Search Results (12,919)

Fintech has become an important driver of digital transformation and sustainable development in the banking industry. However, existing studies report inconsistent findings regarding the relationship between fintech and bank financial performance. This study examines the impact of fintech adoption on the financial performance of Chinese listed commercial banks and investigates the mediating roles of green finance and ESG performance, as well as the moderating role of ownership status. Using panel data from 42 Chinese A-share-listed commercial banks between 2015 and 2024, this study employs panel regression analysis to evaluate the direct, mediating, and moderating relationships among the variables. The results indicate that fintech significantly improves market valuation, operational profitability, and asset utilisation efficiency in Chinese listed commercial banks. In addition, green finance and ESG performance partially mediate the relationship between fintech and financial performance, suggesting that fintech contributes to sustainable financial value creation through sustainability-oriented mechanisms. The findings further show that ownership status significantly moderates the fintech–financial performance relationship, with fintech generating stronger positive effects among non-state-owned banks than state-owned banks. Furthermore, the instrumental variable and other robustness tests confirm the robustness of the findings after addressing potential reverse causality concerns. This paper suggests that the effectiveness of fintech depends not only on technological investment but also on sustainability capabilities and institutional conditions. This study provides empirical evidence on fintech-driven sustainable banking transformation in China and offers practical implications for regulators and commercial banks seeking to promote digital finance and sustainable development. Full article

Sustainable building practices can reduce environmental harm and support resilient urban development. To aid built-environment professionals such as architects, building scientists and planners in accomplishing regenerative design objectives, a variety of building rating and accreditation schemes have been developed, such as Greenstar or the Living Building Challenge. These schemes primarily focus on sustainability targets, such as energy and water use. Biodiversity considerations, despite their importance for ecosystem services and human health, are predominantly absent as core objectives in the building rating tools currently in use. To address this gap, we introduce the New Zealand Biodiversity Factor—Building (NZBF-B), a tool created to educate and incentivise the integration of biodiversity into buildings by assessing their biodiversity value, with a focus on prioritising native species. We outline the development of the NZBF-B, including its components, its scoring methodology, and an expert-informed weighting process used to determine the ecological relevance of each category. The tool captures key characteristics of building-associated biodiversity through measurable indicators that reflect both habitat provision and opportunities to strengthen human–nature connection. We advocate for the use of the NZBF-B alongside existing certification schemes to achieve more effective green building performance outcomes related to biodiversity. Full article

Rapid economic development has led to a growing reliance on private car commuting, making the mitigation of carbon dioxide (CO₂) pollution along road environments critical for the health of nearby residents. Road greening serves as an ecological barrier between traffic emissions and adjacent residential areas, and its effectiveness in reducing local CO₂ pollution has been widely studied. However, the influence of different spatial morphologies of road greening on the distribution of CO₂ around buildings remains underexplored. In this study, we developed a numerical simulation model to investigate CO₂ dispersion on building surfaces under various road greening spatial configurations. Simulation results indicate that a “tree–shrub–grass” composite configuration significantly reduces CO₂ concentrations around buildings. These findings provide practical guidance for optimizing vegetation spatial layouts in high-density road networks and contribute to the global pursuit of carbon peak and carbon neutrality goals. Full article

Curcuminoids from Curcuma longa L. (curcumin, demethoxycurcumin, bisdemethoxycurcumin) are attractive bioactives yet constrained by low water solubility and chemical instability. Herein, we introduce a Supramolecular Deep Eutectic Solvent (SupraDES) as a “Janus” green platform, combining extraction and stabilization with a subsequent solvent-to-material strategy. Eight NaDES/SupraDES formulations based on choline chloride (ChCl) or betaine with glycerol (Gly) or citric acid (CitA), with/without β-cyclodextrin (βCD), were assessed. The extinction coefficients of the most promising solvents were extrapolated at 425 nm for the UV–vis quantification of curcuminoids, to determine extraction performance. The SupraDES ChCl:Gly:βCD gave the best performance during the first solvent screening, improving at the same time the bioactive stability (after 30-day, 47.5% loss vs. 62.8% of ChCl:Gly alone). Subsequent microwave-assisted extraction (MAE) optimization identified 80 °C as the optimal process temperature, with near-equilibrium reached within 15 min (3139.4 µgCurc/gEXT). Peleg modelling (R² = 0.997) indicated a fast extraction rate and limited benefit from longer residence times. Finally, the curcuminoid-loaded SupraDES was incorporated into polyvinyl alcohol (PVA) networks crosslinked with CitA and 2,5-bis(hydroxymethyl)furan (BHMF); thermal analysis confirmed the formation of a stable crosslinked structure. To the best of our knowledge, this is the first report of a βCD-based SupraDES acting as a Janus platform that couples supramolecular extraction of lipophilic bioactives with their direct incorporation into bio-based polymeric materials, exemplifying an integrated green chemistry approach aligned with circular bioeconomy principles. Full article

This study examines the determinants of carbon dioxide (CO₂) emissions across 25 European Union countries over the period 2000–2021, with particular emphasis on the roles of environmental taxation and green innovation in shaping environmental sustainability. The analysis is grounded in ecological modernization theory, endogenous growth theory, and the Environmental Kuznets Curve hypothesis, which collectively explain the long-run and dynamic interactions between environmental policy, economic activity, structural transformation, and environmental outcomes. To ensure robust empirical inference, this study applies a comprehensive econometric framework that accounts for cross-sectional dependence, heterogeneity, non-stationarity, cointegration, and endogeneity. The empirical strategy begins with Pesaran cross-sectional dependence tests and slope heterogeneity diagnostics, followed by second-generation panel unit root tests (Pesaran CADF/CIPS) and Westerlund cointegration tests to establish the existence of long-run equilibrium relationships among the variables. Long-run coefficients are estimated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), Canonical Cointegrating Regression (CCR), and Common Correlated Effects Mean Group (CCEMG) estimators. In addition, the Panel Autoregressive Distributed Lag (ARDL) model is employed to capture both short-run dynamics and long-run adjustment processes, while the System Generalized Method of Moments (System GMM) estimator addresses potential endogeneity, reverse causality, omitted variable bias, and dynamic persistence in CO₂ emissions. The empirical results indicate that environmental taxation has a positive and statistically significant association with CO₂ emissions, suggesting that current fiscal environmental policies in EU-25 countries may not yet be sufficiently effective in discouraging pollution-intensive activities. In contrast, green innovation is found to significantly reduce CO₂ emissions, underscoring the critical role of innovation-driven environmental investment and technological progress in improving environmental quality. Economic growth, exports, and urbanization are associated with higher emissions, while imports contribute to emission reductions, reflecting differences between domestic production-based effects and trade-related structural adjustments. The System GMM results further confirm the persistence of CO₂ emissions over time and validate the robustness of the long-run relationships identified by alternative estimators. Likewise, the CCEMG and Panel ARDL results support the stability and consistency of the findings under conditions of cross-sectional dependence and heterogeneous country dynamics. Taken together, the results highlight the importance of integrating environmental taxation with green innovation policies, innovation-driven investment, and sustainable trade policies to achieve long-term emission reductions in the European Union. This study contributes to the environmental economics literature by providing robust empirical evidence using second-generation panel econometric techniques that explicitly address cross-sectional dependence, heterogeneity, and endogeneity in the analysis of environmental sustainability. Full article

Against the backdrop of carbon peaking, carbon neutrality, and digital economy development, exploring the pathways through which artificial intelligence (AI) applications in manufacturing enterprises empower green transformation is of great significance. Using panel data on Chinese A-share listed manufacturing companies from 2005 to 2024 and a difference-in-differences (DID) model, this study examined the impact of the National Artificial Intelligence Innovation and Application Pilot Zones (AI Pilot Zones) policy on corporate green innovation. The results showed that the establishment of AI Pilot Zones significantly promoted green innovation among manufacturing enterprises, and this conclusion remained robust after parallel trend tests, PSM-DID estimation, and alternative variable measurements. Mechanism analysis revealed that financing constraints served as a key mediating channel, and that AI policies promoted green innovation through a serial mediation mechanism involving fintech development and the alleviation of financing constraints. Moderation analysis indicated that both human capital and digital transformation enhanced the policy effect. Heterogeneity analysis suggested that the policy’s impact was more pronounced among non-state-owned enterprises, large enterprises, and firms located in eastern regions. This study provides empirical evidence on the effectiveness of AI Pilot Zones in promoting green innovation among manufacturing firms and clarifies the underlying mechanisms. Full article

This study aims to investigate the effect of organizational identification (OI) on green organizational behavior (GOB) and the mediating role of psychological well-being (PWB) in this relationship. To achieve this research goal, a quantitative study was conducted using a structured questionnaire designed to assess the relevant variables. Data was collected from 264 white-collar employees in the service sector in Istanbul. Surveys were collected from participants face-to-face, using a judgmental sampling method. Hypotheses were tested using AMOS22, SPSS 24 and PROCESS Macro. The significance of indirect effects was analyzed by employing the bootstrapping technique. The results indicate that OI has positive and significant direct effects on GOB and PWB. Furthermore, PWB was found to significantly predict GOB. The bootstrapping analysis revealed that the indirect effect was significant, supporting a partial mediation model. This research illustrates that OI increases GOB both directly and indirectly through PWB. The findings are considered to be of relevance to the literature because this is one of the few studies that addresses the concept of green organizational behavior, which is a focal point in the organizational behavior literature, and it emphasizes the importance of psychological resources in promoting environmentally friendly behaviors within organizations. Full article

Green bonds have become an important financial instrument for supporting environmental investment and industrial transformation. This paper examines short-term profitability dynamics around first green bond issuance among heavy-polluting firms listed on China’s A-share market. Using a staggered-adoption framework based on the group-time average treatment effect estimator of Callaway and Sant’Anna we compare issuing firms after issuance with never-issuing and not-yet-issuing firms while controlling for firm characteristics, firm fixed effects, and year fixed effects. The estimates show that issuing firms experience an average post-issuance ROE decline of approximately 4.9 percentage points during the four years following issuance. Given that the average ROE in the sample is 0.0702, this estimate is economically substantial. Because green bond issuance is a voluntary corporate financing decision rather than an externally assigned policy shock, the estimates are interpreted as treatment-on-the-treated effects under the assumptions of no anticipation, overlap, and conditional parallel trends. Additional diagnostics and a DuPont-style mechanism analysis suggest that the post-issuance ROE decline is mainly associated with lower net profit margins and, to a lesser extent, lower asset turnover. Heterogeneity analyses indicate that the post-issuance profitability pressure varies across ownership types, regions, and industries. Full article

The housing sector in major cities is facing escalating challenges due to rapid population growth and land scarcity. Consequently, vertical growth has been adopted as a strategic solution to optimize land use while balancing economic, social, and environmental needs. This study examines the phenomenon of vertical growth of the Dammam Metropolitan Area (DMA) in Saudi Arabia, from an urban sustainability perspective, focusing on evaluating the current state of multi-story buildings, their determinants, and their impact on quality of life and infrastructure efficiency. This study utilizes a systematic review methodology and a conceptual approach to develop an integrated framework for sustainable vertical growth. Furthermore, an empirical validation was conducted by projecting this framework onto vertical housing projects in Dammam, focusing on challenges related to design, construction quality, shared service management, and the suitability of apartments for family needs. The results indicate that the shift toward vertical growth achieves land-use efficiency, limits random horizontal expansion, and provides economic opportunities. However, it faces social and cultural constraints, most notably the resistance of some families to changing traditional ownership patterns, limited privacy and green spaces, and challenges in building maintenance and operations. The study highlights the importance of integrating urban planning, governance, architectural design, and infrastructure to ensure the sustainability of vertical growth and provide suitable housing alternatives. The study recommends further field research to assess social acceptance, improve quality-of-life indicators, and develop policies encouraging sustainable vertical expansion in alignment with Saudi Vision 2030 and the 2030 Sustainable Development Goals (SDGs), ensuring cities are more resilient, efficient, sustainable, and liveable. Full article

As sustainable finance continues to advance, an important question is how scientifically designed and well-targeted policies can curb corporate ESG greenwashing and improve the quality of firms’ ESG and sustainability disclosure. From the perspective of fiscal–financial policy coordination, we exploit the green loan interest subsidy policy (GLIS) as a quasi-natural experiment and develop an analytical framework around four policy components: commercial banks’ information screening, local governments’ green screening, the subsidy instrument’s leverage and certification effects, and firms’ internal green governance. Within this framework, we examine whether the GLIS can restrain corporate ESG greenwashing. Using Chinese listed firms from 2009 to 2022 as the sample and identifying the effect through a multi-period difference-in-differences (DID) model, we find that the GLIS significantly curbs corporate ESG greenwashing. In exploring the underlying channels, we find that the GLIS curbs corporate ESG greenwashing by strengthening commercial banks’ information screening, enhancing local governments’ green screening, easing firms’ external financing constraints, and reinforcing firms’ internal green governance. Further analysis indicates that the inhibitory effect of the GLIS on corporate ESG greenwashing is more pronounced among non-state-owned firms, firms in the growth stage, firms in heavily polluting industries, and firms located in regions with weaker resource endowments. In addition, the stronger a firm’s digital technology R&D capability and corporate governance capability, the greater the restraining effect of the GLIS on its ESG greenwashing. By systematically evaluating the governance effect of fiscal–financial policy coordination on corporate ESG greenwashing, our study provides useful insights for governments seeking to improve green finance policies and optimize the coordination of green policy instruments. Full article

Soybean is a critical economic, oil and industrial raw material crop, yet its production is often hindered by pathogen infection and pesticide residues. This study explored the synergistic effects of Rhizophagus intraradices and mycorrhizal helper bacteria (MHB) on AMF colonization, AMF spore density, total number of bacterial colonies, soybean growth, root rot disease index, and carbendazim residues. Hydroponic and pot experiments were conducted using a completely randomized design (CRD) with five biological replicates per treatment; after 30 days of growth, three replicates were randomly selected for all measurements. Results showed that inoculation with microbial agents, particularly co-inoculation, increased soybean biomass, reduced disease index, and decreased carbendazim residues. In the hydroponic experiment, co-inoculation increased plant height, aboveground fresh weight, and underground dry weight by 64.28%, 78.13%, and 109.09%, respectively, and decreased carbendazim residues by 71.84% relative to the carbendazim-alone group. In the pot experiment, co-inoculation reduced carbendazim residues by 81.25% and root rot disease index by 45.56% compared with the carbendazim-alone group. Correlation analysis showed a strong positive correlation (p < 0.001) between carbendazim degradation in hydroponic and pot systems, indicating stable degradation function across environments. Co-inoculation of R. intraradices and MHB synergistically promotes soybean growth, suppresses root rot, and reduces carbendazim residues, providing a theoretical basis for developing functional microbial inoculants for safe and green soybean production. Full article

Green synthesis of KGM-capped CeO₂ nanoparticles was successfully achieved through a simple coprecipitation method using Konjac Glucomannan (KGM) as a biopolymeric capping and stabilizing agent. The reaction conditions were optimized by varying pH (9–11) and temperature (30–70 °C) to evaluate their influence on nanoparticle formation and photocatalytic performance. The synthesized KGM–CeO₂ nanoparticles were comprehensively characterized using FTIR, UV–Vis spectroscopy, XRD, SEM–EDS, TEM, DLS, and ZP analysis to investigate their structural, optical, morphological, and surface properties. The characterization results confirmed the successful formation of porous sponge-like branched CeO₂ nanostructures with irregular morphology. XRD analysis revealed the crystalline nature of the nanoparticles with an average crystallite size of approximately 7.7 nm, while DLS analysis showed an average hydrodynamic particle size of 29.7 nm with a biomodal particle size distribution. The positive zeta potential value (+16.75 mV) confirmed good colloidal stability and reduced agglomeration due to effective capping by KGM. The synthesized nanoparticles also exhibited favorable optical properties with band gap values suitable for photocatalytic applications. The adsorption and photocatalytic degradation performance of the KGM–CeO₂ nanoparticles was investigated against synthetic textile dyes, including Naphthol Blue Black (NBB), Methyl Orange (MO), and a mixed NBB–MO dye system under acidic conditions. Using an adsorbent dosage of 50 mg and dye concentrations of 100 mg/L, the material achieved degradation efficiencies of approximately 99% for NBB, 91% for MO, and 52% for the mixed dye system under UV irradiation for 120 min. Adsorption kinetic studies indicated that the pseudo-second-order model provided the best fit, suggesting that chemisorption is the dominant adsorption mechanism involving multifunctional surface interactions. These findings are particularly relevant for industrial wastewater treatment, since actual textile effluents typically contain complex mixtures of dyes and organic contaminants rather than single dye pollutants. The mixed dye experiments, therefore, provide a more realistic simulation of industrial wastewater conditions. Overall, the synthesized KGM–CeO₂ nanoparticles demonstrate excellent potential as an eco-friendly, cost-effective, and sustainable multifunctional material for adsorption-assisted photocatalytic treatment of dye-contaminated wastewater. Further optimization of operational conditions and catalyst surface properties may enhance its efficiency in multicomponent wastewater systems. Full article

Complex networks have become a fundamental paradigm for modeling real-world systems. Synchronization of such networks, particularly under hyperchaotic dynamics, presents a significant control challenge due to the high-dimensional state space and multiple positive Lyapunov exponents. This paper addresses the driver node selection problem in a 4D Hyperchaotic Lorenz complex network, formulating it as a constrained binary optimization task. We evaluate a pool of advanced metaheuristics, including the quantum genetic algorithm (QGA), seahorse optimizer (SHO), and artificial bee colony (ABC), across multiple network experiments conducted over 30 independent runs to guarantee statistical validity. The performance of these solvers is rigorously benchmarked against traditional topological heuristics, a random selection baseline comprising 600 feasible configurations, and verified through Wilcoxon statistical testing. Furthermore, addressing computational sustainability, we introduce a “Green-Artificial Intelligence” architecture based on dual-tier structured query language memoization (SQL-memoization) and provide a detailed runtime comparison evaluating its efficiency. The empirical results indicate that swarm-intelligence methods such as ABC and SHO exhibit robust competitive performance in minimizing synchronization errors while the Green-AI framework consistently and drastically reduces the computation of the repetitive simulations. Full article

Environmental supply-chain governance increasingly requires firms to trace climate accountability across buyer–supplier relationships. This study examines whether downstream customer climate pressure is associated with suppliers’ green supply-chain management and value-chain carbon accountability among Chinese listed firms. We construct an exposure-weighted customer pressure measure by combining disclosed top-customer relationships with customer climate-accountability signals, and we decompose this measure into disclosure-based and non-disclosure-based components so that symbolic and substantive accountability can be separated. We then link this measure to supplier green supply-chain indicators, value-chain carbon-disclosure components, Scope 3 disclosure, environmental investment, and reported environmental performance indicators, including air emissions, water pollutant discharge, resource consumption, and environmental tax. Using firm-year panel regressions with fixed effects, alternative pressure measures, selection corrections, and extended outcome tests, we find an association between customer climate pressure and supplier value-chain disclosure. The depth of the association is concentrated where customer carbon-disclosure visibility is observed and is not separately identified in the smaller climate-only subsample, while the value-chain interaction association is positive but imprecisely estimated there. The value-chain disclosure associations are robust to a year-stratified randomization-inference placebo test. We do not find evidence that customer pressure is associated with supplier emissions, resource use, environmental investment, or environmental tax in the available matched samples. The pattern is consistent with symbolic compliance in supply-chain carbon accountability: customer disclosure visibility maps into supplier disclosure visibility, while we do not observe parallel movement in substantive environmental outcomes. The central finding is therefore that downstream customer climate pressure is associated with what suppliers disclose rather than with what they emit, shaping supplier disclosure behavior rather than substantive emission reduction. The estimates apply to supplier-year observations with disclosed and mappable listed-customer links, which we treat as the scope condition of the study rather than as an incidental data limitation. Full article

ESG-oriented marketing and its influence on consumers’ green consumption behavior have become important issues in sustainable development research, yet the emotional and cognitive mechanisms underlying this relationship remain insufficiently examined. Drawing on an integrated emotion–cognition–behavior perspective, this study focuses on Chinese Generation Z consumers and develops a model linking Perceived ESG Communication, Eco-Anxiety, Perceived Consumer Effectiveness, and Green Action Intention. Based on 400 valid survey responses, structural equation modeling and PROCESS 4.1 were employed to examine the structural relationships, mediation effects, and serial mediation pathway among the focal constructs. The results show that Perceived ESG Communication is positively associated with Green Action Intention both directly and indirectly. Specifically, Eco-Anxiety and Perceived Consumer Effectiveness each serve as significant mediators in the relationship between Perceived ESG Communication and Green Action Intention. Further analysis indicates that Eco-Anxiety is positively associated with Perceived Consumer Effectiveness, forming a significant serial mediation pathway through which ESG-related communication is linked to green action intention. These findings suggest that ESG-oriented marketing may influence Generation Z consumers not only by transmitting sustainability-related information, but also by activating environmental concern and strengthening consumers’ perceived effectiveness in contributing to sustainability outcomes. The study contributes to ESG communication and sustainable consumption research by clarifying the affective and cognitive mechanisms through which perceived ESG messages become behaviorally meaningful for young consumers. It also provides practical implications for designing ESG-oriented marketing strategies that combine credible responsibility communication with clear consumer action pathways. Full article