Abstract
Our work offers an understanding of how capital efficiency metrics, such as Return-on-Investment (ROI), affect orders at a stand-alone single stocking stage under demand uncertainty or within bilateral supply chains of a supplier and buyer interacting with the use of a trade-credit-contract. In both environments, the buyer is looking for financing its inventories either through a bank or through the supplier via extended payment terms. In the single stocking stage case, our buyer – the newsvendor – exhibits conservative behaviour and orders less than the traditional quantity. The analysis of the bilateral supply chain of our newsvendor buyer and a supplier, who is willing to finance the buyer's inventories via trade-credit contract, continues to support the low interest rate of such contracts. Interestingly now the buyer orders more than under profit optimisation. The ROI-driven buyer enjoys higher margins due to unusually low supplier financing rates even at slightly increased wholesale. The overall supply chain efficiency improves, and the supplier increases her percentage of the chain profit by offering higher wholesale prices but accepting some inventory financing risk. Using ROI to make ordering decisions better aligns these decisions with sound working capital management metrics while accounting in a balanced way for profit margins.
Data availability statement
Data sharing is not applicable to this article as no new data were created or analysed in this study.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 ROI definition: the ratio of (gain of investment – cost of investment) over the (cost of investment).
2 The failure rate of a distribution is defined as . Most of the distributions used in the supply chain problem, i.e. uniform, gamma, Weibull, modified extreme value and the truncated normal distribution when their parameters are the commonly accepted ones, has a increasing failure rate.
3 Analysis similar to Kouvelis and Zhao (Citation2011).
4 See Appendix 2 for more details.
5 Other parameters including c, p, and are too straightforward.
6 ‘The apparel industry had an inventory problem before coronavirus. What now?’ https://www.supplychaindive.com/news/apparel-inventory-coronavirus-covid19/574785/
7 The inequalities etc. are obtained in other regions.
Additional information
Notes on contributors
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Panos Kouvelis
Dr. Panos Kouvelis is the Emerson Distinguished Professor of Operations and Manufacturing Management at Washington University in St. Louis. He is also the Director of The Boeing Center for Supply Chain Innovation, a supply chain management research centre operating within Washington University's Olin Business School. Prior to joining Olin, Panos Kouvelis served as an associate professor at the Fuqua School of Business at Duke University and as an assistant professor at the University of Texas at Austin. He has published three books and over 80 papers in top-quality academic journals. Kouvelis has held visiting appointments with the Graduate School of Business, University of Chicago, where he taught in the executive programs in Barcelona, Chicago and Singapore, WHU – Koblenz School of Management, Germany, and Singapore Management University, Singapore.
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Yunzhe Qiu
Yunzhe Qiu is currently a Ph.D. Candidate in Supply Chain, Operations, and Technology at Olin Business School, Washington University in St. Louis. He received the M.S. in Industrial Engineering and Management from Peking University, B.E. in Industrial Engineering from Tsinghua University. He is broadly interested in the Interface of Finance, Operations, and Risk Management, Supply Chain Management, Business Analytics, Dynamic Program, and Simulation Optimization.