Search Results (316)

This study investigates the mechanisms by which green finance mitigates non-point source pollution. Based on provincial panel data from China spanning 2005 to 2023, this study conducts an empirical analysis that yields several key findings: (1) The development of green finance significantly reduces the intensity of agricultural non-point source pollution. (2) Green finance indirectly contributes to pollution reduction by incentivizing farmers to adopt environmentally sustainable production practices. (3) The pollution control effects of green finance are amplified in regions with advanced digital infrastructure. (4) The impact of green finance on agricultural pollution demonstrates a threshold effect associated with regional innovation capacity—only when innovation capability exceeds a certain threshold does the emission reduction effect of green finance become evident. Theoretically, this study broadens the research dimensions of green finance by integrating farmer behavioral factors and revealing boundary conditions related to technology and innovation. Policy implications include the need to tailor green financial products for agriculture, accelerate the development of rural digital infrastructure, and implement innovation-driven differentiated policies to enhance precision. Full article

This study examines the integration and sustainability of solar energy technologies as a tool for rural electrification in Ghana, using the Lofetsume community as a case study. Persistent electricity access deficits in rural areas, coupled with unreliable grid systems and high energy costs, underscore the need for alternative energy solutions. Through semi-structured interviews and surveys, the study explores community perspectives and expert views on the viability of solar energy in rural Ghana. Findings reveal strong grassroots support for solar energy due to its reliability and environmental benefits, despite barriers such as high upfront installation costs and maintenance challenges. The study recommends multi-stakeholder partnerships, innovative financing models, and capacity-building initiatives to enhance solar energy adoption. By prioritizing solar energy technologies, the government, private sector, and local communities can collaborate to develop sustainable and affordable electrification solutions, ultimately improving living standards in remote areas and contributing to Ghana’s broader energy sustainability goals. Full article

Indonesia’s post-mining landscapes require an integrated governance approach to achieve equitable and sustainable reclamation. This study developed and evaluated the TILANG Framework (Triple-Bottom-Line Integrated Land Governance) as a multidimensional model that aligns ecological restoration, community empowerment, and institutional accountability. Based on a meta-synthesis of 773 academic and institutional remarks coded using NVivo 12, the study identified sustainable cacao agriculture as a viable compensation mechanism that supports livelihood recovery while restoring degraded land. The framework draws on six foundational theoretical components—Corporate Social Responsibility (CSR), Stakeholder Theory, Legitimacy Theory, the Theory of Planned Behavior, the Triple Bottom Line, and multi-level governance—and is operationalized through six implementation principles: Trust, Inclusivity, Legitimacy, Alignment, Norms, and Governance. The findings support performance-based land reclamation by embedding behavioral readiness and institutional co-financing into sustainability strategies. This model is particularly relevant to Indonesia’s ongoing land-use transformation, where post-extractive zones are shifting toward agroecological and community-centered recovery. The study found that (1) reframing land compensation as a restorative, performance-based mechanism enables more legitimate and inclusive post-mining governance; (2) sustainable cacao agriculture represents a viable and socially accepted strategy for ecological recovery and rural livelihood revitalization; and (3) the TILANG Framework advances land-use transformation by integrating corporate responsibility, behavioral readiness, and multi-level governance into a cohesive performance model. Full article

Blockchain technology is being increasingly deployed to store and process transactions and information in the global financial sector. Blockchain underpins cryptocurrencies such as Bitcoin and facilitates decentralized finance (DeFi), representing a paradigm shift in the global financial landscape, offering alternative solutions to traditional banking, and fostering financial inclusion. In developing economies such as Morocco, where a significant portion of the population remains unbanked, these digital financial innovations present both opportunities and challenges. This study examines the potential role of cryptocurrencies and DeFi in enhancing financial inclusion in Morocco, where cryptocurrencies have been banned since 2017. However, the public continues to use cryptocurrencies, circumventing restrictions, and the Moroccan Central Bank is now preparing to introduce new regulations to legalize their use within the country. In this context, this article analyses the potential of cryptocurrencies to mitigate barriers such as high transaction costs, restricted access to financial services in rural areas, and limited financial literacy in the country. The study pursues a mixed-methods approach, which combines a quantitative survey with qualitative expert interviews and adapts the Unified Theory of Acceptance and Use of Technology (UTAUT) model to the Moroccan context. The findings reveal that while cryptocurrencies offer cost-efficient financial transactions and improved accessibility, their adoption may be constrained by regulatory uncertainty, security risks, and technological limitations. The novelty of the article thus lies in its focus on the key mechanisms that influence the adoption of cryptocurrencies and their potential impact in a specific national context. In so doing, the study highlights the need for a structured regulatory framework, investment in digital infrastructure, and targeted financial literacy initiatives to optimize the potential role of cryptocurrencies in progressing financial inclusion in Morocco. This underscores the need for integrated models and guidelines for policymakers, financial institutions, and technology providers to ensure the responsible introduction of cryptocurrencies in developing world environments. Full article

The export expansion of wood forest products (WFPs) generates substantial socio-economic benefits. Unfortunately, the WFP manufacturing industry frequently experiences challenges in accessing finance and high financing costs. Since profit scramble between financial sector and real economy sectors has become a critical global concern, it is worth investigating how banking sector profits (BSPs) impact WFPs’ export margins, and whether a “financial concession” policy can mitigate or amplify this effect. Drawing on over four million trade records from China’s Customs Database and the United Nations Trade and Business Database, this study quantifies the WFPs’ export margins of 31 provinces in Mainland China to 184 countries during 2007–2022. Then it assesses the effects of regional BSP on the WFPs’ export margins. The results indicate that the extensive, intensive, and quantity margins of WFPs’ export exhibit an overall upward trend with fluctuations, while the price margin has shown steady growth since 2016. Regional BSP has significant negative effects on the extensive, intensive, and quantity margins. The observed upward trend of WFPs’ export margins implies that low BSP may facilitate export growth of WFPs. Further heterogeneity analysis indicates that the BSPs’ negative impact is more pronounced for labor-intensive WFPs’ exports. China’s “financial concession” policy effectively mitigates the BSPs’ adverse effects. Moderation effect analysis demonstrates that a larger number of bank institution outlets, a higher share of rural bank institution outlets, and the development of digital finance significantly reduce the BSPs’ negative effects. Full article

As the primary force driving the sustainable development of the rural economy, the improvement of the total factor productivity (TFP) of agricultural enterprises (AEs) is of great strategic significance. This study innovatively zeroes in on AEs, leveraging micro-level data from agricultural listed companies in China’s A-share market spanning from 2007 to 2023. It aims to investigate the impact of supply chain finance (SCF) on the TFP of these enterprises and elucidate the underlying mechanisms. Uniquely, this study incorporates enterprise digital transformation and innovation capability as moderating variables into the mechanism analysis framework. Furthermore, it examines the heterogeneous effects across different characteristics of AEs. The findings reveal that SCF significantly boosts the TFP of AEs. Specifically, a one-standard-deviation increase in the level of SCF is associated with a 0.2658% increase in TFP relative to the mean. This conclusion holds robustly across various tests. Moreover, the interaction terms of SCF with both enterprise digital transformation and innovation capability are significantly positive. This indicates that greater digital transformation and stronger innovation capability amplify the positive effect of SCF on TFP. The heterogeneous analysis further indicates that for AEs with highly optimized human capital, higher financing constraints, and more efficient credit resource allocation, the positive impact of SCF on TFP is particularly pronounced. Full article

Addressing the outflow of rural labor remains central to achieving inclusive and sustainable development in many emerging economies. This study investigates how rural e-commerce—encompassing both trade- and finance-oriented platforms—affects local employment dynamics. Drawing on panel data from 28 Chinese provinces between 2012 and 2020, we construct a composite index of rural e-commerce development and apply a two-way fixed-effects model to assess its impact on labor retention. Based on a nationwide regression analysis of Chinese survey data, we find that rural e-commerce significantly increases intra-county employment, with estimated effects robust across model specifications. Specifically, a one-unit increase in the e-commerce development index is associated with a 0.1 increase in the likelihood of local labor retention, significant at the 1% level. However, benefits are unevenly distributed: positive impacts are concentrated in eastern and central regions, while western provinces experience adverse effects, and northeastern areas show no significant change. These findings underscore the role of rural e-commerce as a driver of digital inclusion and local economic resilience, while also revealing structural barriers that hinder equitable access to its benefits. By identifying the enabling conditions, this study contributes to a more context-sensitive understanding of how platform economies can support spatially balanced and socially just rural development. Policies that promote rural e-commerce are thus likely to facilitate the local redeployment of rural labor. Full article

Background: Health inequality is seen as a challenge for implementing the Healthy China Strategy. This study analyzes the income-related health inequality among urban–rural resident basic medical insurance (URRBMI) participants. Methods: This study utilized data from the 2019 China Household Finance Survey (CHFS), and the concentration index (CI) was employed to estimate the effects of income-related health inequality on participants. Results: Our findings provide clear evidence that health inequality among participants has fluctuated—narrowing, widening, and then narrowing again—in the areas of the contribution, medical treatment, and reimbursement of URRBMI, respectively. Overall, the analysis indicates a widening of health inequality post-reimbursement, with results remaining consistent. A heterogeneity analysis shows that health inequality is most pronounced among women and those with less than a middle school education. Finally, our study reveals a pro-rich trend in the actual utilization of medical services among participants, with persistent disparities in outpatient and inpatient service usage even after standardization, further exacerbating income-related health inequality. Conclusions: We recommend that the URRBMI design take participants’ income levels into account, with policies favoring disadvantaged individuals to enhance their medical security, improve access to healthcare services, and ultimately reduce health inequality. Full article

The increasingly observable financial vulnerability of households in emerging market countries makes it imperative to investigate the factors influencing it. Considering that China stands as a representative of emerging market economies, analyzing the factors influencing household financial vulnerability in China presents great reference significance for the sustainable development of households in emerging market countries. Using data from the China Household Finance Survey (CHFS) household samples, this paper presents the regional distribution of households with financial vulnerability in China. Utilizing machine learning (ML), this research examines the factors that influence household financial vulnerability in China and determines the most significant ones. The results reveal that households with financial vulnerability in China takes up a proportion of more than 63%, and household financial vulnerability is lower in economically developed coastal regions than in medium and small-sized cities in the central and western parts of China. The analysis results of the SHAP method show that the debt leverage ratio of a household is the most significant feature variable in predicting financial vulnerability. The ALE plots demonstrate that, in a household, the debt leverage ratio, the age of household head, health condition, economic development and literacy level are significantly nonlinearly related to financial vulnerability. Heterogeneity analysis reveals that, except for household debt leverage and insurance participation, the key characteristic variables exerting the most pronounced effect on financial fragility differ between urban and rural households: household head age for urban families and physical health status for rural families. Furthermore, digital financial inclusion and social security exert distinct impacts on financial vulnerability, showing significantly stronger effects in high per capita GDP regions and low per capita GDP regions, respectively. These findings offer valuable insights for policymakers in emerging economies to formulate targeted financial risk mitigation strategies—such as developing household debt relief and prevention mechanisms and strengthening rural health security systems—and optimize policies for household financial health. Full article

Climate risk has emerged as a pressing global challenge, significantly undermining livelihood capital, income stability, and living standards among vulnerable populations. Leveraging balanced panel data from the China Household Finance Survey (CHFS) spanning 2013–2019, this study employs a binary Logit fixed-effects model to examine how climate change risk affects farm households’ multidimensional relative poverty, with particular attention to the moderating role of digital financial inclusion. The findings demonstrate that climate change risk significantly exacerbates multidimensional relative poverty among farm households, while digital inclusive finance effectively mitigates these adverse impacts. Notably, subdimensional analysis reveals that the depth of digital financial usage exerts the strongest influence. In addition, there is heterogeneity in this moderating effect, with digital inclusive finance having a more significant mitigating effect on multidimensional relative poverty in rural households in the central region, with middle and higher incomes, as well as with high digital literacy. This study provides valuable insights into the use of financial instruments to mitigate climate risks, improve the climate resilience of rural populations, and strengthen multidimensional approaches to poverty governance. Full article

Tropical pasture degradation represents a major challenge for global food security and environmental conservation, particularly in Brazil, where up to 60% of pastures are degraded. This study evaluates the economic viability of recovery of degraded pastures using an integrated crop–livestock–forest (ICLF) system. A representative 2-hectare system in the Brazilian Cerrado was analyzed, featuring native Dipteryx alata trees interplanted with pasture for cattle grazing. A deterministic financial model was developed to simulate annual cash flows over a 20-year period under various financing scenarios, including self-financing and multiple subsidized rural credit lines (e.g., Pronaf and Pronamp programs, and ABC Ambiental). The analysis shows that subsidized credit lines with low interest rates and extended grace periods significantly improve project profitability, yielding positive NPVs and robust internal rates of return, while self-financing and high-cost credit options (such as Pronaf Mulher) result in negative NPVs. The dual cash flow strategy—where borrowed funds are immediately invested in secure fixed-income instruments—further enhances economic performance. The findings demonstrate that ICLF-based pasture recovery is economically viable when supported by appropriate financing, offering a scalable model for sustainable agriculture that delivers both economic and environmental benefits. Full article

Addressing the urgent need for sustainable energy transitions in rural development while achieving the dual carbon goals, this study focuses on resolving critical challenges in agricultural photovoltaic (PV) applications, including land-use conflicts, compound energy demands (electricity, heating, cooling), and financial constraints among farmers. To tackle these issues, a dual-mode cost–benefit analysis framework was developed, integrating two distinct investment models: self-invested construction (SIC), where farmers independently finance and manage the system, and energy performance contracting (EPC), where third-party investors fund infrastructure through shared energy-saving or revenue agreements. Then, an integrated photovoltaic-storage agricultural greenhouse (PSAG) microgrid optimization model is established, synergizing renewable energy generation, battery storage, and demand-side management while incorporating operational mode selection. The proposed model is validated through a real-world case study of a village agricultural greenhouse in Gannan, China, characterized by typical rural energy profiles and climatic conditions. Simulation results demonstrate that the optimal system configuration requires 27.91 kWh energy storage capacity and 18.67 kW peak output, with annualized post-depreciation costs of 81,083.69 yuan (SIC) and 74,216.22 yuan (EPC). The key findings reveal that energy storage integration reduces operational costs by 8.5% compared to non-storage scenarios, with the EPC model achieving 9.3% greater cost-effectiveness than SIC through shared-investment mechanisms. The findings suggest that incorporating an energy storage system reduces costs for farmers, with the EPC model offering greater cost savings. Full article

Objectives: This study evaluates the effectiveness of an innovative, integrated healthcare approach based on the “Long-term Care (LTC) in the Community” pilot project, aimed at testing solutions for the new LTC Act and associated regulations in Slovenia. It is based on a small sample, which can be financed from European project funds. This methodology is crucial for the subordinate legislation derived from the LTC Act. Methods: We selected beneficiaries who decided to receive integrated services in their home environment in rural areas. Among 132 beneficiaries who received various care services at home, 75 beneficiaries received integrated services to maintain independence, while a control group of 57 persons did not receive these despite eligibility. The hypothesis that the new reactivation and other services to strengthen and maintain independence facilitate a transition to a lower category of LTC within the system of different states of abilities and that new approaches with integrated home care are much more successful were tested using the Z + 4 test. Results: Seven out of eight users’ abilities were improved by an inventive approach to LTC at home, including reactivation activities, with p < 0.025. The probability that the new methods will outperform the old ones for an arbitrarily selected senior eligible for LTC exceeded 0.89. Thus, we used quantitative methods to confirm the reasonableness of the decisions included in the LTC Act and will help to estimate savings in the health fund. Conclusions: These positive results promote the implementation of integrated care strategies, norms, and standards, which will be further articulated in subordinate legislation. Full article

Rural finance provides financial support for agricultural production. Agricultural credit, as the most important rural financial resource, is designed to regulate rural economic activity and guide the rational adjustment of the rural economy and industrial structure. However, the relationship between the availability of credit to farmers and their choice of cropping behavior in the agricultural production process remains unexplored in depth. To fill this gap, this study constructs an analytical framework for ‘Agricultural credit-production factor allocation-planting structure decision-making behaviour’. Using data from a large-scale rural survey in China, this paper empirically examines the impact of agricultural credit on the specialization and ‘grain-oriented’ of farm households’ planting structure using the OLS model, the mediated effects model, and the 2SLS model. In addition, this study explores the mechanism of the allocation of agricultural production factors in this process. This has enriched the theoretical and practical research on rural finance for agricultural development. Studies have shown that agricultural credit contributes significantly to the specialization and ‘grain-oriented’ of the planting structure. The findings of the study also show that agricultural credit promotes cropping restructuring among farmers through large-scale operations, technological advancement, and green production. In addition, there are differences in the impact of agricultural credit on the planting structure depending on the type of food-producing area, the scale of operation, the development of digital infrastructure, the education of the head, and the source of credit. These findings suggest that increasing rural financial support and promoting the restructuring of land improvement, agricultural machinery, and green production factors may be an effective path to optimizing the cropping structure and improving the efficiency of production factor utilization. Full article

Weeds cause significant yield and economic losses by competing with crops and increasing production costs. Compounding these challenges are labor shortages, herbicide resistance, and environmental pollution, making weed management increasingly difficult. In response, precision weed control (PWC) technologies, such as robots and unmanned aerial vehicles (UAVs), have emerged as innovative solutions. These tools offer farmers high precision (±1 cm spatial accuracy), enabling efficient and sustainable weed management. Herbicide spraying robots, mechanical weeding robots, and laser-based weeders are deployed on large-scale farms in developed countries. Similarly, UAVs are gaining popularity in many countries, particularly in Asia, for weed monitoring and herbicide application. Despite advancements in robotic and UAV weed control, their large-scale adoption remains limited. The reasons for this slow uptake and the barriers to widespread implementation are not fully understood. To address this knowledge gap, our review analyzes 155 articles and provides a comprehensive understanding of PWC challenges and needed interventions for scaling. This review revealed that AI-driven weed mapping in robots and UAVs struggles with data (quality, diversity, bias) and technical (computation, deployment, cost) barriers. Improved data (collection, processing, synthesis, bias mitigation) and efficient, affordable technology (edge/hybrid computing, lightweight algorithms, centralized computing resources, energy-efficient hardware) are required to improve AI-driven weed mapping adoption. Specifically, robotic weed control adoption is hindered by challenges in weed recognition, navigation complexity, limited battery life, data management (connectivity), fragmented farms, high costs, and limited digital literacy. Scaling requires advancements in weed detection and energy efficiency, development of affordable robots with shared service models, enhanced farmer training, improved rural connectivity, and precise engineering solutions. Similarly, UAV adoption in agriculture faces hurdles such as regulations (permits), limited payload and battery life, weather dependency, spray drift, sensor accuracy, lack of skilled operators, high initial and operational costs, and absence of standardized protocol. Scaling requires financing (subsidies, loans), favorable regulations (streamlined permits, online training), infrastructure development (service providers, hiring centers), technological innovation (interchangeable sensors, multipurpose UAVs), and capacity building (farmer training programs, awareness initiatives). Full article