Crowdshipping

Abstract

Thanks to growing online shopping, last mile logistics is becoming a more relevant problem for cities due to its negative impacts, such as congestion and environmental problems. In this research, one of the urban freight transport services aiming to tackle these externalities is analysed: crowdshipping. Crowdshipping is a service where the package is delivered via a traveller who is already making an unrelated trip. Trust is a key concept affecting the adoption of crowdshipping yet to be explicitly investigated . Thereby, this research aims to explore the effect of trust and examine how users' adoption can be achieved. To analyse the stated gap, a stated choice experiment is conducted to test the effect of travel time, travel cost, track and trace, insurance, damage and reputation. A Mediation Choice Model is applied to explore how the relevant attributes would impact trust towards the service adoption. Based on the findings, the direct effects of all the selected attributes were found significant, except for tracking and tracing. Regarding the indirect effects, all the main attributes were statistically significant, meaning that trust has a mediating effect on the adoption of the service. Additionally, the heterogeneity in preferences is explored through a Latent Class Choice Model resulting in a two-class latent model, crowdshipping sceptics and crowdshipping enthusiasts, the latter being more likely to be composed of younger women. Although enthusiasts consider more features while opting for crowdshipping, the delivery company's reputation and delivery cost were the most important factors in crowdshipping service adoption.