Search

In recent years, blockchain technology has attracted substantial interest for its capability to transform supply chain management and finance. This paper employs evolutionary game theory to investigate the application of blockchain in mitigating financial risks within supply chains, taking into account the technology's maturity and the risk preferences of financial institutions. By modeling interactions among financial institutions, small and medium enterprises (SMEs), and core enterprises within the accounts receivable financing framework, this study evaluates blockchain's impact on their decision-making and its efficacy in risk reduction. Our findings suggest the transformative potential of blockchain in mitigating financial risks, solving information asymmetry, and enhancing collaboration between financial entities and SMEs. Additionally, we integrate smart contracts into supply chain finance, proposing pragmatic procedures for their deployment in real-world contexts. Via a detailed examination of blockchain's maturity and financial institutions' risk preferences, this research demonstrates the primary determinants of strategic decisions in supply chain finance and underscores how blockchain technology fosters system stability using risk mitigation. Our innovative contribution lies in the design of smart contracts for the ARF process, rooted in blockchain's core attributes of security, transparency, and immutability, thereby ensuring efficient operation and cost reduction in supply chain finance. [ABSTRACT FROM AUTHOR]

With the rapid growth of the global digital economy, supply chain finance has entered the stage of platform development in view of the history, policy environment, market status and other factors. Supply chain finance relies on multiple supply chain stakeholders to carry out financial business, which needs to solve a variety of financial risk control and pricing issues. The financing model in supply chain finance can be differentiate from the traditional credit model. The service mode and leading mode of supply chain finance need to be adjusted in accordance with the changes of the industrial operation. Further, the business mode of supply chain finance shows a diversification trend, which includes traditional supply chain financial models such as accounts receivable, advance payment, inventory financing, and supply chain credit financing models. In this paper, we investigate the similarities between supply chain finance and options, and further introduce American call options to supply chain financial products under the mode of small and medium-sized enterprises' (SMEs) accounts receivable financing. The price of supply chain financial products is derived through the trinomial tree option pricing model, which determines the corporate financing interest rates. The rationality of the proposed pricing model is validated in comparison with the medium and long-term load bank interest rates. The contribution of the paper is in providing SMEs with supply chain financial products under the accounts receivable model to resolve financing difficulties and the pricing the products through the trinomial budget pricing model. [ABSTRACT FROM AUTHOR]

Purpose: The particular characteristics of agri-food cooperatives reduce their ability to access external financial resources. The purpose of this paper is to explore the factors influencing the agri-food cooperatives' trade credit operations by measuring their accounts receivable and comparing the results with agri-food investor-owned firms (IOFs). Design/methodology/approach: The authors apply a partial adjustment model (PAM) estimated using a dynamic panel model with a two-step general method of moments (GMM) estimator to a sample of 11,930 Spanish agri-food cooperatives and IOFs for the period 2011–2018. Findings: The study concludes that cooperatives and IOFs have an accounts receivable target, which they attempt to achieve rapidly. Cooperatives tend to behave as IOFs do, but they present lower adjustment coefficients. This difference seems to be explained by the unique characteristics of cooperatives which set different economic and social goals, not just profit maximization as IOFs. The findings show differences between the financial and commercial purposes of the cooperatives and IOFs as a result of their internal management policies. Larger cooperatives with access to external financial sources, positive cash flows and operational necessities will grant trade credit. Originality/value: This study gives interesting implications for cooperative managers and policymakers to help them to understand the strategies behind trade credit policies. Previous empirical studies on the agri-food sector are scarce and focus on IOFs without considering the role of trade credit in European cooperatives. [ABSTRACT FROM AUTHOR]

Risk aversion, which refers to the reluctant attitude of an economic agent to accept uncertain outcomes compared with a certain one even if the latter has a lower outcome in monetary value, plays a fundamental role in decision theory and risk management. This paper investigates how to measure different agents' risk-averse attitudes towards a risky situation consisting of multiple uncertain components under uncertainty theory. First, a general method to approximately compute the multivariate uncertain risk premium is proposed. Subsequently, the multivariate uncertain risk aversion is formally defined based on the multivariate uncertain risk premium, and the corresponding sufficient condition for utility functions being multivariate risk-averse is given. Its relation to Richard's correlation aversion under the framework of uncertainty theory is also discussed. Finally, the suggested theoretical findings are applied to an accounts receivables (ARs) pricing problem to exhibit their applicability. The results show that our method is more applicable in practice than the univariate approach. Moreover, for the AR financing, the AR owner should choose higher-credit trading partners and financial institutions with less risk aversion to cooperate for acquiring more cash. [ABSTRACT FROM AUTHOR]

The research work on multi-task principal-agent in supply chain seldom considered other factors. In this paper, basing on accounts receivable mode of supply chain finance, we add the financing factor of bank in multi-task principal-agent to study the incentive mechanism between the manufacturer and the supplier. First we develop an incentive model under the condition of symmetric information and work out the optimal result. Next the circumstance with asymmetric information is also discussed. Last, the effort level of supplier is discussed when the receivables business ran normally. [ABSTRACT FROM AUTHOR]

In order to cope with the increasingly severe energy crisis and climate and environmental change, energy conservation and environmental protection industry has become an emerging field for the optimization of China‘s economic structure and the development of green circular economy. However, lack of funds restricts the growth of energy conservation and environmental protection industries. Aiming at the financing difficulty of energy conservation and environmental protection industry, this paper introduces supply chain finance theory and game theory to establish accounts receivable game model. In a two-level supply chain composed of the core manufacturer and the supplier with financial constraints, the optimal decision and profit of the supplier, manufacturer, and bank under the condition of three-party compliance are studied, by using the Stackelberg game model. At the same time, the supply chain financing game under complete information condition and incomplete information condition is analyzed theoretically. Finally, through the method of example analysis, it is proved that the supplier’s initial capital, the manufacturer’s order quantity, the bank interest rate, the supplier’s financing pledge rate and so on have a significant impact on the supply chain financing income. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the financial condition and ability of farmer cooperatives to withstand significant increases in bad debt expense. Design/methodology/approach: A unique data set of farmer cooperative financial statements that spans from 1996 to 2019 is used to examine the changes in profitability, solvency, liquidity and accounts receivable risk. Also, a deterministic stress test model is designed to shock bad debt expense and the resulting write-off of accounts receivable for farmer cooperatives. The stress test provides insights to the resiliency of farmer cooperatives. Findings: Results find that farmer cooperatives are in a strong financial position, which has improved over time. The majority of farmer cooperatives are able to absorb a substantial increase in bad debt expense because of their sizable, retained earnings position. However, cooperatives that have significant profitability challenges do experience much larger losses, especially mixed farmer cooperatives (roughly equally amounts of grain and farm supply sales) and large cooperatives with more than $500 million in sales. Practical implications: The stress test results suggest farmer cooperative managers and boards of directors could re-examine their credit policies and consider extending additional credit. Also, cooperatives should consider monitoring and identifying an optimal accounts receivable to retained earnings ratio, which is similar to how banks examine their tier 1 capital ratios. Originality/value: The value of this study is having data that allows for the examination of the financial condition of farmer cooperatives over time. Also, having current data means the accounts receivable stress test results are more relevant and timelier. This is important because these accounts receivable are primarily tied to crop input supplies, and farmer cooperatives are a significant market participant in the crop input supply market. [ABSTRACT FROM AUTHOR]

Network Function Virtualization (NFV)-based 5G networks deliver specific services to a end-users through the creation of Service Function Chains (SFCs), which are composed of a number of Virtualized Network Functions (VNFs) interconnected via a set of virtual links (vLinks). VNFs consume computational resources of the network's servers, while vLinks utilize the communicational resources of the network. The efficient utilization of network resources remains a challenge in NFV-based networks. To this end, in this paper, we propose an analytical framework for the Admission Ratio (AR) calculation in NFV-based converged optical-wireless 5G networks. The proposed methodology employs a network slicing architecture in which different network slices form end-to-end logically isolated networks and each slice delivers a specific service type to the users through its SFC(s). In the proposed analysis, we not only take into account the occupancy distribution in both the network's computational and communicational domains (servers and fiber links), but we also consider the SFC establishment AR by taking into account different sub-service-classes belonging to different slices. The accuracy of the model is evaluated through the comparison of analytical and simulation results and was found satisfactory. Furthermore, the proposed model is employed for the determination of the optimal (minimum) capacity for all SFCs elements (VNFs and vLinks), in a way that users belonging to a specific slice experience a predefined value of AR as minimum. Additionally, our calculations deploy recursive formulas, which have a low computational complexity, as opposed to time-consuming simulations, without requiring the application of complex optimization algorithms. [ABSTRACT FROM AUTHOR]