Investigating multi-parcel crowdsourcing logistics for B2C e-commerce last-mile deliveries
Arianna Seghezzi, Riccardo Mangiaracina
Abstract
B2C e-commerce last-mile delivery (LMD) is a critical process, considering both efficiency and effectiveness: it implies high costs, and online customers have stringent service level expectations. One promising LMD solution based on crowdsourcing logistics (CL) is the ‘multi-parcel’ paradigm (each rider accomplishes different deliveries in the same tour). This work analyses the impact of multi-parcel CL on delivery costs compared to traditional by-van LMD. First, it develops an analytical model that –generating customers’ demand and assigning deliveries to riders– computes both CL and traditional LMD costs. Second, the model is applied to a case in Milan, Italy. Third, sensitivity analyses are run on key variables/parameters. Multi-parcel CL entails significant benefits compared to traditional LMD (about 11% saving). On the academic side, this work contributes to the literature, proposing a model that investigates the performances of multi-parcel CL. On the managerial side, it may support practitioners in implementing this innovative delivery solution.