Urban regions in China are presently confronting a significant challenge with the “carbon lock-in” phenomenon, which poses a substantial barrier to achieving the “Dual-Carbon Commitment” and advancing sustainable economic practices. To address this challenge, the strategic application of biased technological progress may offer a viable solution for alleviating the constraints of carbon lock-in. This research utilizes panel data from 282 Chinese cities covering the period from 2006 to 2019, employing an indicator system grounded in the entropy weight approach to evaluate the extent of urban carbon lock-in. It then conducts asymmetric analysis, mechanism validation, and heterogeneity analysis to empirically examine the mechanisms relating to biased technological progress influencing carbon lock-in from various angles. The findings show that biased technological progress significantly alleviates China’s carbon lock-in woes. On average, the carbon lock-in index drops by 0.028

With the rapid diffusion of industrial robots due to the aging of the global population, their implications for carbon emissions have increasingly become salient. Using a comprehensive industry-level dataset covering manufacturing sectors in 40 countries, this study provides novel empirical evidence on the impact of robot adoption on industrial carbon emission intensity. Results show that robot adoption significantly reduces carbon emission intensity in manufacturing industries. This finding remains robust after several robustness checks, including the estimation of instrumental variables and alternative measures of robot adoption. Mechanism analyses reveal that the carbon-reducing effect of robot adoption primarily operates through improvements in total factor productivity. Furthermore, a significant ripple effect is identified, whereby robot adoption in upstream industries amplifies downstream carbon emission reductions through interindustry linkages. From a policy perspective, these results underscore the relevance of promoting productivity-enhancing robot adoption and leveraging supply-chain interactions to support global low-carbon economic development.

Promoting the transition toward green and low-carbon lifestyles is essential for advancing sustainable consumption and environmental sustainability. Based on 6903 valid survey responses from 19 digital household pilot regions in China, this study examines the relationship between household digitalization and green and low-carbon lifestyles. A household digitalization level (HDL) index is constructed using the entropy method across five dimensions: digital network services, digital infrastructure, digital literacy, digital skills, and digital applications. The empirical results show that higher HDL is positively associated with the adoption of green and low-carbon lifestyles, and this association remains robust across a series of sensitivity analyses. Exploratory mechanism analysis indicates that HDL is linked to green and low-carbon lifestyles through improved satisfaction with digital smart technologies and enhanced environmental awareness. Heterogeneity analysis shows that this association is stronger among larger households, urban and suburban households, and households with development-oriented consumption, but weaker among smaller, rural, and subsistence-oriented households. These findings provide micro-level evidence supporting the exploration of the linkage between household digitalization and sustainable household consumption and the coordinated development of digitalization and environmental sustainability.

This study investigates the role of Corporate Social Responsibility (CSR) in shaping employee perspectives towards green initiatives and its consequent impact on environmental sustainability within the Congolese cobalt sector. The research is based on cross-sectional data analysis, with survey questionnaires administered to 398 employees across various mining companies. The study reveals a positive relationship between an employee’s mindset towards CSR and green initiatives, which subsequently leads to improved environmental sustainability outcomes. Furthermore, the research demonstrates that CSR measures moderate this relationship: when CSR practices are strong and visible (clear environmental policies, training, incentives, and resource support), they provide direction and support that strengthen the effect of employee mindset on green initiatives while when CSR practices are weak, the same mindset is less likely to lead to green initiatives. The findings offer valuable theoretical and managerial implications, particularly for organizations in sectors with considerable environmental impacts. The study reveals the necessity of aligning CSR strategies with both corporate objectives and employee attitudes to optimize their effectiveness. The study provides a robust model for future research and practical implementation.

The Kyoto Protocol and Paris Agreement have anchored global efforts to reduce greenhouse gas (GHG) emissions and achieve climate neutrality. Yet, despite growing momentum, these frameworks reveal a persistent challenge: advancing environmental goals without exacerbating social and economic disparities. As climate policy enters a critical phase, integrating equity into climate action, especially within the broader scope of the Sustainable Development Goals (SDGs), has become imperative. Against this backdrop, this study explores the roles of green taxation and energy justice in reducing GHG emissions, focusing on carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Using panel data from 38 OECD countries between 1990 and 2023, we employ robust econometric techniques including Generalized Method of Moments and Two-Stage Least Squares (2SLS) to assess policy impacts. Our findings indicate that green taxes significantly reduce emissions, confirming their utility as fiscal tools for climate mitigation. Energy justice, defined as equitable access to clean, affordable energy, not only contributes directly to emission reductions but also amplifies the effectiveness of green taxation. This interaction reveals a powerful synergy, demonstrating that fiscal and justice-based policies can work in tandem to support sustainable outcomes. We also observe substantial heterogeneity shaped by regional, institutional, and policy-specific factors. These results underscore the need for context-sensitive and integrated strategies that align environmental and social objectives. Ultimately, this research presents a dynamic policy framework that supports both climate neutrality and the SDG agenda, offering critical insights for designing equitable, high-impact climate interventions.

Environmental contamination has grown to be a major issue for policymakers in recent years. This proposed study fills this void by presenting an empirical analysis that considers the effects of different green (hydropower, geothermal, solar, nuclear, and wind energy) and non-green (coal, oil, and gas) energy productions on ecological and carbon footprints. Fully Modified Ordinary Least Square is used to estimate the long-term associations among selected variables in the top ten nations that export electricity with data spanning 1990 to 2021. The findings demonstrate that geothermal and hydro energy production is expanding, which has raised ecological and carbon footprints. Additionally, it is discovered that the rise in energy production from nuclear, solar, and wind resources decreased the ecological and carbon footprints. In contrast, results show that oil production minimized environmental deterioration while coal and gas production increased it. This research also discovered that research and development (R D) negatively correlated with ecological and carbon footprints within economies. These findings hold significant policy implications, particularly for nations aiming to modernize their green energy sectors. Promoting environmentally sustainable geothermal and hydropower technologies, alongside increased investment in R D, emerges as a strategic pathway toward sustainable development.

Corporate sustainability is becoming increasingly vital as companies face mounting pressure from investors, regulators, and stakeholders to incorporate environmental, social, and governance (ESG) principles into corporate strategies. However, the impact of ESG ratings on corporate financial performance (CFP) remains unclear, particularly in emerging markets. This study examines this relationship using a sample of 8,921 firm-year observations from firms listed on the Johannesburg Stock Exchange, employing a two-way fixed-effects panel model to control for firm-specific and time-invariant factors. The findings show a positive relationship between ESG ratings and financial performance, mediated by operational efficiency and corporate debt. Firms with higher ESG ratings demonstrate improved resource utilization, process optimization, and workforce productivity while benefiting from decreased borrowing costs due to improved creditworthiness, risk perception, and transparency. Furthermore, the findings show that larger firms, non-state-owned enterprises, high-pollution industries, and those operating under stringent environmental regulations benefit the most from ESG ratings, underscoring significant heterogeneity across firms and industries. These findings underscore the economic benefits of ESG adoption beyond regulatory compliance and provide critical insights for corporate executives, investors, and policymakers. This study emphasizes the importance of structured ESG frameworks and standardized reporting to curb greenwashing and improve corporate transparency and financial stability in emerging markets.

This research adopts a parametric technique to estimate energy efficiency under heterogeneous production technologies and addresses concerns related to latent country-specific heterogeneity while decomposing energy efficiency into persistent (long-term) and transient (short-term) components. The dataset, spanning from 1995 to 2019 and encompassing a global panel of 126 countries, reveals an optimal model with four Classes, where Classes 1 and 2 are characterized by developing economies, while Classes 3 and 4 comprise developed and emerging upper-income countries. According to the energy demand frontier, income, economic structure, price, population, and urban development all have a substantial impact on energy use, with some evidence of heterogeneity between classes. Under homogeneous technology, global average energy efficiency is 29.6%, revealing a sizable 70.4% untapped efficiency potential for improvement. While the mean transient energy efficiency is high at 91%, persistent energy efficiency is relatively low at 32.7%, pointing to the structural nature of energy inefficiency with long-term consequences. However, when accounting for heterogeneity in production technologies, the average estimated energy efficiency values varied among the four Classes. Specifically, around 84%, 83%, 59%, and 42% of untapped energy efficiency potential were identified in Classes 1, 2, 3, and 4, respectively. Similarly, persistent energy inefficiency was evident in all cases, underscoring the need for longterm-oriented government or regional energy policies to address and improve overall energy efficiency.

This research study conducts a thorough review of the agritourism research literature. The study used a structured literature review process to identify established and emerging research clusters for epistemological analysis. Using a structured literature review process, the study identified established and emergent research clusters for epistemological analysis. This research study carry out a comprehensive evaluation of the agritourism research literature. Research clusters that are both established and new were identified for epistemological examination in the study, which used a structured literature review process. In the study, established and emergent research clusters have been found for epistemological analysis utilizing a systematic literature review method. Such analysis aids in identifying the main research topics, interrelations, and collaboration patterns in the study area of agritourism and other fields of study incorporating related themes. Using visualization of commonalities, the agritourism research field is graphically mapped (VOSviews). VOS software examined the bibliographic information in 352 research publications using data extracted from Web of Science databases from a period of 2000 and 2024. This graphical mapping illustrated the authors’ and countries’ contributions, their collaboration, and publication pattern over the period. In addition, this paper gives insights about majorly studied research themes, identified common areas of current research interest and also potential directions for future research.

The energy crisis, resource depletion, competition, and waste reduction challenges have pushed organizations to embrace sustainable practices. Green Lean Six Sigma adoption (GLSA) is crucial for sustainability. However, various factors impact GLSA, including driving forces (DFs), barriers, and enablers. This study aims to analyze and model how these factors affect GLSA by collecting data from 207 respondents and using Partial Least Square Structural Equation Modeling (PLS-SEM). The findings reveal that government-related barriers have a significant negative impact on GLSA. In contrast, industry, cost, and energy-related DFs, government policies/legislation, and capability/capacity-related enablers have a positive effect. Based on the findings, an adoption strategy for Green Lean Six Sigma is proposed. These insights are valuable for managers and policymakers struggling to promote GLS in the construction industry. This study contributes to the GLS literature by analyzing the quantitative influence of barriers, DFs, and enablers on GLSA and suggesting an adoption strategy. This study highlights the need for targeted government policies and industry initiatives to overcome barriers and leverage enablers for successful GLSA implementation in construction projects, thereby enhancing sustainability and operational efficiency.

Geographic distance between underwriters and bond issuers, an objective constraint on companies' access to underwriters in corporate bond financing, influences capital liquidity. Using Chinese credit bonds issued between 2010 and 2022, this paper examines the mechanism through which the geographical distance between underwriters and bond issuers affects bond financing costs (BFCs). The findings indicate that greater geographic distance leads to higher financing costs. This conclusion is robust even after endogeneity concerns are addressed and robustness checks are performed. Moderating effect analysis indicates that underwriters' digital transformation, reputation, and regional marketisation level weaken this effect. The heterogeneity analysis further indicates that the distance premium is more pronounced for bonds underwritten by non-local institutions, those with lower credit ratings, and issuers exhibiting subpar ESG performance. This conclusion enriches theoretical research on the impact of geographic distance on financial markets and provides targeted policy implications for participants and regulators in China's bond market.

This study investigates the impact of the digital economy on energy efficiency through a combination of theoretical analysis and empirical testing. The research contributes by categorizing the energy value creation process into two stages: the energy input stage and the energy operation stage and by examining both the direct and indirect effects of the digital economy on energy efficiency. Indirect effects are explored through factors such as industrial structure, green innovation, transaction efficiency, and environmental regulation. Using panel data from 41 cities in the Yangtze River Delta region of China, covering the period from 2006 to 2020, the study empirically examines the effects of the digital economy on energy efficiency. The findings emphasize the significant role of the digital economy in enhancing energy efficiency, particularly through upgrading industrial structures, increasing transaction efficiency, and stimulating green innovation. A heterogeneity analysis reveals that the influence of the digital economy on energy efficiency is less pronounced in resource-based cities than in non-resource-based cities. Based on these findings, the study provides targeted policy recommendations to further leverage the digital economy for improving energy efficiency.

This study explored the impact of environmental regulation on green technology innovation (GTI) of listed Chinese companies from 2007 to 2019. The findings revealed that, first, the command and control regulations positively affected GTI through the operating costs. Second, R&D mediated the relationship between the environmental subsidies under market-based incentive regulations and the GTI. Third, informal regulations of news media reports have significantly promoted GTI in energy-intensive enterprises. This promotional effect was found through the mediating variables of financing constraints. Fourth, we also have found that environmental subsidies were the most important incentive policies for promoting GTI. We have conducted a verification of both the weak and strong of the Porter hypothesis. Based on these results, management policies have been suggested.

Macroeconomic uncertainties—such as political risk and economic policy instability—have been widely examined in relation to energy transition, security, and environmental performance. However, their impact on energy efficiency remains underexplored. A key question emerges: do geopolitical risks impede energy efficiency or do they compel governments to enhance efficiency and reduce import dependence? This paradox calls for empirical investigation. While recent studies suggest that geopolitical threats may still improve energy efficiency in Europe due to their advanced infrastructure and technological capacity, it is unclear whether these findings hold globally and how outcomes differ across income groups. To address this gap, we employ a news-based geopolitical risk index and endogenous stochastic frontier analysis (SFA) to provide a comprehensive global assessment across income levels and time periods for 1985–2022. The results show that geopolitical risks significantly increase global energy inefficiency, with low-income countries most severely affected. However, evidence indicates that, over time, countries may adapt by improving efficiency and diversifying energy sources. Counterfactual scenarios analysis further demonstrates that reducing geopolitical risks could lower global energy inefficiency by at least 13%. These findings highlight the importance of policies that both mitigate geopolitical risks and strengthen the resilience of energy systems worldwide. Graphical abstract

This paper considers environment management in a new context. In the e-waste recycling industry, most e-waste is irresponsibly recycled and disposed of by informal enterprises, causing serious secondary pollution. Cooperation between emerging online recyclers and offline formal disposing enterprises can help reduce secondary pollution and improve the efficiency of resource reuse to achieve co-benefits, but they operate at a cost disadvantage compared with informal enterprises, which results in a weak motivation for cooperation. Reasonable government regulations are critical to the cooperation between these two types of enterprises. Existing research lacks attention to this. We develop evolutionary game models under a market mechanism and under government regulation to study the influence of multiple factors, including the impact of the prospective loss on the strategies evolution of the game players. We also analyze the effect of government regulation when the market mechanism fails. The results show that: (1) there is a threshold for the ratio of cooperation costs to the excess benefits obtained from cooperation (i.e., between 0.31 and 0.35). When the ratio is greater than the threshold value, the market mechanism fails, and the enterprises' behavior evolves towards non-cooperation. (2) Compared with earnings, enterprises are more sensitive to the prospective loss. Therefore, the government should provide subsidies that help reduce the cost for enterprises to cooperate, and penalize enterprises failing to cooperate. (3) There is a threshold effect in government subsidies and penalties (thresholds between 0.25 and 0.3 and 0.3–0.4, respectively). Only when exceeding the threshold, can they be effective. However, excessive subsidies and penalties also have limitations, and moderate subsidies and penalties can effectively promote the cooperation between the two types of enterprises. Our findings clarify the conditions under which the government can promote online and offline cooperation on e-waste recycling. These insights can also offer a reference for other countries and industries facing similar challenges.

The Congolese cobalt industry is pivotal to the global mineral economy, yet it faces mounting sustainability challenges amid increasing demand. This study addresses a critical research gap by investigating the role of Managerial Green Commitment (MGC) in enhancing Sustainable Supply Chain Performance (SSCP). Utilizing Structural Equation Modeling (SEM) and data from 159 managers, we explore the mediating roles of Supply Chain Management Practices (SCMP) and Information Systems (IS). The findings show that MGC significantly enhances SSCP both directly (β = 0.53, p < 0.01) and indirectly through SCMP (β = 0.46, p < 0.05) and IS (β = 0.42, p < 0.05). Specifically, the results show that effective supply chain management practices (β = 0.61, p < 0.01) and the integration of advanced information systems (β = 0.60, p < 0.01) are crucial for leveraging managerial green commitment to achieve sustainable performance. The study offers actionable insights for industry leaders and policymakers, highlighting the necessity of integrating green initiatives at the organizational level to achieve sustainable performance in the cobalt supply chain. These insights are crucial for strategic planning and policy formulation to improve sustainability in the mineral industries.

With financial liberalization and economic globalization, international trade balance has become an important channel to increase a country's fiscal revenue. To facilitate global trade, exchange rate markets are an indispensable means of currency circulation, and research on volatility is also a hot topic worldwide. To reveal the impact of different types of macroeconomic fundamentals on foreign exchange market volatility, this study uses eight fundamental indicators for macroeconomic attention indices (MAIs) proposed by Fisher et al. (2022) to explore their impact on the volatility of the yen/dollar rate while considering the asymmetric case of short-term volatility. The results show that the dynamics of the MAIs affect yen/dollar rate volatility, with almost all the MAIs having significantly positive coefficients. The results of the MCS test confirm that considering both asymmetric effects and MAI information improves the predictive accuracy of the model. This result is robust to alternative tests, alternative sample lengths, and alternative MAI indicators. Overall, the empirical results highlight the value of incorporating asymmetric effects and MAI indicators in forecasting yen/dollar rate volatility. This finding is of self-evident importance for promoting the balance of payments, regulating currency flows, and developing a country's economy.

A green building (GB) is a design idea that integrates environmentally conscious technology and sustainable procedures throughout the building’s life cycle. However, because different green requirements and performances are integrated into the building design, the GB design procedure typically takes longer than conventional structures. Machine learning (ML) and other advanced artificial intelligence (AI), such as DL techniques, are frequently utilized to assist designers in completing their work more quickly and precisely. Therefore, this study aims to develop a GB design predictive model utilizing ML and DL techniques to optimize resource consumption, improve occupant comfort, and lessen the environmental effect of the built environment of the GB design process. A dataset ASHARE-884 is applied to the suggested models. An Exploratory Data Analysis (EDA) is applied, which involves cleaning, sorting, and converting the category data into numerical values utilizing label encoding. In data preprocessing, the Z-Score normalization technique is applied to normalize the data. After data analysis and preprocessing, preprocessed data is used as input for Machine learning (ML) such as RF, DT, and Extreme GB, and Stacking and Deep Learning (DL) such as GNN, LSTM, and RNN techniques for green building design to enhance environmental sustainability by addressing different criteria of the GB design process. The performance of the proposed models is assessed using different evaluation metrics such as accuracy, precision, recall and F1-score. The experiment results indicate that the proposed GNN and LSTM models function more accurately and efficiently than conventional DL techniques for environmental sustainability in green buildings.

This study explores the dynamic relationship between industrial pollution and urban economic development in the Yangtze River Delta urban agglomeration based on the EKC hypothesis. In this paper, we use a panel dataset covering 27 cities in the Yangtze River Delta from 2006 to 2019 for the analysis, group the samples by a panel threshold model, and use a fixed-effects model for EKC estimation. The result shows that the EKC forms in different regions of the Yangtze River Delta are all N-shaped, and most cities are between two inflection points. The relationship is developing for the better in the short term, but the situation is not optimistic in the long term. The current industrial transformation has not been fully effective, and the development of industries still increases environmental pollution. The level of foreign investment will reduce pollution emissions. The effectiveness of environmental regulation is related to the city’s development stage and has not been fully highlighted in the Yangtze River Delta. Based on the findings, this study concludes that environmental improvement should be used as an essential channel for sustainable urban development to enhance economic innovation and competitiveness. Meanwhile, it is necessary to promote industrial structure upgrading further, actively introduce foreign investment, strengthen regulation, and establish a two-way interaction mechanism between cities to increase R D expenditures for eco-friendly industrial operations.