Search Results (389)

Appropriate-scale operation is important for integrating ordinary farm households into modern agriculture, yet the appropriate scale may differ substantially across producer types. Using micro-level data from the nationally representative 2021 China Household Finance Survey, this study develops an analytical framework integrating efficiency and resilience perspectives to compare ordinary farm households and family farms. Efficiency is the core empirical dimension and is assessed using cost–benefit analysis, the DEA-BCC model, and multivariate econometric methods. Resilience is treated as a theoretical perspective and a constraint on scale decisions; it is interpreted indirectly through the scale responses of the two groups to disaster shocks rather than measured using a standalone resilience index. The results identify distinct efficiency-based appropriate-scale ranges: 1–3 mu (approximately 0.07–0.20 hm²) for ordinary farm households and 100–200 mu (approximately 6.67–13.33 hm²) for family farms, with lower net profit per unit area at intermediate scales. Economic rationality and institutional constraints show marked heterogeneity across producer types: commercialization, land titling, subsidies, and credit access are more strongly associated with the scale expansion of family farms, whereas non-farm employment opportunities play a more decisive role for ordinary farm households; household labor and social networks contribute to scale expansion in both groups, and their between-group differences are not statistically significant. Disaster impact is associated with a significant reduction in the operational scale of ordinary farm households, whereas in the subgroup estimates the operational scale of family farms shows no significant association with disaster impact, suggesting that family farms are better able to maintain their operational scale. Digital technology also operates through differentiated pathways: it primarily alleviates information and factor constraints among ordinary farm households while strengthening efficiency, financial access, and organizational coordination among family farms. These findings support differentiated scale and digital-agriculture policies in economies characterized by heterogeneous farm structures. Full article

Mozambique has prioritized soybean within its agricultural strategy, yet smallholder yields remain far below attainable levels and the share of that shortfall attributable to inefficient use of existing inputs has not been quantified. This study estimates farm-level technical efficiency (TE) and its determinants for 926 smallholder soybean farmers drawn from the 2023 Integrated Agricultural Survey covering Zambezia, Tete, Manica and Niassa, the provinces supplying the great majority of national output. A translog stochastic production frontier with a half-normal inefficiency term was fitted by maximum likelihood in a single step, with the variance of the inefficiency term parameterized as a function of farm and household characteristics. Approximately 72% of the residual variation separating farmers from the frontier was attributable to technical inefficiency rather than to random noise. Mean TE was 0.40 (range 0.02 to 0.81), an efficiency gap of about 60 percentage points, corresponding to a proportional output increase of approximately 147% from better use of existing inputs. Returns to scale over the continuous inputs entering the frontier were decreasing (approximately 0.74). Land was the dominant continuous frontier input and irrigation shifted the frontier upward. Farmers in the Central zone were more efficient than those in the North (0.43 against 0.36). The sex of the household head and region were the only determinants significant on both the coefficient and bootstrap tests, while credit access, though largest in marginal effect, was supported by the bootstrap interval alone. The findings support geographically targeted extension and gender-sensitive support. Full article

Sustainable agriculture in Southeast Asia requires balancing economic viability with climate mitigation. This study investigated whether integrated intercropping can mitigate early-stage economic “dead zones” in perennial crops while simultaneously enhancing long-term carbon sequestration. A 25-year bio-economic simulation in Thailand compared three scenarios: oil palm monoculture (OPM), cassava monoculture (CM), and cassava-oil palm intercropping (COPI) during the initial 5-year establishment phase. Secondary national data were analyzed to quantify crop yields, carbon footprint, carbon sequestration, and inclusive income (incorporating crop revenues, self-employment wages, and potential carbon credits). Results demonstrate that COPI and OPM achieve identical accumulated carbon sequestration (−389.50 tCO₂eq/ha with the same number of palm plants, with carbon footprints of 65.07 and 63.57 tCO₂eq/ha, respectively (CM: 30.78 tCO₂eq/ha)). Economically, COPI successfully bridges early-stage cash deficits, achieving the highest cumulative inclusive income (2.95 × 10⁶ THB/ha) and commercial profit (2.93 ×10⁶ THB/ha), outperforming OPM (2.78 × 10⁶ THB/ha and 2.77 × 10⁶ THB/ha) and CM (2.91 × 10⁶ THB/ha for both). Although OPM yields a slightly higher net cash flow (0.77 × 10⁶ THB/ha vs. COPI’s 0.74 × 10⁶ THB/ha), COPI optimizes smallholder livelihood stability via retained household self-employment wages. Overall, integrated intercropping improves smallholder climate resilience and financial stability, providing a scalable model for sustainable tropical agriculture. Full article

The 1st International Online Conference on Environments addresses issues of environmental understanding, management, and restoration. Sessions ranged from general frameworks to a broad area of specific investigations: heavy metal removal using inactive yeast, gadolinium’s aquatic toxicity, adsorptive removal of pollutants, energy recovery from waste and wastewater treatment, recycled carbon fibers, climate-resilient urban development, renewable biofuel production, green hydrogen, anthropogenic and volcanic CO₂ emissions, quantifying aging dignity in urban ecosystems and stray dogs as pollution health sentinels. Keynotes covered digital plant phenotyping for restoration, microplastic dynamics, agricultural residue management, carbon credits, air quality, atmospheric pollution, transitional waters, green chemistry, ecotoxicity, micropollutants, and coastal darkening effects on plankton, among others. Applied solutions included phytoremediation of eutrophication in urban streams, circular approaches in aquaculture, biochar for wastewater treatment, AI-assisted mangrove monitoring, and true-cost accounting for food systems. The conference demonstrated that effective environmental policy requires the integration of laboratory findings, field restoration, and shared resource responsibility across terrestrial and marine ecosystems. Full article

Promoting the adoption of climate-smart agricultural technologies (CSATs) is essential for food security and achieving the Sustainable Development Goals (SDGs). However, adoption rates remain low. The objective of this study is to reveal the associations between financial instruments and farmers’ adoption of CSATs. Using survey data from 1219 farmers in climatic transition zone of China, the Probit model, and mediation model were used to empirically test the associations of credit and insurance on farmers’ adoption of CSATs. The results show that both credit and insurance are positively associated with CSATs adoption, with insurance exhibiting a stronger marginal effect than credit. Mediation analysis reveals that credit and insurance are positively associated with farmers’ adoption behavior through attending technical training, strengthening subjective norms, and improving risk attitudes. Heterogeneity analysis indicates that these associations vary significantly across different climatic sub-regions. The findings provide evidence-based policy insights for leveraging targeted financial instruments to accelerate CSATs adoption among smallholders in China and other countries. Full article

The growing urgency of climate change, environmental sustainability, and financial resilience has led to increased global interest in green finance as a tool for achieving sustainable economic development. However, the existing research lacks a comprehensive empirical framework integrating multiple green finance mechanisms and examining their collective influence on the sustainable performance of financial institutions across environmental, social, and economic dimensions, particularly in emerging economies. This study is grounded in institutional theory, the resource-based view, diffusion of innovation theory, and the cost-efficiency approach. It develops and empirically tests a model in which green bonds, green bank loans, carbon credit financing, sustainable agricultural financing, green microfinance, energy-efficient financing, renewable energy financing, and environmental impact financing determine green finance. Green finance, in turn, enhances the sustainable performance of financial institutions across environmental, social, and economic dimensions in Saudi Arabia. This study employs Partial Least Squares–Structural Equation Modelling to analyse survey data collected from 384 employees in Saudi financial institutions. The results show that all eight green finance mechanisms significantly contribute to green finance, which in turn significantly enhances the sustainable performance of financial institutions. This study makes a significant theoretical contribution by developing and validating measurement items for nine green finance constructs and empirically testing a comprehensive model that explains how green finance mechanisms enhance the sustainable performance of financial institutions. This study provides one of the first comprehensive empirical analyses in Saudi Arabia of green finance’s role in promoting sustainable financial strategies aligned with the United Nations Sustainable Development Goals. The findings offer a strong foundation for future research and provide valuable insights for policymakers, financial regulators, and industry leaders in advancing sustainability-focused financial decision-making and policy reforms. Full article

Brazil’s agricultural sector is characterized by persistent productive duality: a technologically advanced export-oriented segment coexists with a large stratum of smallholders generating low economic returns. Understanding the economic determinants of this gap requires moving beyond individual farm surveys toward systemic, nationally representative evidence. This study examines the socioeconomic drivers of sustainable technology adoption and their effect on the Gross Value of Production (GVP) in Brazilian agriculture, using data from the 2017 Agricultural Census aggregated to 558 micro-regions and Partial Least Squares Structural Equation Modeling (PLS-SEM). Unlike prior survey-based studies, the census-based approach reduces sample selection bias relative to small-sample surveys and supports a macro-level, ecological analysis grounded in complete census coverage. The structural model explains 69.2% of the variance in technology adoption (R²adj = 0.692) and 47.4% of the variance in GVP (R²adj = 0.474). The results show that rural cooperatives are the dominant institutional mechanism driving both credit access (β = 0.733) and technical assistance (β = 0.746), with effect sizes far exceeding those of individual-level factors. Access to technical information (β = 0.215) and technology adoption itself (β = 0.179) also positively influence GVP. These findings indicate that overcoming productive duality requires a systemic policy approach centered on rural cooperativism, digital connectivity, and institutional capacity. Full article

The management of organic waste in high-altitude mining poses a distinctive circularity challenge: waste is generated at sites decoupled from agricultural systems, while the same operations are legally required to revegetate the land they disturb. This study provides, to the best of our knowledge, the first primary-data environmental characterization of a real system that valorizes dining-facility organic waste from a high-altitude mining unit in northern Peru into a solid biofertilizer and a liquid biol, both applied in situ for land reclamation. Unlike methanogenic digesters, the system operates under a lactic (acidogenic) fermentation regime inoculated with effective microorganisms and does not recover biogas. A cradle-to-gate life cycle assessment (ISO 14040/14044) with Monte Carlo uncertainty propagation was combined with a well-established family of five circular economy indicators, adapted to the non-energy-recovery case by redefining the Energy Self-Sufficiency Ratio (ESSR) and the Decarbonization Circularity Indicator (DCI). The principal contribution is methodological: the framework is extended to a circularity archetype that previous, biogas-centered formulations could not represent, showing that a system can close its material and nutrient loops robustly (WVI = 0.97) while the energy loop is absent by design (ESSR = 0). The climate result is conditional and is a first-order greenhouse-gas (GHG) screening balance, not a physical carbon-sequestration claim: under the upper-bound assumption of full fertilizer substitution, the avoided fertilizer credit outweighs non-methane process emissions only below a narrow fugitive-methane threshold (≈0.32 kg CH₄ per ton), a margin that narrows further once agronomic equivalence is discounted. The measured product acidity suggests that this condition is plausible, but, because methane was not measured directly, the low-emission interpretation is presented as a hypothesis requiring confirmation rather than as a demonstrated result. The environmental burden is driven by material and electricity inputs—chiefly the polypropylene containers and grid electricity—rather than by the biological process, which broadens the set of improvement priorities beyond methane management to include capital-good reuse and electricity decarbonization, without implying that methane can be neglected. Full article

The natural disasters caused by climate change are increasingly threatening the livelihood sustainability of rural households. How to enhance the adaptability of farmers has become a major issue that urgently needs to be addressed in rural development. An increasing amount of research suggests that the digital transformation in rural areas may provide solutions to this problem. This study selected large sample data from the China Family Panel Studies (CFPS) from 2014 to 2020 to empirically test the role of digital economy in mitigating the adverse impact of natural disasters on livelihood resilience of rural households in China. The empirical results indicate that although natural disasters have a significant negative impact on the livelihood resilience of rural households, the embedding of digital technology can alleviate this negative impact to some extent by expanding non-agricultural employment opportunities for rural households, enhancing households’ access to credit, and improving agricultural production strategies. During this process, the buffering capacity, self-organization ability, and learning ability of rural families have been significantly improved. Moreover, the mitigating effect of the digital economy exhibits heterogeneity. It is more pronounced in the central and western regions than in the eastern regions, and also more evident among high-income families relative to low-income families. The key to improving the benefits of digital technology may lie in tailored policy interventions and digital skills training for farmers. Finally, this study provides empirical evidence from rural China on the role of the digital economy in strengthening farmers’ adaptive capacity against disaster risks. While these findings are context-specific, they may still provide valuable insights for other agriculture-dependent developing countries facing persistent climate risks. Full article

Digital agricultural service platforms are transforming rural financial systems by converting public data into actionable credit intelligence, yet the mechanisms underlying this value creation process remain under-theorized. This study employs grounded theory to investigate Longjiang Nongtou in China, with comparative insights from CropWizard in the United States. Based on semi-structured interviews with platform operators, technical staff, bank loan officers, smallholder farmers, and government officials, supplemented by secondary data, we develop a three-stage value creation model comprising data aggregation, credit profiling, and value integration. Our findings reveal that reducing transaction costs through sequential stages—information asymmetry, search and evaluation costs, and contracting and enforcement costs—constitutes the core mechanism enabling rural financial inclusion. A cross-national comparison demonstrates that divergent institutional environments generate two distinct value pathways: credit empowerment for smallholders versus knowledge-based agronomic services. This study offers a processual theoretical framework for data-driven agricultural platforms, extends transaction cost theory to digital agriculture by specifying sequential mechanisms of cost reduction, and provides practical implications for platform operators and policymakers seeking to advance sustainable rural development. It should be noted that CropWizard is examined as a contrasting secondary case based on publicly available documentation, rather than as an equally grounded empirical case. Full article

Background: This study analyses the predictive causal relationships between sesame supply chain performance, participatory governance, and domestic credit to the private sector in Chad. In Sahelian economies, agricultural value chains continue to be subject to structural constraints relating to limited access to finance and substandard institutions. Therefore, understanding the interactions between local governance, productive finance and agricultural performance is essential for guiding public policy. Methods: This analysis uses annual data from 2002 to 2021. Sesame production serves as an indicator of supply chain performance, while participatory governance is assessed using a composite index based on citizen participation, government effectiveness, and regulatory quality. The study applies the Granger causality test in the Toda–Yamamoto sense. Results: The findings reveal unidirectional causality from participatory governance to sesame production. The findings also reveal bidirectional causality between domestic credit to the private sector and sesame production. No direct causality was observed between participatory governance and private credit. Impulse response functions confirm that institutional and financial effects on production manifest themselves gradually over time. Conclusions: These results imply that sustainable development of the sesame sector in Chad necessitates an integrated strategy combining stronger local governance, improved access to private finance, and agricultural value chain modernisation. Full article

Accurate default risk prediction for agricultural loans is a prerequisite for balancing financial inclusion and safety in rural finance, yet traditional assessment methods have a limited capacity to capture exogenous variables such as climate risk. To this end, this paper constructs a credit risk prediction framework integrating multi-source remote sensing data with explainable machine learning to optimize the credit profile of agricultural loans. Controlling for conventional agricultural loan variables, a logistic regression model examines the statistical association between multi-source remote sensing features and farmers’ default risk. A comparative analysis of multiple machine learning models further demonstrates that incorporating remote sensing data helps improve prediction accuracy, with temperature and precipitation volatility emerging as the most important remote sensing predictors, capturing the predominant climate-related variations in default prediction. Analysis using the Explainable Boosting Machine (EBM) quantifies the contribution of these variables to default risk prediction and identifies notable interaction patterns between remote sensing indicators and traditional agricultural loan variables. Full article

Emerging economies face crucial challenges around fiscal stability, particularly servicing foreign debt and securing long-term financing arrangements. In this context, we investigated the relationship between the share of banking facilities allocated to various economic sectors, the growth of public revenues and the proportion of long-term loans relative to total foreign debt in Jordan. Using data from 2008: Q1 to 2022: Q4 and employing two regression models along with the Vector Error Correction model, key findings reveal that the share of banking facilities allocated to total financing positively impacts public income and reduces long-term liabilities (LRL). Additionally, the positive effect of direct credit from financial institutions on real GDP and public income is associated with a negative impact on LRL. Conversely, direct credit from financial corporations negatively influences real GDP and public income while positively affecting LRL. Direct credit from public sector financing exhibits an inverse relationship with economic growth and public income, leading to a positive association with LRL. The statistically significant error correction coefficients indicate that short-run deviations are corrected toward the long-run equilibrium, with the first model showing a faster but oscillatory adjustment process and the second model exhibiting a slower and more gradual return to equilibrium. These findings suggest that developing countries like Jordan must prioritize banking facilitation for sectors such as industry, tourism, and agriculture to facilitate debt repayment. Full article

This study provides a structured operational-to-financial roadmap for soil organic carbon (SOC) sequestration in mineral soils as a specific carbon-farming pathway. It integrates SOC management; Monitoring, Reporting, and Verification (MRV) execution; financial recognition; and farmer adoption barriers. A comparison of carbon farming pathways is first presented to investigate their strengths and limitations, highlighting the specific importance of SOC management in mineral soils. For high-integrity carbon accounting, SOC gains should be assessed not only for quantity, but also for additionality, permanence, uncertainty, leakage, lifecycle emissions, and transparent verification. Credible MRV frameworks operationalize this logic: monitoring quantifies SOC changes, reporting ensures transparency, and verification provides independent assurance for carbon credit issuance and financial recognition. However, MRV execution faces several challenges, including high spatial variability of SOC, slow accumulation rates, methodological uncertainty, and high costs that limit scalability and reduce trust among stakeholders. Financial incentives are available from both public and private sources, supporting long-term soil carbon stabilization, verified carbon removals, and corporate insetting projects. Yet, adoption remains constrained by uncertain payments, poor transparency, contract and permanence concerns, as well as learning and operational costs for farmers. Addressing these bottlenecks is essential for transforming mineral-soil SOC sequestration into a scalable, high-integrity climate and economic opportunity. Full article

Against the backdrop of rising global economic uncertainty and growing risks in agricultural supply chains, strengthening supply chain resilience has become essential for safeguarding national food security and advancing high-quality agricultural development. As a governance-optimizing force, the role of patient capital (e.g., through long-term credit and institutional investor participation) in shaping agricultural supply chain resilience merits systematic investigation. Drawing on panel data from 895 Chinese listed agricultural enterprises (2010–2024), this paper examines the association between patient capital and agricultural supply chain resilience and explores variables consistent with potential mechanisms. The results show that patient capital is positively associated with agricultural supply chain resilience, with evidence consistent with three possible mechanisms: improving internal management efficiency, advancing digital-intelligent transformation, and strengthening collaboration capabilities. Heterogeneity analyses reveal that this positive association is more pronounced among non-chain-leader enterprises, firms with low supply chain transparency, and those exhibiting a strong bullwhip effect. Further analysis indicates that strong ESG performance and high green total factor productivity strengthen the positive association between patient capital and agricultural supply chain resilience. This study provides enterprise-level evidence regarding the potential role of patient capital in promoting more efficient, modern, and sustainable agricultural supply chains. Full article