Financing the newsvendor with preferential credit: bank vs. manufacturer

Abstract

This paper examines how preferential credit based on retailers’ credit line impacts on capital-constraint retailer’s operational decisions. We consider a condition of loan competition when banks and manufacturers offer preferential credit to capital-constraint retailers in the newsvendor model. Different credit lines and discounted rates of preferential credit mainly involve in retailers’ exogenous collateral and risk preference of banks and manufacturers in our model. We investigate impacts of bank financing, trade credit, and portfolio credit (financing from both bank credit and trade credit with different ratios) on retailer’s inventory decision with different cases that the retailer’s financing amounts exceed credit line or not. We derive the equilibrium wholesale price, expected sale price, and order quantity when retailers face with different conditions of collaterals and institutes’ risk preferences facing with market risk. A debt-financed retailer favours items with trade credit compared to bank financing, especially in conditions when its sourcing demand is great and when it finances from high-risk preference institutes. Retailer prefers to using the loan with high trade credit ratio when he opts portfolio credit conditions.

Keywords:

• supply chain financing
• default risk
• preferential credit
• trade credit
• bank finance

Acknowledgements

This work was supported in part by the Ministry of Science and Technology of China under Grant 2016YFC0503606, in part by the National Natural Science Foundation of China under Grant 71825007, in part by the Chinese Academy of Sciences Frontier Scientific Research Key Project under Grant QYZDB-SSW-SYS021, in part by the CAS Strategic Research and Decision Support System Development under Grant GHJ-ZLZX-2019-33-3, in part by the Marianne and Marcus Wallenberg Foundation under Grant MMW 2015.0007, in part by the Strategic Priority Research Program of CAS under Grant XDA23020203 and supported by the International Partnership Program of Chinese Academy of Sciences, Grant No.211211KYSB20180042.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 See: https://www.ft.com/content/9ebcdfaa-b012-11dd-a795-0000779fd18c.

2 See: http://boeing.mediaroom.com/2012-02-17-Boeing-Citi-Start-Export-Import-Bank-Supplier-Financing-Program.

3 See: https://decisionsciences.org/two-keynotes-to-highlight-2019-conference/.

4 See: https://caspiannews.com/news-detail/made-in-azerbaijan-expected-to-diversify-economy-2019-2-1-28/.

5 See: http://finance.sina.com.cn/roll/2019-01-16/doc-ihqfskcn7466096.shtml.

6 See: http://www.cb.com.cn/index/show/jj/cv/cv1152735797.

7 See: https://www.globalbankingandfinance.com/committed-to-your-success-banking-in-sri-lanka-with-ndb-bank/.

8 In this part, the banks’ credit is zero. We could define the $L_B=0$. Then, we obtain the discount rate for trade credit is $r_M-eu{L}_C$.

Additional information

Funding

This work was supported in part by the Strategic Priority Research Program of CAS under [grant number XDA23020203], the National Natural Science Foundation of China under [grant number 71825007], the Chinese Academy of Sciences Frontier Scientific Research Key Project under [grant number QYZDB-SSW-SYS021], Marianne and Marcus Wallenberg Foundation under [grant number MMW 2015.0007], and the International Partnership Program of Chinese Academy of Sciences [grant number 211211KYSB20180042].