Search Results (225)

India faces large, persistent yield gaps across eight major crops—wheat, rice, maize, soybean, pulses, mustard, cotton, and sugarcane—that collectively limit food security and rural income. This review synthesises evidence from over 100 peer-reviewed studies (1990–2024) to provide the first comprehensive, multi-crop, agro-climatically resolved yield gap analysis for India. Applying the three-tier framework of potential yield ($Y_p$), attainable yield ($Y_a$), and farmer yield ($Y_f$), exploitable yield gaps are quantified at national and agro-climatic zone level, ranked limiting factors are identified, and projected climate change impacts are assessed. Yield gaps range from 20 to 35% in irrigated rice of the north-western Indo-Gangetic Plain to 60–75% in rainfed cotton and pulses of the semi-arid tropics. Yield gaps of blackgram across 20 major districts average 515 kg ha⁻¹, driven by moisture stress, biotic pressure, and management constraints. Nitrogen management, irrigation access, variety adoption, and sowing-date optimisation collectively explain 80–85% of exploitable gaps, while nitrogen and irrigation alone account for 40–58%. Closing 50% of exploitable yield gaps could add approximately 100 million tonnes of food grain annually without expanding cultivated area, directly supporting Sustainable Development Goal (SDG 2). However, climate change is projected to widen yield gaps of rainfed rice by 15–30% by the 2040s under Representative Concentration Pathway (RCP) 8.5. Beyond this crop-by-crop synthesis, the review proposes a constraint-transition framework in which the dominant type of limiting factor shifts predictably from biophysical (water, climate) in the largest-gap rainfed systems to agronomic management (nitrogen, sowing date, variety) at intermediate gap levels and to institutional and socioeconomic constraints (credit, extension, land tenure, gender) as gaps narrow in the best-resourced irrigated systems, thus offering a conceptual lens for prioritising interventions by development stage rather than by crop alone. Full article

Consumer trust is critical to the sustainable development of cross-border B2C e-commerce platforms. Accurately evaluating and diagnosing trust weaknesses has become a key concern for both practitioners and researchers. To address the inherent limitations of existing trust evaluation methods, this study proposes an improved AHP-Ridge Regression hybrid model that integrates expert knowledge with actual consumer perception data. First, an improved Analytic Hierarchy Process based on stakeholder-oriented nonlinear programming is employed to optimize the evaluation weights of nine experts, reduce subjective bias, and generate expert prior weights for each dimension and indicator. Second, these prior weights are incorporated as the regularization prior mean of the Ridge Regression model to construct the improved AHP-Ridge Regression model. Based on survey data from 387 valid respondents across five major cross-border platforms (Tmall Global, JD International, Pinduoduo Global, Sam’s Club Global, and CDFG Duty-Free), the model is compared with six baseline models using a 30-times repeated five-fold nested cross-validation. The proposed model achieves the lowest RMSE (0.3179) and highest R² (0.6510) among all compared models, with statistically significant improvements over all baselines (Nadeau–Bengio-corrected p < 0.001, large Cohen’s d effect sizes). However, the improvement over conventional Linear Regression is modest in absolute magnitude (ΔRMSE ≈ 0.0012). The primary value of the proposed model lies not in a dramatic leap in predictive accuracy but in its theoretical grounding, interpretability, and diagnostic capability. Permutation importance analysis reveals that Platform Fluidity, AI Technology Usability, Page Layout & Navigation Clarity, Content Accuracy, and Policy Assurance are the most important predictors of consumer trust. Comprehensive calibration and residual diagnostics (including MAE, normality tests, and heteroscedasticity checks) confirm the model’s predictive reliability. Furthermore, platform-specific diagnostics identify three distinct trust profiles (high-trust benchmark, trust-improvement priority, and mixed-profile platforms), providing managers with actionable insights for resource allocation. This study offers cross-border B2C e-commerce platforms a trust evaluation tool that balances predictive accuracy and interpretability, and provides implications for sustainable platform governance and ESG-oriented management by linking trust diagnostics with platform accountability frameworks. Full article

As an emerging form integrating digital finance and green finance, Green Digital Finance (GDF) serves as a critical driving force for consumption structure upgrading (CSU) and coordinated regional development. Based on panel data of 30 provincial-level regions in China from 2011 to 2023, this paper systematically investigates the enabling effect of GDF on CSU from the dimensions of spatial spillover effects, transmission mechanisms, income thresholds, and urban-rural heterogeneity. The empirical results show that the local effect of GDF on CSU is 0.057 and the spatial spillover effect is 0.094, with the spillover effect exerting significant impacts only in the short run. GDF functions by raising residents’ income, advancing industrial structure upgrading and easing credit constraints. A single income threshold exists at the income level of 23,414.25 yuan; after crossing this threshold, both the local driving effect and spatial spillover effect are significantly strengthened. Furthermore, GDF generates more pronounced driving effects on developmental consumption and rural areas. This study provides empirical evidence and implications for optimizing the allocation of regional financial resources and formulating differentiated policies. 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

This paper studies the impact of weather shocks on the credit risk of bank portfolios in small and rural municipalities in Colombia, which are highly vulnerable to these climate variations. It addresses the relationship between extreme temperature and precipitation events and the increase in the proportion of loans at risk, using data from 2011 to 2023. Extreme climate shocks negatively affect loan portfolio quality in Colombian rural municipalities, especially in microcredits. Credit risk decreases in municipalities with higher per capita incomes. It varies according to the type of loan and the nature of the weather shock. The results show that low temperature shocks increase risk in commercial and consumer loans. In contrast, low-precipitation shocks increase risk in microcredit. The increasing importance of climatic disturbances stresses the need for banks to develop their own models to manage these risks and to deepen analysis that incorporate borrower-specific information and banking policies to protect both financial institutions and borrowers from the impacts of climate change. The integration of sustainable practices and climate education can be key to improving financial resilience in these vulnerable areas. 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

Food insecurity remains a structural impediment to rural welfare in sub-Saharan Africa (SSA), with smallholder farming households in northern Nigeria among the most severely affected. This study examined the socioeconomic determinants of food security among farming households in Kano State, Nigeria, with emphasis on the role of institutional credit access, using the Food Consumption Score (FCS) methodology. Data were collected through semi-structured face-to-face interviews using multi-stage cluster sampling and analyzed using descriptive statistics, chi-square analysis, one-way ANOVA, and multiple linear regression. Slightly fewer than half of the sampled households met the food-secure threshold, and food security status was significantly associated with the level of access to institutional credit, with a noticeable gap in food security status between high-access and no-access households. Multiple regression confirmed that access to institutional credit, farming experience, and farm size were significant and positive determinants of food security, while household size was a significant negative determinant. These findings demonstrate that institutional credit is an important, policy-actionable pillar of rural food security in Kano State Nigeria, best pursued alongside corresponding investments in farmer experience-transfer, land access, and household welfare. 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

The co-pyrolysis of waste sawdust and non-recyclable polypropylene at 500 °C was investigated for low-cost adsorbent production and solid waste valorization in rural Thailand. Sustainability was evaluated through techno-economic analysis, gate-to-gate environmental screening, CO₂ emission accounting, adsorption cost analysis, and social return on investment assessment. The sawdust–polypropylene biochar produced at 500 °C production system requires a total capital expenditure of 46,000 THB and achieves a unit production cost of 316 THB kg⁻¹ at a 35% w/w biochar yield, 7–14 times lower than commercial granular-activated carbon and powdered-activated carbon. Based on a hypothetical community-scale deployment scenario, the estimated capital expenditure payback period under in-house granular-activated carbon substitution falls below six months. All annual techno-economic and SROI results presented in this study represent scenario-based screening estimates and should not be interpreted as demonstrated community-scale performance. Gate-to-gate environmental screening estimated gross production emissions of 8.771 kg CO₂e kg⁻¹ SPB-500. A consequential waste-diversion scenario incorporating carbon sequestration and avoided-disposal credits yielded a hybrid scenario-based net greenhouse-gas balance of +3.082 kg CO₂e kg⁻¹ SPB-500, supporting its potential application under the evaluated scenario of approximately 0.4–5.9 kg CO₂e kg⁻¹ relative to commercial-activated carbon benchmarks. Social return on investment analysis yields a base–case ratio of 1.39:1 (five-year total present value: 6,025,841 THB; minimum across sensitivity scenarios: 1.13:1), with water quality improvement (SDG 6; 46.1%) and health risk reduction (20.7%) jointly accounting for 66.8% of monetized outcomes, confirming investment justification from public health benefits alone. Quantifiable alignment is demonstrated across five UN Sustainable Development Goals. Collectively, these findings suggest that SPB-500 co-pyrolysis has the potential to be an economically accessible and socially beneficial waste-valorization technology under the evaluated scenario, supporting its potential application in decentralized heavy-metal remediation in resource-constrained communities. Full article

Sustainable rural development requires households to move beyond defensive medical spending and emergency borrowing toward more productive, forward-looking resource allocation. This study uses panel data from the China Household Finance Survey (CHFS), covering the 2017, 2019, and 2021 waves plus a newly released 2023 green-channel wave. We examine whether improvements in safe drinking water, clean cooking energy, and sanitation are associated with lower rural household economic vulnerability. We employ a staggered difference-in-differences design with household and year fixed effects, complemented by event–study tests, mediation analysis, and robustness checks. Environmental infrastructure improvements are significantly associated with lower child hospitalization and out-of-pocket medical expenditure, reduced reliance on high-cost informal credit, and higher income-generating asset shares. Mechanism analysis supports a “health–credit–income” channel, in which environmental improvements reduce preventable health shocks, ease emergency borrowing, and relax liquidity constraints on productive asset allocation. Threshold results further show that these financial-resilience benefits are strongest among households with the lowest baseline resource endowments. The study focuses on rural China, yet the identified health–credit–income mechanism offers a broader, scalable framework. Environmental infrastructure first reduces preventable disease burden, then eases emergency informal borrowing, and finally frees liquidity for income-generating assets. This sequence helps explain how environmental investment can create the financial preconditions for sustainable consumption and investment across developing economies. These findings offer micro-level evidence for integrating environmental infrastructure, rural financial resilience, and ESG social-value assessment. Full article

This study analyses the economic performance, sustainability, and resilience of family farming systems in São Tomé and Príncipe, using an approach that combines quantitative and qualitative data. Primary data were collected through a survey of 50 rural families from the seven districts of the country, focus group discussions, and field observations. Quantitative analysis included descriptive statistics and exploratory comparative procedures, complemented by economic evaluation, while thematic analysis examined the qualitative data. The findings reveal diversified agroforestry systems, integrating up to 33 crops and small-scale livestock production. At the individual and aggregate levels, agroforestry shows viable economic performance, with a net profit margin of 57.4%, capable of generating income and marketable surpluses. This improves rural livelihoods, strengthens resilience to climate and market shocks, and supports both subsistence and market-oriented production. Despite these strengths, structural constraints persist, including fragile value chains, limitations in access to credit and markets, low technology adoption, and climate vulnerability. Human capital, particularly education, emerges as a key factor in improving productivity and value creation. Integrated policies on access to resources and education are needed to promote diversification, multi-activity, and market integration as central strategies for increasing sustainability, food security, and risk reduction in family farming. Full article

Against the backdrop of the growing alignment between green agricultural transformation and rural land system reform, how stable land tenure promotes farmers’ adoption of green production technologies has become an important issue in achieving high-quality agricultural development. Using 2024 survey data from 1117 farm households in Inner Mongolia under China’s second-round land contract extension policy, this study applies Poisson regression and mediation models to examine how land tenure stability affects farmers’ adoption of green production technologies. The results show that legal, factual, and perceived tenure stability, measured by second-round contract extension signing, no land disputes since the second round, and expectations of no future land adjustment, all significantly promote adoption. Tenure stability promotes adoption through higher income, better credit access, stronger benefit expectations, and greater risk-coping capacity, reflecting both economic and psychological effects. Its positive effect is stronger among small-scale farmers and those with lower-quality cultivated land. Policy efforts should not only prudently advance the second-round land contract extension, but also strengthen tenure security in practice and coordinate support for green production, rural finance, and risk protection. From a multidimensional land tenure stability perspective, this study provides new empirical evidence on how rural land reform translates into green behavioral responses. Full article

In sub-Saharan Africa, the sustainability of smallholder farming systems is threatened by climate change. Women farmers are often disproportionately affected. These disproportionate impacts are linked to gender-based inequities like limited decision-making power and resource constraints, which limit women’s adaptive capacity. Previous research has examined inequities in agriculture generally, as well as women farmers’ adaptation to climate change. However, relatively few studies have explicitly focused on the experiences of women who are the primary farmers. Intersectional research is also limited. This paper presents the results of a scoping review to identify how climate change affects women smallholder farmers and how they adapt. The review identified 41 studies between 2014 and 2024. The most frequently identified vulnerability factors were access to credit, social and cultural norms, and land issues (e.g., tenure issues). Few studies took an explicitly intersectional approach. The findings suggest the need for support that targets the challenges faced by women smallholders. More intersectional research is needed to examine how gendered impacts are shaped by other forms of inequality and inhibit sustainable livelihood options. The review revealed a pervasive patriarchal assumption in which dual-headed households are often described as “male-headed”. Revising such discourses can support women’s adaptive agency in the face of future climate challenges. These findings have direct implications for the sustainability of smallholder farming systems and rural livelihoods in the region, emphasizing the need for gender-responsive approaches to sustainable development in sub-Saharan Africa. Full article

Farmer Producer Organizations (FPOs) have gained increasing attention as institutional mechanisms for improving the resilience of smallholder farming systems under changing climatic conditions. This study examines the role of FPOs in promoting the adoption of Climate-Smart Agriculture (CSA) practices, improved irrigation strategies, and sustainable land management in the arid region of Pali district, Rajasthan, India. A comparative assessment was conducted between FPO-associated member and non-member farmers to evaluate differences in climate change perception, adoption behaviour, and adaptive capacity. The study employed a mixed-methods research design using primary data collected from 408 farm households through structured interviews, focus group discussions, and key informant consultations. Descriptive statistics, mean comparison tests and regression analysis were used to examine adoption patterns and identify the major factors influencing farmers’ responses to climate risks. The findings indicate that delayed rainfall, rising temperatures, and increasing drought frequency are widely perceived by farmers as major threats to agricultural production. FPO membership was associated with higher levels of climate-risk awareness and greater reported adoption of CSA practices; however, these findings should be interpreted as associations rather than causal effects. Farmers linked with FPOs reported stronger uptake of improved and stress-tolerant crop varieties, crop diversification, mixed farming systems, agroforestry, soil moisture conservation, rainwater harvesting, improved irrigation methods, and integrated pest management practices. Education, farm size, access to extension services, market linkages, and climate information were also found to significantly influence adoption decisions. The study highlights the important contribution of FPOs in reducing transaction costs, improving access to inputs, technical knowledge, credit and markets, and encouraging collective responses to climate stress. Strengthening FPO governance, expanding extension support, and targeting vulnerable farmer groups can substantially enhance climate resilience and support sustainable agricultural transitions in arid regions. The findings demonstrate that farmer organizations can serve as effective intermediary institutions linking household-level adaptation strategies with broader goals of irrigation efficiency, land management, and rural sustainability. Full article