Search Results (201)

Improving the green innovation quality (GIQ) of center cities is crucial to achieve sustainable urban agglomeration development. Utilizing data on green patent citations and economic indicators across cities in the Yangtze River Delta urban agglomeration (YRD) from 2003 to 2022, this research examines the influence of center cities’ GIQ on the economic performance of peripheral municipalities. The results show the following: (1) Center cities’ GIQ exerts a significant suppressive effect on peripheral cities’ economic growth overall. Heterogeneity analysis uncovers a distance-dependent duality. GIQ stimulates growth in proximate cities (within 300 km) but suppresses it beyond this threshold. This spatial siphoning effect is notably amplified in national-level center cities. (2) Mechanisms suggest that GIQ accelerates the outflow of skilled labor in peripheral cities through factor agglomeration and industry transfer mechanisms. Concurrently, it impedes the gradient diffusion of urban services, collectively hindering peripheral development. (3) Increased government green attention (GGA) and industry–university–research cooperation (IURC) in centers can mitigate these negative impacts. This paper contributes to the theoretical discourse on center cities’ spatial externalities within agglomerations and offers empirical support and policy insights for the exertion of spillover effects of high-quality green innovation from center cities and the sustainable development of urban agglomeration. Full article

In this work, we examine the correlation between financial inclusion and the Environmental, Social, and Governance (ESG) factors of sustainable development with the assistance of an exhaustive panel dataset of 103 emerging and developing economies spanning 2011 to 2022. The “Account Age” variable, standing for financial inclusion, is the share of adults owning accounts with formal financial institutions or with the providers of mobile money services, inclusive of both conventional and digital entry points. Methodologically, the article follows an econometric approach with panel data regressions, supplemented by Two-Stage Least Squares (2SLS) with instrumental variables in order to control endogeneity biases. ESG-specific instruments like climate resilience indicators and digital penetration measures are utilized for the purpose of robustness. As a companion approach, the paper follows machine learning techniques, applying a set of algorithms either for regression or for clustering for the purpose of detecting non-linearities and discerning ESG-inclusion typologies for the sample of countries. Results reflect that financial inclusion is, in the Environmental pillar, significantly associated with contemporary sustainability activity such as consumption of green energy, extent of protected area, and value added by agriculture, while reliance on traditional agriculture, measured by land use and value added by agriculture, decreases inclusion. For the Social pillar, expenditure on education, internet, sanitation, and gender equity are prominent inclusion facilitators, while engagement with the informal labor market exhibits a suppressing function. For the Governance pillar, anti-corruption activity and patent filing activity are inclusive, while diminishing regulatory quality, possibly by way of digital governance gaps, has a negative correlation. Policy implications are substantial: the research suggests that development dividends from a multi-dimensional approach can be had through enhancing financial inclusion. Policies that intersect financial access with upgrading the environment, social expenditure, and institutional reconstitution can simultaneously support sustainability targets. These are the most applicable lessons for the policy-makers and development professionals concerned with the attainment of the SDGs, specifically over the regions of the Global South, where the trinity of climate resilience, social fairness, and institutional renovation most significantly manifests. Full article

The tequila industry generates significant quantities of vinasse, a highly polluting byproduct that poses serious environmental challenges. Addressing this issue requires innovative solutions that align with the principles of bioeconomy, transforming waste into valuable resources. This article provides a comprehensive review of 688 scientific articles and 315 patent documents related to vinasse valorization technologies, retrieved from the Scopus and Espacenet databases. The review identifies key types of vinasse valorization, including bioethanol, biofertilizers, biogas, animal feed, biodiesel, and phenolic compounds, and evaluates trends, technical advances, and commercialization pathways. The findings highlight the feasibility of integrating these technologies within the tequila production process, promoting environmental sustainability and economic efficiency, and mention the current limitations of vinasse-based innovations. This study aims to guide researchers, industry stakeholders, and policymakers in developing strategies to harness the full potential of vinasse, contributing to a more sustainable and circular economy. Full article

Under the impetus of the global urbanization, the synergistic relationship between smart city policies and green innovation capabilities has emerged as a critical agenda for achieving sustainable development goals. While existing studies have explored the techno-economic effects of smart cities, systematic evidence remains scarce regarding their pathways and heterogeneous impacts on green growth. This study investigates the influence of smart city pilot policies on urban green growth trajectories and their heterogeneous characteristics. Leveraging panel data from 293 Chinese prefecture-level cities, we employ a multi-period difference-in-differences (DID) model with two-way fixed effects to control for unobserved city-specific and time-specific factors, complemented by robustness checks including parallel trend tests, placebo tests, and alternative dependent variable specifications. Data sources encompass the China City Statistical Yearbook, CNRDS, and CSMAR databases, covering core metrics such as green patent applications and grants, industrial upgrading indices, and environmental regulation intensity, with missing values being addressed via mean imputation. The findings demonstrate that smart city pilot policies significantly enhance green innovation levels in treated cities, with effects exhibiting pronounced spatial and resource-based heterogeneity; there are notably stronger impacts in non-resource-dependent cities and eastern regions. Mechanism analysis shows that policies are driven by a dual effect of industrial upgrading and environmental regulation. The former is manifested by the high substitution elasticity of the digital economy for traditional manufacturing, while the latter is reflected in the rising compliance costs of polluting enterprises. This research advances a cross-nationally comparable theoretical framework for understanding green transition mechanisms in smart city development while providing empirical benchmarks for policy design in emerging economies. Full article

This study analyses the impact of agricultural greenwashing on financial performance via green innovation. To this end, it employs data from Chinese A-share agribusinesses from 2012 to 2022. The study indicates the following results: (1) the practice of greenwashing (ESG disclosure–performance gap, GW) has a significant negative impact on ROA, particularly in non-state firms; (2) green innovation (patents, GI) partially mediates this relationship, with a percentage of 9.09%, as GW diverts research and development resources toward image management. Robustness checks are employed to confirm the results obtained using ROE and lagged models. Property rights moderate the effects: non-state firms are more adversely affected by innovation dependency, while state firms are protected by policies. The “double-edged” mechanism elucidates GW’s short-term legitimacy gains in contrast to long-term innovation suppression and financial decline. The report calls for the establishment of standardised ESG metrics (for example, the disclosure of pesticide residue) and targeted green incentives (for example, SME R&D subsidies) to be aligned with UN SDGs 9.4 (green tech) and 12.6 (responsible production). The present study offers insights into the governance of environmental, social, and governance (ESG) matters within the context of agriculture in China. Full article

This work aims to use a suitable regression model to study a count response random variable, namely, the number of citations of a research paper, that is affected by some explanatory variables. The count variable exhibits substantial variation, as the sample variance is larger than the sample mean; thus, the classical Poisson regression model seems not to be appropriate. We concentrate our attention on the negative binomial regression model, which allows the variance of each measurement to be a function of its predicted value. Nevertheless, the process of citations of papers may be divided into two parts. In the first stage, the paper has no citations, while the second part provides the intensity of the citations. A hurdle model for separating documents with citations and those without citations is considered. The dataset for empirical application consisted of 43,190 research papers in the Economics and Business field from 2014–2021, which were obtained from The Lens database. Citation counts and social attention scores for each article were gathered from the Altmetric database. The main findings indicate that both collaboration and funding have positive impacts on citation counts and reduce the likelihood of receiving zero citations. Open access (OA) via repositories (green OA) correlates with higher citation counts and a lower probability of zero citations. In contrast, OA via the publisher’s website without an explicit open license (bronze OA) is associated with higher citation counts but also with a higher probability of zero citations. In addition, open access in subscription-based journals (hybrid OA) increases citation counts, although the effect is modest. There are clear disciplinary differences, with the prestige of the journal playing a significant role in citation counts. Articles with lower expert ratings tend to be cited less frequently and are more likely to be cited zero times. Meanwhile, news and blog mentions boost citations and reduce the likelihood of receiving no citations, while policy mentions also enhance citation counts and significantly lower the risk of being cited zero times. In contrast, patent mentions have a negative impact on citations. The influence of social media varies: X/Twitter and Wikipedia mentions increase citations and reduce the likelihood of being uncited, whereas Facebook and video mentions negatively impact citation counts. Full article

Environmental impacts, such as elevated temperatures due to urban heat islands (UHIs), associated with land cover change due to urbanization, should not be ignored. In contrast to conventional impermeable concrete, permeable pavements have been implemented as green infrastructure strategies for achieving environmental benefits, such as stormwater management. Their impacts and benefits on other environmental aspects should not be ignored, especially for those with limited discussion in the literature. Therefore, this study monitored the surface and air temperatures of three types of pavements: conventional impermeable concrete (IC), pervious concrete (PC), and the patented JW Eco-technology (JW). As UHIs are more intense in the summer, temperature profiles during targeted periods when surface temperatures exceeded 40 °C for consecutive days were examined. In addition, as an available option at the study site, shade was created to evaluate its effect on surface temperatures across the pavement systems. Overall, the annual average surface and air temperatures of the three pavements were similar. However, seasonal and diurnal variations in temperatures were both observed, suggesting summer was the season when the differences in temperatures among pavements were most noticeable. Investigation during the targeted periods revealed that the average surface temperatures of PC were 2.4–2.7 °C and 3.2–3.3 °C higher than those observed on IC and JW, and the average air temperature of PC was 1.8 °C greater than that of IC and JW between 12:00 and 16:00. On the contrary, the average surface temperatures of PC were significantly lower than those on IC (1.3–1.4 °C) and JW (1.5 °C) between 21:00 and 5:00. Results also indicate that shade was an effective way to alleviate the high surface temperatures during the warm hours by lowering surface temperatures 21.0 °C, 15.4 °C, and 15.0 °C, for PC, IC, and JW, respectively. Finally, temperatures associated with the aqueducts of JW Eco-technology and the impacts on overall surface temperatures will be discussed. Full article

New-quality productivity and industrial structure upgrading has become a primary area of concern with respect to regional economic transformation and sustainable development. Based on static panel data of 108 prefecture-level-and-above cities in the Yangtze River Economic Belt from 2013 to 2022, the projection pursuit model, coupling coordination degree model, and obstacle degree model were used to study the spatiotemporal patterns and key obstacle factors in the coupling of new-quality productivity and levels of industrial upgrading. Results show the following: (1) The average coupling coordination degree increased from 0.42 in 2013 to 0.53 in 2022, exhibiting a three-stage trend of “initial advancement, rapid growth, and high-level fluctuation”. (2) Regionally, a gradient pattern of “downstream leading, midstream following, and upstream catching up” persists, but regional gaps have narrowed significantly. (3) Spatially, the coupling coordination level shows a pattern of “high in the east, low in the west, led by the core, and breakthrough in the local area”, with significant positive aggregation characteristics. (4) The main obstacle factors across the entire area include digital patents (7.03%), green patents (7.03%), and the number of high-tech enterprises (6.96%), but the weights of the obstacle factors vary greatly across different areas. These findings provide scientific support for green transformation, regional integration, and sustainability-oriented industrial policy design in the Yangtze River Economic Belt. Full article

Patent licensing is essential for sustainable technological diffusion, fostering innovation and strengthening industrial resilience. However, the determinants influencing patent licensing decisions remain underexplored. This study investigates these factors at both the enterprise and patent levels, emphasizing their role in promoting sustainable industrial innovation and knowledge transfer. Given the low proportion of licensed patents, this research proposes a measurement framework to identify thematically similar but unlicensed patents and applies a conditional logistic regression model to analyze the factors affecting licensing decisions. Using patent abstracts from the intelligent connected vehicles (ICVs) sector, topic modeling is conducted to classify technological themes, and Kullback–Leibler divergence is applied to measure differences between licensed and unlicensed patents. The results indicate that technological prestige and depth negatively influence licensing, whereas technological breadth, advancement, and stability have a positive effect. From a sustainability perspective, enterprises should optimize technology management to support responsible knowledge transfer and green innovation. Universities should enhance patent quality and innovation impact to contribute more effectively to sustainable development. Policymakers should refine patent licensing frameworks to foster an efficient, inclusive, and sustainable intellectual property ecosystem, thereby facilitating cross-sectoral technology diffusion, advancing eco-friendly industrial transformation, and promoting sustainable economic growth. Full article

The energy transition is not only a technological or market-driven process but also a discursive and institutional challenge. While conventional research emphasizes financial incentives and regulatory frameworks, the role of policy narrative intensity in shaping renewable energy innovation has received limited empirical attention. This study addresses this gap by analyzing 8837 provincial-level policy documents (2005–2023) from 31 regions across China. We construct a policy narrative intensity index using the PMC framework to systematically assess how institutional discourse influences the direction and intensity of renewable energy development. The results reveal that a 1% increase in policy narrative intensity corresponds to a 4.60% rise in renewable energy innovation, as measured by renewable electricity generation, with robustness confirmed through IV and IHS methods. Regional heterogeneity is also evident: executive-led regions such as Jiangxi, Shandong, and Fujian exhibit higher narrative strength and stronger renewable energy outcomes, while market-driven provinces like Shanghai and Guangdong show weaker narrative alignment. Mechanism testing demonstrates that policy narratives enhance renewable energy innovation by (1) strengthening environmental regulation enforcement (β = 0.37), (2) increasing green patent activity by 23.6%, and (3) raising public adoption of renewable energy by 17.2 percentage points. This study highlights the governing value of policy narratives as institutional public goods and reveals their crucial role in aligning administrative capacity, corporate innovation, and public engagement to drive energy transition. These insights contribute to the broader discourse on SDG7/SDG13-aligned sustainability governance. Full article

Amid the accelerating global transition toward a low-carbon economy, collaborative innovation within the new energy vehicle industry has emerged as a critical mechanism for advancing green technology diffusion and fostering industrial ecosystem sustainability. This study explores the evolutionary features of the cooperative network and the ways in which network embedding influences innovation performance by analyzing 2808 patents pertaining to battery technologies for new energy vehicles (NEVs) in China, which adopted the network embedding theory. The results show that (l) the innovation performance within China’s NEV battery technology innovation cooperation network exhibits significant variation, the industry is undergoing accelerated stratification, and a trend towards head concentration is evident; (2) network size amplifies the beneficial influence of structural holes and centrality on innovation performance; and (3) the mediating role of external knowledge search between network embeddedness and innovation performance is negatively moderated by relationship intensity. By extending the social network theory to the field of new energy vehicle batteries, this study reveals the special law of network embedding in the technology-intensive industry, elucidates the mediating mechanism of external knowledge search, and innovatively proposes the “innovation paradox” of relationship strength, confirming the innovation advantage of weak relationship cross-border reorganization in this field. Full article

This study investigates the long-run impact of digital transformation and fintech innovation on environmental sustainability across OECD countries from 1999 to 2024. Drawing on a novel empirical framework that integrates panel fully modified ordinary least squares, the system-generalized method of moments, and machine learning estimators, the analysis captures both linear and nonlinear dynamics while addressing heterogeneity, endogeneity, and structural complexity. Environmental sustainability is measured by per capita CO₂ emissions, while digital transformation and fintech innovation are proxied by secure internet servers and G06Q patent applications, respectively. The findings reveal that both digital infrastructure maturity and fintech-driven innovation significantly reduce carbon emissions, suggesting that technologically advanced digital ecosystems serve as effective instruments for climate mitigation. Robustness checks via the system-generalized method of moments confirm the stability of these relationships, while machine learning models—Random Forest and XGBoost—highlight digital variables as top predictors of emissions reduction. The convergence of results across estimation methods underscores the reliability of the digital–environmental nexus. Policy implications emphasize the need to embed sustainability metrics into digital strategies, promote green fintech regulation, and prepare labor markets for Industry 4.0 transitions. These findings position digital and fintech innovation not merely as enablers of economic growth, but as structural levers for achieving environmentally sustainable development in high-income economies. Full article

The Industry–Finance Collaboration Pilot (IFCP) integrates governmental green guidance with digital collaboration platforms to promote non-equity-based cooperation between industrial and financial sectors. Using a Difference-in-Differences (DID) approach and a sample of A-share listed industrial firms on the Shanghai and Shenzhen Stock Exchanges from 2011 to 2023, this study examines the IFCP’s impact on corporate green innovation (GI). Results show that the IFCP increases the number of green patent applications by 7.5% on average, indicating its effect in stimulating GI. This effect operates through two main mechanisms. First, under governmental green guidance, the IFCP encourages local green fiscal subsidies, increases green investor participation, improves environmental information disclosure, and lowers agency costs. Second, through digital finance empowerment, it mitigates information asymmetry and transaction costs in financial activities, thereby reducing credit costs and enhancing firms’ access to green credit. The effect of the IFCP on GI is more pronounced in regions with stricter environmental regulation, in pollution-intensive industries, and among firms with smaller asset sizes. Further analysis indicates that the IFCP primarily stimulates tactical, low-value GI driven by compliance or opportunistic motives, rather than promoting substantive, high-quality innovation. This study provides empirical evidence and policy insights into how governmental green guidance and digital finance empowerment can jointly promote green industrial development. Full article

This study focuses on the intrinsic mechanisms and sustainable value of artificial intelligence (AI)-driven green collaborative innovation in enterprises amid the global green low-carbon transition, revealing new pathways for digital technology-enabled green development. Based on the data of China’s A-share listed companies jointly applying for green patents with other entities from 2010 to 2023, this study used a high-dimensional fixed effect model to empirically find that artificial intelligence significantly promotes green collaborative innovation. This promoting effect proved more pronounced in the case of high macroeconomic uncertainty, large enterprises and SOEs. A mechanism test revealed that artificial intelligence drives green collaborative innovation primarily by reducing transaction costs and optimizing the labor structure. A moderating effect analysis showed that green investor entry and CEO openness can strengthen the facilitating effect of artificial intelligence on green collaborative innovation. In addition, the facilitating effect of artificial intelligence on green collaborative innovation helps companies reduce carbon emissions and improve ESG performance, driving the transformation of business ecosystems toward environmental sustainability. From a technology–organization–environment co-evolution perspective, this research clarifies the micro-level operational chain of AI-enabled green innovation, providing theoretical support for developing countries to achieve leapfrog low-carbon transitions through digital technologies. Practically, it offers actionable insights for advancing AI-enabled green industries, constructing collaborative green innovation ecosystems, and supporting the realization of the United Nations Sustainable Development Goals (SDGs). Full article

As global digital transformation accelerates alongside the “dual carbon” goal, understanding how the digital economy can drive the green transformation of traditional energy systems is critical to overcoming resource and environmental constraints. This study examines the impact of digital economy attention on Green Total Factor Energy Efficiency (GTFEE) using panel data from 275 Chinese prefecture-level cities between 2011 and 2022. Three main findings emerged. First, an increase in attention to the digital economy significantly enhances GTFEE, serving as a key driver of improved energy efficiency. Specifically, a one-standard-deviation increase in attention raises GTFEE by 0.276 standard deviations. Second, this effect operates through two pathways: (1) digital technology advancements, such as higher internet penetration; (2) human capital accumulation, reflected in a greater college student ratio; and (3) green innovation, measured by a rise in green patents. Third, regional heterogeneity is evident, with stronger positive effects in eastern and coastal cities, while high-carbon-intensity regions exhibit a suppressed impact. These results underscore the importance of public engagement in digitalization to optimize energy systems. Policymakers should adopt region-specific strategies, such as boosting digital infrastructure in low-carbon areas and supporting structural reforms in high-carbon regions. This study expands our understanding of the digital economy’s role in enhancing energy efficiency and offers policy guidance for the green energy transition. Full article