A multi-period multi-product stochastic inventory problem with order-based loan *

Abstract

This paper investigates a multi-period multi-product stochastic inventory problem in which a cash-constrained online retailer can leverage order-based loans provided by some Chinese e-commerce platforms to speed up its cash recovery for deferred revenue. Sample average approximation (SAA) and moment-matching scenario tree are adopted to solve this multi-stage problem with the objective of maximising the retailer's expected profit over the planning horizon. We conduct numerical tests based on crawling real data from an online store. The results show that the solutions of the two stochastic modelling approaches are very close. Moreover, the retailer tends to use order-based loans when its initial available cash is limited or it is facing a long revenue delaying length. Practitioners can make use of the modelling techniques in this paper to estimate whether it is beneficial to apply for an order-based loan.