Inventory availability commitment under uncertainty in a dropshipping supply chain

Abstract

Dropshipping, where e-retailers manage marketing and dropshippers manage inventory and fulfillment, has become a common practice in e-commerce. However, due to information asymmetry, some e-retailers require dropshippers to share available inventory quantity committed to them on a periodic basis (x-hour, day,...), via an availability commitment. Such commitment leaves the potential for dropshippers to overpromise and exploit availability pooling benefit as it does not involve physical transaction. To further prevent fulfillment failure, some e-retailers stop accepting more orders once remaining promised quantity falls below a promised availability threshold, which is unknown to the dropshipper. In this paper, leveraging the collaboration with a dropshipping furniture manufacturer in the US market, we tackle the inventory availability commitment (IAC) problem for dropshippers at the operational decision level. Three commitment policies are proposed based on varying overpromising allowance: guaranteed fulfillment, controlled fillrate, and penalty-driven fillrate policies. The IAC optimization problem, under uncertain customer demand and retailers threshold, is modeled as a two stage stochastic program. Experimental results on a case study demonstrated that penalty-driven fillrate policy is a dominating policy for a dropshipper under any availability level while the impact of overpromising is maximized under lean availability. E-retailers imposing thresholds tend to receive more availability than those not imposing any threshold in general. However, non-overpromising dropshippers with lean or lower availability level will promise less availability to e-retailers imposing threshold.