital transformation and environmental accounting information disclosure. It has been found that digital transformation significantly impacts the quality of environmental accounting information disclosure. Further, based on the dual perspectives of internal empowerment and external monitoring, digital transformation improves environmental accounting information disclosure by promoting executive compensation incentives and enhancing analyst attention. Furthermore, the positive impact of digital transformation on environmental accounting information disclosure is more pronounced with the implementation of new environmental protection laws, high-quality audits and a high level of digital transformation, and non-state-owned enterprises. The findings provide theoretical support for the government to improve the environmental accounting information disclosure system and provide valuable policy insights to promote digitalization and green, low-carbon transformation paths for heavily polluting enterprises. Full article

From the perspective of the interlocking directorate network, investigating the impact of digital transformation network peer groups on corporate carbon neutrality performance holds substantial significance for enterprises in accomplishing green and low-carbon transformation within the digital economy framework. Using Shanghai and Shenzhen A-share listed companies from 2018 to 2023 as research samples, this study empirically explores the existence of a digital transformation peer effect within the interlocking directorate network and its influence on corporate carbon neutrality performance, as well as the moderating effect of the supply chain concentration. The results indicate the following: (1) A digital transformation peer effect exists within the interlocking directorate network and significantly improves the carbon neutrality performance of enterprises. (2) The aforementioned positive effect is more pronounced under lower supply chain concentrations. (3) The green innovation level of enterprises serves as an intermediary factor between the digital transformation network peer group and the carbon neutrality performance of enterprises. (4) In regions characterized by stringent environmental regulations, capital-intensive industries, and large-scale enterprises, the digital transformation network peer group exerts a more significant impact on the enhancement of carbon neutrality performance. These results offer a reference for facilitating the formation of digital transformation network peer groups, improving corporate carbon neutrality performance, and consequently attaining sustainable development. Full article