Fulfilling online orders quickly is increasingly vital in e-commerce, with many companies offering same-day shipment to meet rising customer expectations. However, firms risk overpromising when shipment options and fees are not aligned with their fulfillment capacity, leading to delayed orders and customer dissatisfaction. Fulfillment centers may be unable to hand over all orders to parcel delivery companies by the agreed deadlines. To avoid this, shipment options and fees should be adapted based on information that is both operationally relevant and marketable to customers—namely, the time remaining for the fulfillment center to collect and ship these orders.

We develop a parsimonious model of a fulfillment center with Poisson customer arrivals, stochastic processing capacity, and the objective of maximizing long-run average profit, and provide an exact steady-state analysis based on a periodic Markov chain. As shipment fees affect both the volume and timing of same-day demand, direct analysis in the price domain is analytically intractable. We therefore devise a problem-domain transformation that maps each shipment policy to its induced cumulative demand profile. This transformation enables both structural insights—the optimal shipment policy includes a cutoff point and monotonically increasing fees—and tractable optimization, as the reformulated profit function is supermodular, allowing computation of the optimal shipment policy in polynomial time. We also propose a simple shipment policy with a two-level fee structure that is easy to communicate to customers and achieves near-optimal performance.

Overall, transparent time-dependent shipment policies provide a customer-friendly alternative to opaque dynamic pricing, allowing e-commerce companies to align same-day demand with fulfillment capacity while maintaining fairness and simplicity.