Search Results (75)

Background/Objectives: Urban green space has been increasingly recognized as a determinant of maternal and child health. This study investigated the association between prenatal exposure to different types of green space and the risk of congenital anomalies in South Korea. Methods: We analyzed data from the National Health Insurance Service (N = 142,422). Green space exposure was measured at the area level and categorized into grassland and forest; statistical analysis was performed using generalized estimating equations and generalized additive models to analyze the associations. Additionally, subgroup and sensitivity analyses were performed. Results: GEE analysis showed that a 10% increase in the proportion of grassland in a residential district was associated with a reduced risk of nervous system (adjusted odds ratio [aOR]: 0.77, 95% confidence interval [CI]: 0.63–0.94) and genitourinary system anomalies (aOR: 0.83, 95% CI: 0.71–0.97). The subgroup analysis results showed significance only for male infants, but the difference between the sexes was not significant. In the quartile-based analysis, we found a slightly significant p-value for trend for the effect of forests on digestive system anomalies, but the trend was toward increasing risk. In a sensitivity analysis with different exposure classifications, the overall and nervous system anomalies in built green space showed that the risk decreased as green space increased compared to that in the lowest quartile. Conclusions: Our results highlight the importance of spatial environmental factors during pregnancy and suggest that different types of green spaces differentially impact the offspring’s early health outcomes. This study suggests the need for built environment planning as part of preventive maternal and child health strategies. Full article

This study aims to develop an optimal underwriting strategy for affordable (H1 and M1) and premium (L1 and M2) electric vehicles (EVs), balancing financial risk and sustainability commitments. The research is motivated by regulatory pressures, risk management needs, and sustainability goals, necessitating an adaptation of traditional underwriting models. The study employs a modified Delphi method with industry experts to identify key risk factors, including accident risk, repair costs, battery safety, driver behavior, and PCAF carbon impact. A sensitivity analysis was conducted to examine premium adjustments under different risk scenarios, categorizing EVs into four risk segments: Low-Risk, Low-Carbon (L1); Medium-Risk, Low-Carbon (M1); Medium-Risk, High-Carbon (M2); and High-Risk, High-Carbon (H1). Findings indicate that premium EVs (L1 and M2) exhibit lower volatility in underwriting costs, benefiting from advanced safety features, lower accident rates, and reduced carbon attribution penalties. Conversely, budget EVs (H1 and M1) experience higher premium fluctuations due to greater accident risks, costly repairs, and higher carbon costs under PCAF implementation. The worst-case scenario showed a 14.5% premium increase, while the best-case scenario led to a 10.5% premium reduction. The study recommends prioritizing premium EVs for insurance coverage due to their lower underwriting risks and carbon efficiency. For budget EVs, insurers should implement selective underwriting based on safety features, driver risk profiling, and energy efficiency. Additionally, incentive-based pricing such as telematics discounts, green repair incentives, and low-carbon charging rewards can mitigate financial risks and align with net-zero insurance commitments. This research provides a structured framework for insurers to optimize EV underwriting while ensuring long-term profitability and regulatory compliance. Full article

Reducing the carbon intensity of well-being (CIWB) is essential for advancing environmental sustainability and socio-economic development. The expansion of digital service trade has emerged as a novel engine of global economic growth and a promising pathway for pollution reduction and carbon mitigation. This study investigates the nonlinear impact of digital service trade on CIWB, identifying an inverted U-shaped relationship—initially increasing CIWB, then reducing it beyond a certain threshold. In the financial digital service trade sector, this effect is mediated by energy structure transition, whereas in the technology-intensive sector, it is driven by green technological innovation. In contrast, digital service trade in the insurance, pension, and audiovisual sectors directly suppresses CIWB. Moreover, rising public environmental awareness helps leverage and strengthen the inhibitory effect of digital service trade on CIWB. Regionally, except for North America (which displays a consistently inhibitory effect), Asia, Africa, Europe, and Oceania reflect patterns similar to the overall sample. In regions with higher economic and internet development levels, the inverted U-shaped curve is steeper, and its turning point is located further to the left. Temporally, the relationship mirrors the full-sample patterns prior to the enforcement of the Paris Agreement, while an inhibitory effect emerges afterward. These findings offer policy implications for achieving the United Nations’ 2030 Sustainable Development Goals. Full article

The operational efficiency of insurance companies is crucial for their long-term stability and sustainable development. Climate risk has emerged as a significant factor affecting insurers’ operational performance in the context of global climate change and sustainable development goals. Although prior research provides a solid foundation, further exploration is needed to clarify how climate risk influences insurers’ efficiency and underlying mechanisms. This paper uses panel data from 248 Chinese insurance companies spanning 2011 to 2021 to construct a climate risk indicator and systematically examines the potential pathways through which this indicator influences operational efficiency. Precisely, absolute temperature deviation measures physical climate risk, and an entropy-weighted method captures climate transition risk; the DEA model evaluates operating efficiency. A fixed-effects model reveals that physical climate risk may adversely affect operational efficiency, while climate transition risk demonstrates a U-shaped relationship with efficiency. Mechanism analysis shows that physical climate risk increases exposure to natural disaster losses, whereas transition risk may encourage green insurance development. Heterogeneity emerges across insurer types and between coastal and non-coastal regions, with resilient infrastructure mitigating the adverse effects of physical risks and insurance technology driving gradual transformation to offset initial transition risks. Overall, this study expands the perspective on how climate risk shapes the insurance industry’s sustainable development, offering theoretical and practical insights for policymakers to optimize risk management and promote green finance. Full article

In recent years, global climate and environmental issues have become prominent, making green housing a major focus. However, during the development of green housing, there is a tendency to prioritize design while neglecting the operation. Meanwhile, house owners’ green rights and interests during the operation stage are not well protected. In response, some countries have promoted green housing insurance. However, this type of insurance remains immature because of insufficient public awareness, a lack of supporting policies, and limited practical application. These challenges result in low acceptance among house owners, hindering the development of green insurance and green housing sector. To address this issue, this study applies the push–pull theory to establish a driver system for house owners’ acceptance of green housing, considering internal push and external pull drivers. Structural equation modeling (SEM) is then used to analyze the mechanisms that drive house owners’ acceptance. The key findings are as follows: (1) drivers in the pull dimension have a stronger impact on acceptance than drivers in the push dimension; and (2) premium subsidies and economic compensation play a crucial role in driving house owners to accept green housing insurance. This study identifies the key drivers and pathways that influence the acceptance of green housing insurance, providing valuable insights for increasing public recognition and acceptance. The findings can contribute to the development of the green housing industry. Full article

Climate change has emphasized the need for sustainable practices across industries, including insurance. This study explores the management priorities for greenhouse gas (GHG) emissions in the insurance sector, focusing on the perspectives of marketers and brokers. It aims to identify critical emission sources and propose effective strategies for carbon reduction. Using the analytic hierarchy process (AHP) and importance–performance analysis (IPA), this study evaluates the significance and performance of GHG emission sources. Results reveal that both marketers and brokers prioritize indirect emissions, especially those from purchased electricity. However, marketers emphasize investment-related impacts, while brokers focus on emissions during the use phase of sold products. Purchased electricity is a well-managed source, while emissions from sold products require immediate attention. This study concludes that insurance companies should prioritize high-importance underperforming emission sources. Recommendations include improving energy efficiency for purchased electricity, promoting low-carbon practices during product usage, and reallocating resources from lower priority areas like investments and capital goods. By implementing these strategies, insurance companies can align environmental goals with operational priorities, enhance sustainability practices, and reinforce their reputation as socially responsible enterprises. Full article

Green technology innovation (GTI) is an important way for enterprises to promote technological progress and enhance their market competitiveness. As investment in R and D and innovation is a high-risk, long-term investment project with high sensitivity to relevant policies, increases or drastic fluctuations in economic policy uncertainty (EPU) may have a strong impact on technological innovation. Therefore, it is necessary to examine how EPU affects GTI. In contrast to studies that have focused on the impacts of EPU on GTI in developed countries or state-owned firms in China, this study uses the mediating effect panel fixed effect model to investigate the impacts of EPU on corporate GTI and its mechanisms, based on data from China’s Shanghai and Shenzhen A-share private manufacturing listed companies from 2013 to 2022. The results indicate that an increase in EPU has a positive impact on the GTI of private enterprises and that the impact is stronger in companies with multiple major shareholders, those purchasing directors’ and officers’ liability insurance, and those with stricter environmental regulations. This conclusion remains valid after robustness checks and instrumental variable tests. Mechanism tests reveal that the increase in EPU indirectly promotes GTI by forcing private enterprises to avoid short-sighted management tendencies, increase risk-taking levels, boost environmental protection investments, and strengthen internal controls. For example, EPU will lead to increased investment in green protection, meaning that private companies are more willing to promote green transformation and market competitiveness through innovative activities. These findings provide a reference for the Chinese government to formulate targeted environmental regulation policies and financing policies to guide the green transformation of businesses; they also provide insights for enterprises in other developing countries to cope with economic policy risks and promote green technological advancement. Full article

Driven by growing demands for environmental protection and sustainable development, green finance has gained increasing attention, evolving from a peripheral topic to a core research area. Research in green finance primarily focuses on financial products, services, and policies, analyzing their impacts on society, markets, and listed companies. Through a systematic literature screening and analysis process, this study reviewed the existing body of literature on green finance, with a particular emphasis on key areas such as green financing, green financial technology, green financial products and derivatives, green building, financial reform and innovation in green finance, and carbon trading markets. Using keywords such as “green finance”, “green insurance”, “green securities”, and “green investment”, we identified 15,487 relevant publications from 2014 to 2023 across multiple databases. We then applied Latent Semantic Indexing (LSI) to cluster these documents, identifying core subfields and conducting a detailed bibliometric analysis. Our results reveal a geographic shift in green finance research prominence from the U.S. to China, with a thematic shift from green building and energy efficiency to green bonds and climate finance. Through our analysis, we provide policy recommendations informed by these findings. This study’s unique contribution lies in its systematic extension of bibliometric analysis into emerging subfields of green finance, such as green financial technology and carbon trading markets, both of which are becoming increasingly critical. Additionally, this study offers valuable insights into the evolving landscape of green finance research, bridging the gap between academic research and industry practice and providing actionable policy recommendations for stakeholders across different sectors. Full article

The automotive supply chain is one of the top eight value chains that cause 50% of global emissions. Despite its significance, limited literature has researched the role of insurance companies in addressing automotive supply chain emissions. This research explores strategies developed by insurance companies for addressing carbon emissions in the automotive supply chain in the UK. It employs a qualitative multiple case study approach and conducts in-depth analysis of main drivers, barriers, and strategies in four insurance companies in addressing automotive supply chain emissions. It finds that cost savings and competitive advantage, changing mindset, impending regulation, market changes, and increased connectedness are the main drivers. But further progress is slowed down by five main barriers: ‘the complexity of tracking and quantifying emissions’, ‘conflicts of interest in the supply chain’, ‘skill shortage’, ‘lack of accountability’, and ‘profit prioritisation’. To overcome this, the study establishes five main strategies for insurance companies to follow: ‘circular business model with green parts and repair-over-replace methodologies’, ‘supply chain collaboration’, ‘quantifying emissions and setting key performance indicators’, ‘higher weighting for ESG in tenders and policies’, and ‘education and awareness’. If followed correctly, businesses will be able to achieve ‘emission reductions’, ‘gain competitive advantage’, and ‘reduce costs in the supply chain’. Taking into account these findings and the academic literature, this study develops a framework for insurance companies to mitigate automotive supply chain emissions. This is one of the first papers to study carbon emissions in automotive supply chains from the perspective of the insurance industry. It provides practical implications for the insurance industry in developing carbon emission strategies in automotive supply chains. Full article

The construction of digital villages has progressed in tandem with the transformation of traditional production methods, offering new perspectives for agricultural green growth and sustainable development. This study employs the entropy value method alongside the super-efficient global SBM (Slacks-Based Measure) mixed function model, which assesses efficiency by accounting for both inputs and outputs, thereby facilitating a comprehensive evaluation of agricultural green growth. This methodology facilitates the examination of the correlation between digital villages and agricultural green growth, as well as the influence of digital villages on this growth. Furthermore, the utilization of financial resources is employed as a mediating variable to elucidate the mechanism of action. The utilization of green finance and agricultural insurance can be facilitated by the establishment of digital villages, and that has been shown to promote agricultural green growth. Additionally, the promotion of agricultural green growth by digital village construction is stronger in middle-altitude regions, non-grain-producing regions, and regions where the digital literacy of the rural labor force is higher than average, as well as areas where the use of agricultural film is higher than average. Accelerating the construction of digital villages and promoting the utilization of rural financial resources while adapting the digital village development to local conditions are crucial for effectively fostering agricultural green growth and sustainable agricultural development. Full article

Agricultural insurance not only plays a significant role in disseminating agricultural risks and stabilizing farmers’ income, but also constitutes an essential means of promoting the transformation of agricultural development from excessive reliance on resources to a green production mode. Based on the survey data of 978 rice farmers in Jiangxi Province in 2022, this paper explored the influence of farmers’ participation in policy-based agricultural insurance on the adoption of soil testing and formula fertilization technology through the propensity score matching method. The results indicate that farmers participating in policy-based agricultural insurance exhibit significantly superior performance in adopting soil testing and formula fertilization technology compared to those not participating. Further analysis found that there were significant differences between farmers with different resource endowments participating in policy-based agricultural insurance, and that the policy-based agricultural insurance had a better effect on the adoption of soil testing and formula fertilization technology for farmers with more years of education, part-time employment, and more flat land than it did for farmers with fewer years of education, professional farmers, and more sloping land. The main conclusion is that the guarantee function of agricultural insurance in rural areas should be enhanced; the training and publicity of farmers’ production technology and environmental awareness should be strengthened; rural characteristic industries and county economies should be vigorously developed; high-standard farmland should be vigorously constructed; and policy suggestions should be made on agricultural infrastructure construction. Full article

This study investigates the crucial role of green finance in addressing the imperative of reducing industrial carbon emissions for a sustainable global economy. Encompassing facets, such as green credit, insurance, investment, and governmental help for growth in green businesses. Our research on the strength of a comprehensive dataset covering China’s 30 provinces between 2010 and 2019 employs a fixed-effects regression and heterogeneity assessment, revealing an inverse association between green finance and industrial carbon emissions. This verifies the notion that green finance serves as a deterrent to carbon emissions from the industrial sector. According to the results of this study, green financing can significantly lower the CO₂ emissions from industries, which in turn can lead to an enhancement in environmental quality. Notably, our findings revealed substantial regional variations in this relationship. By proposing actionable recommendations, we advocate strategies to address regional disparities, standardize measurement protocols for green finance, optimize the environment for technological innovation, and realize industrial structures. By acknowledging these nuanced dynamics, our study not only contributes to the understanding of the impact of green finance but also offers targeted solutions to foster high-quality sustainable development in China, ensuring a more effective and comprehensive approach to mitigating carbon emissions in the industrial sector. Full article

Artificial Intelligence and Deepfake Technologies have brought a new dimension to the generation of fake data, making it easier and faster than ever before—this fake data could include text, images, sounds, videos, etc. This has brought new challenges that require the faster development of tools and techniques to avoid fraudulent activities at pace and scale. Our focus in this research study is to empirically evaluate the use and effectiveness of deep learning models such as Convolutional Neural Networks (CNNs) and Patch-based Neural Networks in the context of successful identification of real and fake images. We chose the healthcare domain as a potential case study where the fake medical data generation approach could be used to make false insurance claims. For this purpose, we obtained publicly available skin cancer data and used recently introduced stable diffusion approaches—a more effective technique than prior approaches such as Generative Adversarial Network (GAN)—to generate fake skin cancer images. To the best of our knowledge, and based on the literature review, this is one of the few research studies that uses images generated using stable diffusion along with real image data. As part of the exploratory analysis, we analyzed histograms of fake and real images using individual color channels and averaged across training and testing datasets. The histogram analysis demonstrated a clear change by shifting the mean and overall distribution of both real and fake images (more prominent in blue and green) in the training data whereas, in the test data, both means were different from the training data, so it appears to be non-trivial to set a threshold which could give better predictive capability. We also conducted a user study to observe where the naked eye could identify any patterns for classifying real and fake images, and the accuracy of the test data was observed to be 68%. The adoption of deep learning predictive approaches (i.e., patch-based and CNN-based) has demonstrated similar accuracy (~100%) in training and validation subsets of the data, and the same was observed for the test subset with and without StratifiedKFold (k = 3). Our analysis has demonstrated that state-of-the-art exploratory and deep-learning approaches are effective enough to detect images generated from stable diffusion vs. real images. Full article

Hog insurance and rural environmental protection are complementary to each other. Studying the environmental effects of hog insurance is imperative for safeguarding food safety and promoting the long-term development of the agricultural insurance industry. Informed by the risk management theory and sustainable development theory, this paper constructs a theoretical framework for the impact of policy-supported hog insurance on the green total factor productivity (GTFP) of hog farming. Utilizing panel data from China’s hog-dominant production areas spanning from 2005 to 2021, the slacks-based measures of directional distance functions (SBM-DDF) model and multiple-time-point difference-in-differences (DID) approach were used to measure GTFP and explore the effects of hog insurance on GTFP and the underlying mechanisms. The findings indicate a substantial enhancement in GTFP due to hog insurance. The conclusion drawn was robust to various tests. The mechanism is that hog insurance fosters GTFP by expanding the breeding scale, adjusting the planting–breeding structure, and promoting technological progress. Furthermore, the environmental effects of hog insurance policy are more pronounced in economically developed regions, with significant effects observed on the GTFP of free-range, small-scale, and medium-scale hog-farming households. This study contributes new evidence to the field of assessing the environmental impact of agricultural insurance policies and provides valuable insights for furthering green transformation and development in the hog insurance-supported breeding industry. Full article

Ecological environment restoration has become an important strategy for the high-quality development of the Yangtze River Economic Belt, and green finance is indispensable to supporting industrial transformation and green innovation. It is of great importance to clarify the internal relationship between green finance and ecological resilience construction. This paper introduces the concept of resilience into the field of ecological construction and constructs an ecological resilience index system from three dimensions of “resistance-adaptability-resilience”. On this basis, it focuses on the different aspects of green finance, such as green credit, green securities, green investment, green insurance, etc., and examines the role of green financial development on the ecological resilience of the Yangtze River Economic Belt. The results of the study showed that (1) during the study period, the overall ecological resilience level of the Yangtze River Economic Belt improved significantly and there were significant differences in the ecological resilience of the economic belts but such spatial differences are converging; (2) green insurance has a significant positive influence on ecological resilience, while green credit, green securities, and green investment have a significant negative influence on ecological resilience; (3) green credit and green securities have a significant positive effect on the resistance to ecological resilience, green credit and green investment inhibit the adaptability of ecological resilience, and green insurance significantly improves the resilience of ecological resilience. Green financial policies should be further optimized, and innovative all-round and multi-level products and services should be provided. It is necessary to leverage social capital to promote green transformation and technological innovation in high-pollution industries. By combining resource endowment and location advantages, we can explore the benign interaction between green finance and ecological civilization construction. Full article