Wilson Chen '23
Supply Chain Finance Part 1

Supply Chain Finance (SCF) is an effective method to lower financing costs and improve financing efficiency and effectiveness, and it has gained research momentum in recent years. It has always been considered in need of financing and provides further insights for future research by doing some preliminary work on a unified model. Specifically, I consider a case relevant to current COVID-19 by depicting a supply chain with external shock and I achieve an unified case through considering multiple parameters of interest. Although no closed-form solution can be derived when it comes to the overall performance of the supply chain, I analyze the case of retailers, and such qualitative results can be of interest when trying to understand its behavior. Also, I use numerical analysis to gain further insights of the overall supply chain performance by considering reasonable numerical values.

Although my paper is the first to consider such a case as it’s motivated by the outbreak of COVID-19, some relevant papers are summarized as below.

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Xu et al. (2018) identified four research clusters, including: deteriorating inventory models under trade credit policy based on the EOQ/EPQ model; inventory decisions with trade credit policy under more complex situations; interaction between replenishment decisions and delay payment strategies in the supply chain and roles of financing service in the supply chain by using rigorous bibliometric and visu- alization tools [4]. Lee and Rhee (2011) attempted  to shed light on trade-credit from a supplier’s perspective and present it as a tool for supply chain coordination. Specifically, they explicitly assumed firms’ financial needs for inventory [2]. Zhang et al. (2019) empirically tested the relationship between supply chain finance and not only the firm’s financial performance, but also extended the knowledge of this discipline by studying the relationship between supply chain finance and inventory performance and bankruptcy risk for the focal firm [5]. Wang et al. (2015) have built a prediction model for the business failure of supply chain financing clients to help the financial institutions improve the predictability of business failure of supply chain finance clients with the use of external big data sets. Logistic regression method was deployed to test the model [3]. The list can go on. But the work most relevant to mine, to the best of author’s knowledge, is that of Kouvelis and Zhao (2016), where they studied contract design and coordination of a supply chain with one supplier and one retailer, both of which are capital constrained and in need of short-term financing for their operations[1]. We ignore the capital constraint of suppliers because it’s irrelevant in some cases when it comes to the case of China, where suppliers have a larger scale of economy compared to retailers. We further expand the settings by considering a nonzero inventory level, which is specifically tailored to mimic the external shock. Some other settings are also generalized. This comes at the expense of analytical tractability, but the result can be applied readily in reality. My work is only preliminary and the first attempt at such a unified model, and some considerations (e.g., supply chain coordination, trade-credit) can be integrated in my model, which might be a future research path.

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In short, as the first paper to target a unified model for external shock, this paper is relevant to a larger audience. Supply chain under such circumstances can use my model to analyze performance numer- ically. Banks can use such a model to identify which supply chain to finance and the government can use qualitative results to pinpoint which supply chain is vulnerable and thus, needs governmental subsidy to continue its operations. Further research can provide information for these audiences by tailor- ing specifically for those questions. That said, my current research is only a first attempt, and can be viewed as a foundation for future research.
 

References

1. [1]  Panos Kouvelis and Wenhui Zhao. Supply chain contract design under financial constraints and bankruptcy costs. Management Science, 62(8):2341–2357, 2016.

2. [2]  Chang Hwan Lee and Byong-Duk Rhee. Trade credit for supply chain coordination. European Journal of Operational Research, 214(1):136–146, 2011.

3. [3]  XiaojunWang,LeroyWhite,XuChen,XiandeZhao,KwanHoYeung,QiupingHuang,andXiaoSong. Improving the predictability of business failure of supply chain finance clients by using external big dataset. Industrial Management & Data Systems, 2015.

4. [4]  Xinhan Xu, Xiangfeng Chen, Fu Jia, Steve Brown, Yu Gong, and Yifan Xu. Supply chain finance: A systematic literature review and bibliometric analysis. International Journal of Production Economics, 204:160–173, 2018.

5. [5]  TiantianZhang,CherryYiZhang,andQifanPei.Misconceptionofprovidingsupplychainfinance: Its stabilising role. International Journal of Production Economics, 213:175–184, 2019.