Last Mile Delivery Capacity Planning With Two-Sided Uncertainty

Abstract

Crowdsourced delivery (CD) is increasingly combined with private delivery (PD) to respond to last mile delivery (LMD) demand uncertainty. As independent contractors, CD drivers self-schedule, which simultaneously creates labor supply uncertainty. Consequently, such LMD capacity planning requires addressing both uncertainties concurrently, a duality we term “two-sided uncertainty.” In this setting, two key questions emerge: what is the optimal level of PD capacity when CD is available? How does two-sided uncertainty impact the PD capacity decision? To that end, we adapt a two-stage newsvendor model to explore the impact of two-sided uncertainty on optimal PD capacity when CD is available. We combine Monte Carlo simulation and optimization in empirically grounded experiments using data from a Brazilian prepared meals company. We find a positive relationship between two-sided uncertainty and PD capacity. We also reveal nuance in the relationship by identifying moderating effects due to correlation in driver availability across CD price tiers and failed delivery costs. The results also indicate that optimal delivery capacity typically combines PD and CD sources rather than relying on a single source. We show that managerial decisions based solely on lowest unit delivery cost while assuming away two-sided uncertainty can lead to suboptimal decisions.