Search Results (136)

It is unknown how recurring flooding impacts household diet in Central Java. We aimed to assess how recurrent flooding influenced household food access over 22 years in Central Java by linking the Global Surface Water dataset (GSW) to the Indonesian Family Life Survey. We examined linear and nonlinear relationships and joint effects with indicators of adaptive capacity. We measured recurrent flooding as the fraction of district raster cells with episodic flooding from 1984–2015 using GSW. Food access outcomes were household food expenditure share (FES) and dietary diversity score (DDS). We fit generalized linear mixed models and random forest regression models. We detected joint effects with flooding and adaptive capacity. Wealth and access to credit were associated with improved FES and DDS. The effect of wealth on FES was stronger in households in more flood-affected districts, while access to credit was associated with reduced odds of DDS in more flood-affected districts. Flooding had more predictive importance for FES than for DDS. Access to credit, a factor that ordinarily improves food access, may not be effective in flood-prone areas. Wealthier households may be better able to adapt in terms of food access. Future research should incorporate land use data to understand how different locales are affected and further understand the complexity of these relationships. Full article

This study explores the influence of risk disclosure levels and types on the readability of annual reports of non-financial firms in the UK during the COVID-19 outbreak. It further investigates how the disclosure of COVID-19-related information moderates the relationship between risk disclosure and readability. The study uses a content analysis approach and CFIE software to measure the level of risk disclosure and readability in the annual reports of non-financial firms listed on the FTSE all-share from 2019 to 2021. The results show a positive and significant effect of risk disclosure level on readability, which is stronger for firms that disclosed COVID-19 information. Different types of risk disclosure have varying effects on readability, with COVID-19 risk, credit risk, and strategic risk positively affecting readability, while operational risk negatively affects it. The study contributes to the literature on information asymmetry and institutional theory by demonstrating how risk disclosure and readability are influenced by external factors like the COVID-19 outbreak and internal factors such as firm characteristics and types of risks. It introduces a new risk definition and category specific to the COVID-19 pandemic and develops new measurements for risk disclosure, including credit, liquidity, market, operational, business, strategic, and COVID-19 risks. The study provides valuable insights for managers, investors, regulators, and standard setters on the relationship between risk disclosure and readability in annual reports. It highlights the importance of disclosing COVID-19-related information to enhance the readability and understandability of financial communication. The paper contributes to the literature and practice on risk disclosure, readability, and financial communication during crises. Full article

Sustainability assurance (SA), an independent third-party evaluation aimed at enhancing the credibility of corporate sustainability disclosure, plays a vital role in fostering corporate green transformation. This paper systematically examines the impact of SA on corporate green transformation and the mechanisms through which it operates, using data on SA reports and green patents from A-share listed companies in China between 2010 and 2022. The findings reveal that SA significantly promotes corporate green transformation, particularly when conducted in accordance with standard ISAE 3000. Mechanism analysis indicates that SA facilitates green transformation by reducing the cost of credit and promoting risk-taking behaviors. Heterogeneity analysis further demonstrates that the positive effects of SA on green transformation are more pronounced in heavily polluting and competitive industries as well as in firms with weaker internal and external governance. This study not only underscores the beneficial impact and underlying mechanisms of SA on corporate green transformation but also contributes to the broader literature on the drivers of corporate green transformation. Full article

In recent years, rapid technological advancements have propelled blockchain and artificial intelligence (AI) into prominent roles within the digital industry, each having unique applications. Blockchain, recognized for its secure and transparent data storage, and AI, a powerful tool for data analysis and decision making, exhibit common features that render them complementary. At the same time, machine learning has become a robust and influential technology, adopted by many companies to address non-trivial technical problems. This adoption is fueled by the vast amounts of data generated and utilized in daily operations. An intriguing intersection of blockchain and AI occurs in the realm of federated learning, a distributed approach allowing multiple parties to collaboratively train a shared model without centralizing data. This paper presents a decentralized platform FBLearn for the implementation of federated learning in blockchain, which enables us to harness the benefits of federated learning without the necessity of exchanging sensitive customer or product data, thereby fostering trustless collaboration. As the decentralized blockchain network is introduced in the distributed model training to replace the centralized server, global model aggregation approaches have to be utilized. This paper investigates several techniques for model aggregation based on the local model average and ensemble using either local or globally distributed validation data for model evaluation. The suggested aggregation approaches are experimentally evaluated based on two use cases of the FBLearn platform: credit risk scoring using a random forest classifier and credit card fraud detection using a logistic regression. The experimental results confirm that the suggested adaptive weight calculation and ensemble techniques based on the quality of local training data enhance the robustness of the global model. The performance evaluation metrics and ROC curves prove that the aggregation strategies successfully isolate the influence of the low-quality models on the final model. The proposed system’s ability to outperform models created with separate datasets underscores its potential to enhance collaborative efforts and to improve the accuracy of the final global model compared to each of the local models. Integrating blockchain and federated learning presents a forward-looking approach to data collaboration while addressing privacy concerns. Full article

Fund investment, as a type of financial investment in the capital market, is designed to attract more social capital towards the green environmental protection sector and foster a harmonious relationship between economic development, social advancement, and ecological conservation. Therefore, as a significant policy instrument, will implementing the green credit policy impact the investment preferences of fund investors? How does it influence their participation in the market? This study utilizes microdata from Chinese Shanghai and Shenzhen A-share-listed companies from 2004 to 2020 to establish a DID model based on the Green Credit Guidelines introduced in 2012. The research delves into the effects of the green credit policy on fund investment and its underlying mechanisms. The green credit policy was found to favor the entry of fund investment, and the results are still valid after a series of robustness tests. The attraction effect of the green credit policy on investors is more evident in non-state-owned enterprises, small and micro enterprises, and non-green industries. Green credit policy can positively influence investor entry through the financing constraint effect and productivity effect. The study theoretically supplements the literature in the field of evaluating the effect of the green credit policy, and practically provides practical guidance and inspiration for strengthening the synergy of the government, banks, and enterprises in implementing green credit policy, promoting industrial transformation, and upgrading, and realizing high-quality economic development. Full article

Lending to the agricultural sector by commercial banks in Ghana is characterized by high credit risk. Empirical evidence suggests that commercial banks in Ghana have credit risk management (CRM) challenges. This study explores the credit risk mitigation strategies adopted by commercial banks to minimize credit risk in agricultural finance in Ghana. The study adopted a mixed-method approach using a survey questionnaire and interview instruments. The findings indicate that some of the strategies used by commercial banks to mitigate credit risk in agricultural finance do not meet commercial banks’ CRM needs. In addition, Ghanaian commercial banks have not fully adopted some of the recommended strategies that are used to mitigate credit risk associated with agricultural lending. The study unveils some appropriate strategies used to mitigate credit risk exposure in agricultural finance among commercial banks. These strategies include agricultural value-chain financing, collaboration with off-takers, incentive-based and risk-sharing schemes, adoption of a holistic agricultural value chain financing, policy interventions, use of agricultural insurance pool, and the proper structuring of agricultural loans. Full article

Credit purchase enables the manufacturers in the e-commerce environment to provide pre-sales service that consumers can experience first and pay later. This paper considers demand associated with price and green promotion service level and builds four decentralized game models to study two green promotion service allocation strategies and demand forecasting information sharing strategies in a dual-channel environment. The effects of the degree of dual-channel competition and free-riding on the perfect Bayesian Nash equilibrium are studied. The results show that the retailer should actively cooperate with the manufacturer and share private forecasting information if the coefficient of channel substitution is relatively high. Sharing information will aggravate double marginalization and hurt the retailer. In addition, the retailer’s profit is positively influenced by the forecasting accuracy in four models. When the manufacturer invests in the green promotion service, the prediction accuracy hurts the manufacturer’s profit without information sharing and there is a positive impact with information sharing. In particular, when a retailer provides service, we take the consumer’s free-riding behavior into account, and we find that free-riding hurts both parties and the whole supply chain. In addition, the manufacturer’s profit is irrelevant to the prediction accuracy without information sharing and positively influenced by the accuracy with information sharing. Full article

In response to climate change, the proportion of renewable energy penetration is increasing daily. However, there is a lack of flexible energy transfer mechanisms. The optimization effect of low-carbon economic dispatch in a single park is limited. In the context of the sharing economy, this study proposes a research method for multi-park electricity sharing and benefit allocation based on carbon credit trading. Firstly, a framework for multi-park system operation is constructed, and an energy hub model is established for the electrical, cooling, and heating interconnections with various energy conversions. Secondly, a park carbon emission reduction trading model is established based on the carbon credit mechanism, further forming an optimal economic and environmental dispatch strategy for multi-park electricity sharing. Matlab+Gurobi is used for solving. Then, based on asymmetric Nash bargaining, the comprehensive contribution rate of each park is calculated by considering their energy contribution and carbon emission reduction contribution, thereby achieving a fair distribution of cooperation benefits among multiple parks. The results show that the proposed method can effectively reduce the overall operational cost of multiple parks and decrease carbon emissions, and the benefit allocation strategy used is fair and reasonable, effectively motivating the construction of new energy in parks and encouraging active participation in cooperative operations by all parks. Full article

Based on the interactive integration between smart cities and intelligent transportation, this paper discusses how traditional automobile companies achieve intelligent-connected transformation and how to promote the development of intelligent connected vehicles. First, we construct a tripartite evolutionary game model of traditional automobile companies, internet companies, and financial institutions under the dual-credit policy. Second, we define an ideal event and analyze the impacts of cost factors, market factors, and policy factors on system evolution. Finally, funding time delay is combined with the evolutionary game analysis. Results indicate that: (1) Compared with traditional automobile companies and internet companies, financial institutions are more sensitive to the profit-sharing coefficient and cost-sharing coefficient; (2) The probability of an ideal event is more sensitive to credit trading price than new energy vehicle (NEV) credit accounting coefficients and the NEV credit ratio requirement; (3) The government should fully consider the linkage between policy factors and market factors, and it is unreasonable for the government to consider the range of any factor alone; (4) Both the financing amount and regulatory cost have specific threshold ranges within which tripartite collaboration can be facilitated. Full article

This research investigated the role of agricultural cooperatives (ACs) in promoting sustainable agriculture and agrifood security, with a particular emphasis on Greece. A cross-sectional survey technique was employed, and data were collected from 400 farmers and professionals either employed by or associated with Greek agricultural cooperatives by administering an online questionnaire. A response rate of 96.5% was achieved. The study findings show that cooperative techniques bring about a positive shift in agrifood security and sustainable agriculture. Particularly, participants concurred that resource sharing among cooperative members increases farm productiveness and sustainability by 94.2% while improving access to credit and financial support by 91.5%. Moreover, 84.3% agreed that access to up-to-date information enhances the practice of sustainable agriculture, and 95.1% agreed that collective bargaining through cooperatives increases the prices of agricultural commodities. Regarding the application of advanced technologies in cooperative practices, 96.7% of the participants acknowledged that it improved farm efficiency. The cooperative model demonstrates how agricultural expansion may be achieved by collective bargaining, information sharing, resource sharing, and technological integration, while also considerably improving agrifood security and sustainability. These findings highlight the crucial importance of cooperatives in increasing the level of agricultural production, ensuring sustainability, and improving agrifood security in Greece. Full article

This paper considers the impact of the composition of the top management team on the credit default risk of the firm. Finance theory suggests that shareholders prefer higher levels of risk than the risk-averse executives managing the firm. Increasing the influence of female executives may reduce credit default risk, as female executives have been shown to be associated with lower firm risk. Alternatively, as diversity has been shown to improve the quality of group decision-making, a higher but optimal credit default risk may result. This paper uses a matched sample of 6,652 firm-year observations of publicly traded American firms over the period 2010–2020 to investigate the relationship between gender power within the top management team and credit default risk as measured by the Altman Z-score. This paper finds a convex relationship between the Altman Z-score and the influence of female executives. In other words, top management teams where power is shared between female and male executives accept higher levels of credit default risk than teams dominated by just female (or just male) executives. However, this paper also finds that an excessively high credit risk is negatively associated with the influence of female executives. Full article

The advancement of emission reduction benefits in ridesplitting relies on a comprehensive carbon reduction incentive policy initiated by the government and implemented through the collaborative efforts of multiple stakeholders. The aim of this study is to understand the implementation mechanism and explore the carbon reduction potential of the Carbon-Inclusive Policy. A framework has been developed to explore an evolutionary stabilization strategy through a three-party evolutionary game model, which considers the crucial stakeholders of the government, shared mobility companies, and travelers. A comprehensive sensitivity analysis has been conducted across various scenarios on key factors to ensure the robustness and accuracy of findings. The study’s primary findings indicate that the government’s level of commitment to the Carbon-Inclusive Policy significantly influences strategic decisions and the pace of evolution among the three stakeholders in the evolutionary game. Companies critically assess the economic viability of ridesplitting, particularly in light of development costs and subsidy incentives. Government backing and increased ridesplitting adoption by travelers serve to mitigate risks, incentivizing companies to actively promote ridesplitting. Furthermore, the study emphasizes the necessity of balancing individual, company, and societal interests for sustainable transportation development, advocating for reasonable carbon tax credits and the promotion of novel development concepts such as Environmental, Social, and Governance (ESG) principles. These findings serve as a significant resource for policymakers navigating the complexities of integrating carbon considerations into transportation policy frameworks, contributing to a deeper theoretical understanding of Carbon-Inclusive Policy implementation in the sector. Full article

Brazil is the second largest beef producer and a leading exporter, contributing to some 3000 t CWE in global markets (27.7% of market share). The sector has experienced substantial development, but yields remain far below potential, and there are growing concerns regarding land use change and greenhouse gas emissions. The need for sustainable technologies, such as sound pasture management and integrated farming systems, is evident, but adoption may be low amongst farmers unable to keep up with technological advances. This article describes the historical developments of Brazilian beef farming towards sustainability and discusses possible socioenvironmental outcomes. We combined an extensive literature review, public data, and our own insights as senior researchers to achieve that. The trajectory shown here evidenced the technological intensification of Brazilian beef farming, with strong support of public policies for decarbonizing agriculture. Nonetheless, the pace of this transition may affect small to medium farmers with limited access to information, technologies, and credit. Our recommendations involve a broad program of technical assistance and training on sustainable technologies, including financial and digital literacy. A novel approach to financing farmers is suggested to support a sustainable and inclusive transition in beef farming in Brazil. Full article

Improving the level of risk-taking is an important measure for enterprises to realize sustainable development; in this context, commercial credit financing has become an important type of transaction and an indispensable short-term financing method. In this work, we use a sample of A-share-listed companies listed from 2007 to 2021 to test the impact of commercial credit financing on corporate risk-taking. Research shows that commercial credit financing has a U-shaped relationship with corporate risk-taking, i.e., when there is a low level of commercial credit financing, it has an inhibitory effect on corporate risk-taking, and when the level of commercial credit financing is high, it has a promotional effect on corporate risk-taking. The main reason for this, based on substitute financing and buyer market theories, is that commercial credit financing has a “double-edged sword” effect. Further research has found that corporate financialization, debt default risk, and ownership form all have moderating effects on this U-shaped relationship. Heterogeneity analysis results show that among enterprises with good cash flow conditions, low financing constraints, and a low supply of commercial credit, commercial credit financing has a significant U-shaped impact on enterprise risk-taking. However, among enterprises with poor cash flow conditions, high financing constraints, and a high supply of commercial credit, commercial credit financing shows a solely inhibitory effect on enterprise risk-taking. This research innovatively clarifies the dual role of commercial credit financing in corporate risk-taking from the perspective of the supply chain, and these findings are pivotal in guiding enterprises to rationally allocate commercial credit financing and make informed risk investment decisions to realize the simultaneous sustainable development of enterprises and supply chains. Full article

This paper investigates strategic production selections in scenarios of credit sharing between cooperative fuel vehicle (FV) automakers and new energy vehicle (NEV) automakers under the dual-credit policy. Three coopetition production strategies are formulated: the simultaneous production strategy, the FV priority production strategy, and the NEV priority production strategy. On the basis of these three production strategies, this study examines the optimal strategy for both parties in scenarios of no credit sharing, credit sharing dominated by the FV automaker, and credit sharing dominated by the NEV automaker. The simultaneous production strategy is the most conducive to both parties’ coexistence in the vehicle market, and the FV or NEV priority production strategy can be adopted to realize the Pareto optimization of their total profit in certain applicable intervals. Credit sharing will greatly change both parties’ applicable intervals and optimal strategy selections, and credit sharing dominated by FV automakers has been proven to effectively improve their social welfare with a low credit price. Interestingly, a high credit price is sometimes more important for the development of NEVs than the NEV cruising range and substitutability under the dual-credit policy. This study also demonstrates the impact of the credit coefficient, credit equilibrium, and NEV substitutability on both parties’ production decisions and credit sharing. Our study has important managerial implications and can be utilized as strategic guidance for FV/NEV automakers to pursue coopetition under the dual-credit policy. Full article