Search Results (6,445)

Livestock farming is blamed for its significant carbon footprint (CF), contributing to environmental pollution and climate change. Among other approaches, this has highlighted the need to find alternative feeding systems for cattle production that are potentially able to reduce greenhouse gas (GHG) emissions. In this context, the objective of the present study was to compare the CF of producing cattle fed a Conventional diet versus cattle fed a diet that included vegetable by-products (VBP diet) sourced from the local agri-food industry. In this study, twenty-four entire male young bulls were reared in Navarra, Spain. Twelve calves were finished on the VBP diet that also included fodder and grain, and the remaining animals were finished with a local Conventional diet based on concentrate and straw. Results showed a larger CF of meat from animals fed the Conventional diet in comparison with the VBP-fed ones, that is, 117.84 kg versus 42.01 kg of CO₂ equivalent per kilogram of meat, respectively. This research demonstrates that using by-products from the local agri-food industry for feeding cattle has an important beneficial effect on the environment. It is not only a circular economy solution that recovers and recycles by-products instead of treating them as waste, but can also notably reduce the GHG associated with livestock production. This study marks the beginning of ongoing research into the effect of introducing regional vegetable by-products in the diet of livestock and their corresponding impacts on productivity and the environment, particularly in terms of GHG emissions per kilogram of feed consumed. Full article

Historic urban manufacturing territories are increasingly being reconsidered as strategic components of metropolitan sustainability rather than obsolete remnants of industrial economies slated for redevelopment. While these districts have long been associated with pollution, environmental degradation, and post-industrial decline, growing interest in circular economy strategies, Urban Resource Recovery (URR), and climate adaptation has renewed attention to their territorial significance. Using the North Brooklyn Industrial Business Zone and the Newtown Creek watershed as a case study, this paper argues that certain historic manufacturing territories possess an inherent capacity to evolve into Metropolitan Metabolic Infrastructure because of inherited geographic, infrastructural, and institutional characteristics, including waterfront access, freight networks, industrial zoning, large industrial parcels, and utility systems. Drawing upon research developed through the New York City Department of Design and Construction’s Town+Gown Urban Resource Recovery Working Group, the study combines historical analysis, spatial interpretation, planning policy, and case-study research to examine the evolving relationship among urban metabolism, circular economy, environmental justice, and Healthy Cities. Rather than advocating industrial preservation irrespective of environmental performance, the paper argues that these territories can support metropolitan material circulation while advancing cleaner industrial practices, environmental remediation, and more equitable urban development. The Metropolitan Metabolic Infrastructure framework offers a planning perspective for understanding how inherited manufacturing landscapes may contribute to resilient, circular, and healthier metropolitan regions while informing future comparative research on industrial territories undergoing similar transitions worldwide. Full article

Higher education institutions are increasingly expected to reduce greenhouse gas emissions while maintaining reliable educational, laboratory, and administrative operations. This challenge is particularly relevant in transition economies, where university campuses often depend on fossil-fuel-based electricity systems, natural-gas heating, and aging infrastructure. This study presents a campus-scale decarbonization assessment for the Tashkent Institute of Chemical Technology in Uzbekistan. The quantified inventory covered Scope 1 emissions from natural-gas combustion and Scope 2 emissions from purchased electricity. Paper use, digital services, behavioural measures, and campus greening were assessed as supplementary institutional indicators and were excluded from the quantified total because consistent pre- and post-intervention activity data were unavailable. The assessment combined institutional utility records for 2023–2025 with information on renewable-energy deployment, heating modernization, digital transformation, sustainability awareness, and campus greening. A 300 kW solar photovoltaic system comprising 666 modules was commissioned in May 2023, with a documented annualized generation potential of approximately 520,000 kWh. Purchased grid electricity amounted to 711,402, 745,947, and 749,060 kWh in 2023, 2024, and 2025, respectively, while annual natural-gas consumption was 144,775, 161,200, and 142,031 m³. Using a conservative standard-based net calorific value of 31.8 MJ/m³ together with IPCC stationary-combustion factors, annual Scope 1 and Scope 2 emissions were estimated at 637.53, 685.29, and 652.65 tCO₂-eq, respectively. The 2025 total was 4.76% below the 2024 value but 2.37% above the 2023 value. The annualized PV technical potential corresponds to a theoretical maximum Scope 2 displacement of 276.64 tCO₂-eq/year under 100% self-consumption. This value does not represent measured generation or a realized emission reduction and was not included in the quantified inventory. Digitalization, behavioural engagement, and greening were evaluated as complementary measures rather than assigned separate emission-reduction credits. The study provides a transparent and regionally relevant framework for universities in transition economies seeking to strengthen campus carbon management under incomplete data conditions. Full article

The Artificial Intelligence Pilot Zone Policy is an important strategic initiative for building artificial intelligence (AI) innovation hubs. It provides new opportunities to enhance manufacturing firm resilience and promote the sustainable development of the manufacturing sector. The creation of the National New-Generation Artificial Intelligence Innovation and Development Pilot Zones (AI Pilot Zones) is viewed in this study as a quasi-natural experiment. Using data from Chinese A-share-listed manufacturing firms from 2015 to 2023, we employ a staggered DID model to evaluate the impact of the policy on manufacturing firm resilience. We find that the AI Pilot Zone policy increases manufacturing firm resilience by an average of 0.0282 units. The analysis of potential mechanisms shows that the policy significantly promotes digital talent agglomeration, stimulates urban innovation vitality, and improves firm-level supply chain efficiency. These findings are consistent with the theoretical expectations and provide supportive evidence that these factors may constitute potential mechanisms associated with the policy’s effect on manufacturing firm resilience. The heterogeneity analysis reveals a pronounced “weakness-compensating” effect. At the regional level, the resilience-enhancing effect is stronger for manufacturing firms located in areas with relatively weak digital infrastructure. At the industry level, the effect is more pronounced among firms in low-technology manufacturing industries. At the firm level, the effect is stronger for firms with lower levels of human capital, weaker innovation capacity, and lagging digital transformation. Overall, this study provides micro-level evidence on the resilience effects of the AI Pilot Zone policy and offers policy implications for integrating AI more effectively with the real economy. Full article

Forecasting corporate leverage adjustments remains challenging due to persistent financing behavior, firm heterogeneity, and changing macroeconomic conditions. This study investigates whether increasing model complexity improves the forecasting of corporate leverage adjustment by comparing dynamic econometric models, machine learning algorithms, and a neuro-symbolic artificial intelligence framework. The analysis is based on an unbalanced panel of 39,226 firm-year observations from 3001 publicly listed non-financial firms across 18 countries. The empirical analysis compares Fixed Effects and two-step Difference GMM estimators with regularized regression, gradient boosting, artificial neural networks, and a theory-guided neuro-symbolic framework that incorporates economically meaningful financial constraints through a resampling-based approximation of a differentiable rule-based penalty. Model performance is evaluated using out-of-sample forecasting accuracy measured by the Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and the coefficient of determination (R²). The results indicate that corporate leverage exhibits substantial persistence, with estimated adjustment speeds of approximately 29–36% annually. Machine learning algorithms do not improve forecasting accuracy relative to benchmark dynamic econometric models when evaluated out of sample, while incorporating symbolic financial constraints provides only limited additional predictive benefits. These findings suggest that leverage persistence dominates model complexity and that parsimonious dynamic econometric models remain highly effective for forecasting corporate leverage adjustment. The study contributes to the growing literature on explainable artificial intelligence in corporate finance by providing a comprehensive comparison of dynamic econometric, machine learning, and neuro-symbolic approaches within a unified forecasting framework for emerging economies in the MENA region. Full article

Upstream small- and medium-sized enterprises (SMEs) in emerging economies often face severe credit constraints. These constraints hinder green transformation by limiting green R&D investment and production capacity. To address this, we develop a Stackelberg-based governance strategy selection framework. We first analyze cost-sharing (CS) and equity-sharing (ES) contracts and then extend them by incorporating external financing, where the retailer’s contractual commitment serves as an operational guarantee. This integration leads to two incentive-financing bundles, namely CS-F and ES-F. Three main findings emerge. First, capital constraints fundamentally shape the feasibility of green supply chain governance by creating a trade-off between green R&D and physical production. Specifically, the CS contract is feasible only within an intermediate capital range, whereas the ES contract is infeasible. Second, the incentive-financing bundles relax capital constraints and expand the feasible governance region. Although all feasible governance strategies promote green R&D investment, the ES-F bundle remains more sensitive to parameter variations. Third, the optimal governance strategy depends primarily on firms’ capital conditions, shifting across CS, CS-F, and ES-F. Notably, a distributive-efficiency paradox emerges: even when the ES-F bundle yields greater total surplus, a higher sharing ratio violates the retailer’s individual rationality and prevents its adoption. We introduce an asymmetric Nash bargaining mechanism to address this paradox. The mechanism determines transfer payments endogenously and restores the efficient governance outcome. Overall, our findings help supply chain managers select appropriate governance strategies based on observable firm-level capital conditions. Full article

Green finance has emerged as a critical mechanism for aligning capital markets with climate and sustainability objectives, particularly as economies face mounting pressure to transition away from carbon-intensive growth models. In hydrocarbon-dependent regions such as the Gulf Cooperation Council (GCC), this transition poses distinctive challenges that require integrated institutional, policy, and financial frameworks. The global transition toward sustainable finance has gathered significant momentum, with green capital markets emerging as a central mechanism for channeling investment toward climate and development objectives. Hydrocarbon-dependent economies face a distinctive challenge in this transition, as they must reconcile resource-based growth models with rising pressures for environmental accountability and low-carbon diversification. This study develops an integrated theoretical framework to examine how Gulf Cooperation Council (GCC) financial systems are transitioning toward green capital markets, drawing on institutional theory, environmental policy pathway analysis, and climate-finance alignment models. Using descriptive statistics from regional stock exchanges covering 2015–2024, the study maps key trends in sustainable asset growth, institutional investor preferences, and regulatory evolution across the GCC. Findings indicate progressive alignment with global ESG norms; sustainable asset valuations grew at 23.5% CAGR (UAE) and 18.7% CAGR (Saudi Arabia). A fixed-effects panel regression with panel-corrected standard errors is estimated across all six GCC economies; regulatory framework maturity emerges as the strongest predictor of green bond issuance (β = 0.47, p < 0.01). Cumulative green bond issuances reached USD 52.6 billion (2015–2024), with renewable energy accounting for 58.1% of the sectoral allocation and green transportation recording a 55.9% CAGR (2020–2024). Policy recommendations focus on GCC-wide harmonization of mandatory ESG disclosure, adoption of a unified green bond taxonomy, and expansion of concessional green financing mechanisms. Substantial cross-country heterogeneity is documented, driven by differences in energy policy commitment, financial market maturity, and institutional capacity. The proposed framework offers specific policy guidance to accelerate green financial integration in the GCC, emphasizing regulatory harmonization, institutional capacity-building, and alignment with SDG targets 7 and 13. The study contributes to the limited evidence base on green finance in hydrocarbon-dependent economies and provides a foundation for future empirical research. Given the small panel dimensions (N = 6 cross-sectional units; T = 10 years), this study is positioned as exploratory rather than confirmatory: the panel-regression estimates and the hypothesized institutional-to-policy-to-finance sequence are interpreted as associational patterns consistent with the proposed framework rather than as definitive causal tests, and the reported coefficients are offered as indicative magnitudes to be re-examined as longer GCC green-finance time series become available. Full article

Laos is one of the 32 landlocked developing countries (LLDCs) of the world, where isolation from the sea and the lack of a large-scale fishing industry have a direct effect on fish supply and fish consumption. Per capita fish consumption in LLDCs amounted to 5.1 kg/year in 2023, which is much lower than the world average (20.3 kg) as well as the Developing Regions average (20.0 kg). However, per capita fish consumption in Laos has reached 28.5 kg/year in 2023, representing the highest among the 32 LLDCs. Relying on the results and experiences of several decades of work in aquaculture development in Laos and taking into account the observations of local and international publications, documents and statistics included, the authors aimed at identifying the principal reasons for the elevated fish consumption in Laos from different perspectives, including that of aquaculture, as well as Lao language, culture, and religion. In this review, the authors analyzed the availability of aquatic resources, the role of fishing and aquaculture in the Lao economy and social life, market realities, as well as the importance of fish in Lao culture. Full article

Residential electricity tariff structures in emerging economies are often highly complex, dynamically combining regional climatic variables and multi-tiered price adjustments. In Mexico, despite a preferential scheme designed to mitigate seasonal expenditure fluctuations, baseline energy subsidies frequently fail to protect low-income households due to structural targeting inefficiencies based strictly on regional temperature thresholds rather than socioeconomic status. This study addresses this methodological and regulatory gap by developing the Energy-Economic Impact Index (EEII), a novel mathematical and heuristic framework that couples complex Increasing Block Tariffs (IBT) architecture with localized household income dynamics at the state level. The proposed methodology was comprehensively validated using synchronized biennial empirical datasets from all 32 Mexican states, combining Federal Electricity Commission (CFE) billing data and National Surveys of Household Income and Expenditures (ENIGH) spanning the 2018–2024 period. Quantitative results reveal a severe, non-linear escalation of the financial energy burden across the territory, demonstrating that rising residential electricity costs significantly outpaced domestic income growth trajectories. Notably, households situated within high-temperature geographic regimes (Tariffs 1D, 1E, and 1F) exhibited the most critical economic vulnerability, with the calculated energy cost impact absorbing up to 14.90% of the real monthly household income in 2024. Ultimately, the EEII framework proves to be a robust predictive and decision-support tool for energy policy planners aiming to optimize fiscal subsidy allocation, reduce energy poverty gaps, and mitigate socioeconomic risks in transition economies. Full article

Recreational fisheries contribute significantly to global economies through tourism, employment, and ecosystem service valorization. However, a systematic understanding of their economic magnitude and regional disparities remains fragmented. This study conducts a systematic review of 112 peer-reviewed articles published between 1991 and 2024, synthesizing the economic evidence across three key domains: consumer behavior, resource management, and ecological interactions. Consistent with previous research, our systematic synthesis documents a pronounced imbalance in the existing evidence base: studies from high-income countries more frequently report established management frameworks (e.g., bag limits, catch-per-unit-effort monitoring) and robust economic valuation mechanisms (e.g., Willingness to Pay estimation), whereas low- and middle-income countries face significant barriers in infrastructure and resource quantification. We identify that non-market valuation methods, particularly the travel cost method and consumer surplus analysis, are critical for internalizing the environmental value of fisheries. Furthermore, while ecological restoration demonstrates clear positive feedback loops for local economies, the sector exhibits high vulnerability to external shocks, such as the COVID-19 pandemic. This review highlights the urgent need to bridge the data gap in developing regions and suggests that transferring successful adaptive management models from developed nations is essential for achieving equitable and sustainable growth in the global recreational fishery economy. Full article

Financial development can influence carbon emissions through capital allocation, technological support, and policy transmission. To investigate the inherent association between grassroots inclusive financial institutions and territorial green transformation, this study establishes a city-level panel dataset of the Yangtze River Delta urban agglomeration covering the period from 2010 to 2022. Within the analytical framework of the Spatial Durbin Model, this research decomposes the baseline effect, functional transmission pathways, and cross-sectional heterogeneity of the impact of the development of small loan company (SLC) providers on urban carbon intensity. The results show that SLC expansion significantly increases local carbon emission intensity and produces spatial spillover effects across neighboring cities. Mechanism analysis indicates that SLCs increase emissions mainly by supporting the expansion of small- and micro-sized enterprises in energy-intensive manufacturing sectors, while their role in promoting green technological innovation remains limited. Further analysis shows that local government willingness to pursue green transition weakens the carbon-increasing effect of SLCs, whereas digital inclusive finance strengthens it. The effect also varies by location and regulatory environment, with stronger effects in medium-distance cities and under lower regulatory intensity. These findings reveal how grassroots inclusive financial institutions affect regional carbon outcomes and offer policy implications for aligning inclusive finance with green transition goals. This paper innovatively transcends the conventional low-carbon research paradigm focusing on macro-finance and large formal financial institutions, and instead takes SLCs, a typical micro-level inclusive finance entity, to explore their unique paths affecting regional carbon emissions, and clarifies their action boundaries from multiple dimensions including government governance and digital finance empowerment, which enriches interdisciplinary research literature integrating inclusive finance and low-carbon economy. But this study has limitations: its sample is limited to the Yangtze River Delta urban agglomeration, so the universality of the conclusion needs further verification. This research provides theoretical support and policy reference for regulating the sustainable development of the small loan industry, promoting the integration of inclusive finance and green low-carbon transformation, and advancing high-quality regional low-carbon development. Full article

Sustainable Digital Infrastructure plays an increasingly important role in strengthening regional economic resilience and promoting inclusive growth. However, its dynamic effects on nascent entrepreneurship remain underexplored. Treating China’s smart city pilot policy as a quasi-natural experiment, this study uses data on newly registered enterprises in 288 Chinese cities from 2005 to 2019 and a multi-period difference-in-differences (DID) model to examine this relationship. The results show that Sustainable Digital Infrastructure significantly promotes new venture creation. Owing to environmental dynamism—manifested in creative destruction, strategic wait-and-see behavior, and learning-curve effects—its entrepreneurial impact is initially volatile before becoming significantly and persistently positive. The industry-level analysis reveals heterogeneous effects across sectors: the largest estimated effect occurs in wholesale and retail trade, while the estimated effect in scientific research and technical services strengthens over time. Mechanism analyses provide suggestive evidence for three channels: technological innovation, human capital development, and digital finance. The effects are also more pronounced in eastern China and smaller cities. This study provides empirical evidence and practical guidance for emerging economies seeking to promote new venture creation through digital infrastructure. It conceptualizes “sustainability” in the SDI context as the capacity of digital infrastructure to support enduring and inclusive economic development, rather than as a property of the infrastructure’s environmental performance. Full article

Zero-waste city (ZWC) construction serves as a vital approach to regional sustainable development amid tightening resource constraints and the dual carbon goals. Examining its impact on urban green development efficiency (UGDE) and the underlying transmission mechanisms bears important theoretical significance and practical value. Drawing on panel data covering 281 Chinese cities from 2008 to 2024, this study adopts the difference-in-differences model to examine how the zero-waste city pilot (ZWCP) policy affects UGDE. The main findings are summarized as follows. (1) ZWCP policy significantly improves UGDE, and this core conclusion remains robust after multiple robustness tests and endogeneity corrections. (2) Mechanism tests confirm that ZWCP elevates the green development efficiency of pilot cities through two intermediate channels: green industrial agglomeration and public environmental awareness. (3) The ZWCP policy exerts positive spatial spillover effects on UGDE improvement. However, the two transmission mechanisms show heterogeneous spatial linkage effects. Green industrial agglomeration acts as the core channel for policy spatial radiation, with inter-city agglomeration diffusion driving UGDE growth in neighboring cities. In contrast, public environmental awareness only exerts a local mediating effect, with no significant spatial spillover on UGDE. (4) The moderation analysis reveals that government environmental attention (GEA) strengthens both transmission paths, exerting a positive moderating effect on the UGDE promotion of ZWCP. (5) Heterogeneous results indicate that the policy’s boosting effect is more pronounced in eastern regions, resource-based cities and highly urbanized cities. These findings provide empirical evidence and targeted policy references for advancing urban green development efficiency via the differentiated implementation of zero-waste city initiatives across China. They also offer practical Chinese insights for other developing economies pursuing green urban transition. Full article

As a new engine of economic development, the digital economy is profoundly reshaping the governance structure and production models of modern agriculture and has increasingly become a significant force driving the high-quality development of agricultural export trade. Based on provincial panel data from 30 Chinese provinces spanning from 2014 to 2023, this paper employs a two-way fixed effects model to systematically examine the statistical association between the digital economy and agricultural export competitiveness. Furthermore, a mediation effects model is adopted to explore the underlying transmission pathways, and a threshold effects model is applied to reveal the nonlinear characteristics of this association, thereby providing a multidimensional analysis of the underlying mechanisms. The empirical results indicate that: (1) there is a significant positive statistical association between the digital economy and agricultural export competitiveness, and this finding remains robust across a series of robustness checks; (2) upgrading of agricultural industrial structure, agricultural technological innovation, and agricultural labor transfer serve as three important transmission pathways through which the digital economy is associated with enhanced export competitiveness; (3) this positive association exhibits regional heterogeneity, with stronger effects observed in central regions and major grain-producing areas; and (4) there is a nonlinear relationship between the digital economy and agricultural export competitiveness. Finally, based on these empirical findings, several policy implications are proposed, including strengthening digital infrastructure construction, enhancing trade openness, cultivating agricultural digital talents, optimizing factor allocation structures, and improving the digital economy governance system, so as to fully unlock the potential space of the positive association between the digital economy and agricultural export competitiveness. Full article

In 2025, the oil and fat industry of the Republic of Kazakhstan showed steady growth, strengthening the country’s position as a major producer and exporter of vegetable oils. However, the production process generates large amounts of waste (up to 100 tons per day), and its recycling is an important part of the oil and fat industry’s economy. High-temperature processing of plant waste has proven to be a promising method for creating new materials for various industries. The aim of this study was to determine the influence of various technical parameters of carbonization (processing temperature and process environment) on the physical and chemical characteristics of materials obtained by carbonizing sunflower seed husks from the East Kazakhstan region at temperatures of 300, 400, 500, 600, 700 and 800 °C in an inert argon environment, as well as by processing the husks in an oxidizing environment at a temperature of 650 °C, for further use in elastomer compositions as new ingredients. Increasing the carbonization temperature in an inert environment led to an increase in the amorphous carbon content, surface porosity, and pH of the studied materials. Another parameter that showed a tendency to increase with increasing temperature in an inert environment was the BET specific surface area. In the case of using an oxidizing environment, the highest pH value was observed, and the formation of crystalline mineral phases was also observed. The differences in the phase states of the studied materials may play an important role in shaping the spatial stack of the polymer matrix when used in rubber compound formulations. Full article