This study investigates the viability of a "courier friendly" crowd-shipping (CS) model to carry out express package deliveries in an urban area. Imposing almost no managerial control over the occasional couriers (OC) to maximize their willingness to participate, the envisioned model suggests using transshipment points to enhance operational efficiency and a company-controlled backup delivery capacity to account for the uncertainty in the crowd-provided delivery capacity. A dynamic programming (DP) approach is developed to address the package routing problem that needs to be solved for the real-time management of the CS network. The suggested methodology does not assume any specific distributions for the courier and demand arrivals and provides the optimal package routing policy when the courier and service point capacities are not binding. Several extensions of the basic DP approach are studied to consider limited courier and service point capacities and take advantage of the extra information provided by those couriers that declare their arrivals in advance. To the best of the author's knowledge, this study presents the first example of using Monte-Carlo simulations to determine "shadow costs" of capacity utilizations and use them in making the assignment (matching) decisions. An extensive computational study demonstrates the efficacy of the solution approach. It provides valuable insights into, among others, the potential benefits of delivering packages with a coordinated effort of OCs (with transshipments) under short delivery lead time restrictions, the impact of the spatial and temporal distribution of the demand and courier arrivals on the system performance, and the importance of the notice times for OC arrivals.
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