Improving Supply Chain Profit through Reverse Factoring: A New Multi-Suppliers Single-Vendor Joint Economic Lot Size Model

Marchi, Beatrice; Zanoni, Simone; Jaber, Mohamad Y.

doi:10.3390/ijfs8020023

Cited by 8 publications

(5 citation statements)

References 32 publications

(43 reference statements)

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“…e provider of accounts receivable financing funds should also pay attention to the risk of changes in the value of suppliers' accounts receivable [4]. Meanwhile, there are some problems in accounts receivable financing, such as legal supervision, bank enterprise information asymmetry, etc [5].…”

Section: Introductionmentioning

confidence: 99%

A K-Means Clustering Algorithm for Early Warning of Financial Risks in Agricultural Industry

Li¹,

Duan²

2022

Security and Communication Networks

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As the primary industry, agricultural industry is the basis of guaranteeing people’s basic life and national economic development. Agricultural industrial finance/financial is a weak link in the financial system, which seriously hinders the emergence of agricultural scale effect and the improvement in agricultural production efficiency. In order to find the financial risk of agricultural industry in time, this article proposes an agricultural industry financial risk early warning system based on improved K-means clustering algorithm. Because the traditional K-means algorithm is easy to fall into local optimization in the clustering process, the clustering effect is not reliable. In this article, the idea of immune cloning and particle swarm optimization location update is added to the grey wolf optimization algorithm. Grey wolf optimization algorithm and K-means algorithm are combined to solve the problem that K-means algorithm is easy to fall into local optimization. In the experimental part, through comparative verification, it can be found that the prediction performance of this system is superior to other models. Its practical application value is higher. Therefore, choosing this system for early warning of agricultural industry finance can effectively improve the accuracy of early warning and provide guarantee for the economic development of agricultural industry.

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Section: Introductionmentioning

confidence: 99%

A K-Means Clustering Algorithm for Early Warning of Financial Risks in Agricultural Industry

Li¹,

Duan²

2022

Security and Communication Networks

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“…While the cash-on-delivery can represent a solution for improving the responsibility of the actors for providing a product with the required quality to the final customer. A further solution can be the reverse factoring among the buyer-based financing mechanisms, in which the buyer arranges for early payments to its supplier (Marchi et al 2020c), which can be invested for higher quality of the products. At the same time, also shared investment can be considered to improve the performance of the supply chain (Marchi et al 2016;Marchi et al 2018) and guarantee the required surrounding environment to those items.…”

Section: Discussionmentioning

confidence: 99%

Supply chain finance for ameliorating and deteriorating products: a systematic literature review

2022

Self Cite

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Ameliorating and deteriorating products, or, more generally, items that change value over time, present a high sensitiveness to the surrounding environment (e.g., temperature, humidity, and light intensity). For this reason, they should be properly stored along the supply chain to guarantee the desired quality to the consumers. Specifically, ameliorating items face an increase in value if there are stored for longer periods, which can lead to higher selling price. At the same time, the costumers’ demand is sensitive to the price (i.e., the higher the selling price the lower the final demand), sensitiveness that is related to the quality of the products (i.e., lower sensitiveness for high-quality products). On the contrary, deteriorating items lose quality and value over time which result in revenue losses due to lost sales or reduced selling price. Since these products need to be properly stored (i.e., usually in temperature- and humidity-controlled warehouses) the holding costs, which comprise also the energy costs, may be particularly relevant impacting on the economic, environmental, and social sustainability of the supply chain. Furthermore, due to the recent economic crisis, companies (especially, small and medium enterprises) face payment difficulties of customers and high volatility of resources prices. This increases the risk of insolvency and on the other hand the financing needs. In this context, supply chain finance emerged as a mean for efficiency by coordinating the financial flow and providing a set of financial schemes aiming at optimizing accounts payable and receivable along the supply chain. The aim of the present study is thus to investigate through a systematic literature review the two main themes presented (i.e., inventory management models for products that change value over time, and financial techniques and strategies to support companies in inventory management) to understand if any financial technique has been studied for supporting the management of this class of products and to verify the existing literature gap.

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“…The impact of a company's financial condition on its survival as well as its performance on the market is undeniable. Marchi et al (2020) developed a JELS model in an SC with a vendor and multisuppliers in which vendor coordinates both financial and operational decisions with its multiple suppliers through the establishment of a reverse factoring arrangement. In this paper, a numerical example and also a sensitivity analysis have been presented which showed the behavior of the model and compare the economic and operational performance of an SC with and without a reverse factoring agreement.…”

Section: Joint Economic Lot-size Modelmentioning

confidence: 99%

A joint economic lot-size model with collaboration of supply chain members

Sooran

Tayebi

Ebrahimnejad

2022

JM2

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Purpose The purpose of this study is to investigate a joint economic lot-size model with the possibility of cofinancing between members of a three-echelon supply chain (SC) including one supplier, one manufacture and one retailer. Given the differences in credit as well as differences in access to capital markets, SC members will be able to create a financial alliance to maximize the profits of each member. This study proposed a model to maximize the annuity stream of the SC by considering the financial interaction between SC members. Design/methodology/approach This joint economic lot-sizing problem was described and modeled mathematically. To evaluate the mathematical model, different scenarios were considered with (and without) the possibility of financial interaction. Findings It is suggested that, in addition to the goods and information flow among SC members, proper financial flow can also have an impact on the improvement of SC performance. Originality/value While previous studies consider cofinancing between members of a two-echelon SC, this paper considers a three-echelon SC including one supplier, one manufacturer and one retailer where financial cooperation between different levels of the SC in both upstream and reverse directions will be possible.

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Improving Supply Chain Profit through Reverse Factoring: A New Multi-Suppliers Single-Vendor Joint Economic Lot Size Model

Cited by 8 publications

References 32 publications

A K-Means Clustering Algorithm for Early Warning of Financial Risks in Agricultural Industry

A K-Means Clustering Algorithm for Early Warning of Financial Risks in Agricultural Industry

Supply chain finance for ameliorating and deteriorating products: a systematic literature review

A joint economic lot-size model with collaboration of supply chain members

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