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Dr. Amanda Stathopoulos - Empirical analysis of crowd-sourced freight deliveries

Thursday 10 November 2016

Assistant Professor of Civil and Environmental Engineering, Northwestern University.

Empirical analysis of crowd-sourced freight deliveries

Thursday 10th November 2016


This seminar presents results from empirical analysis of crowd-sourced freight deliveries in the US. Crowd-sourced deliveries build on the idea that citizens deliver goods, ideally along planned travel routes. Crowdshipping has a potential to match highly fragmented transport capacities with vastly diverse demand for urban freight deliveries, temporally, spatially and in real-time. This is typically achieved through platforms that connect carriers with consumers in need of deliveries. A third-party broker, who operates the platform, provides match-making, analysis and customer services between demand and supply. The main advantage of crowdshipping is the reduced need for fixed facilities, such as cars or warehouses, to run operations. The main obstacles are trust, liability issues, and ensuring a critical mass of couriers and customers. Despite the growth in operations, there is still a poor understanding of the performance, functionality and acceptability of these new delivery methods.
The seminar presents results analyzing the performance in the early stages of operation of crowdshipping. Based on real operational data from 2 years across the US the performance is examined with an emphasis on the specificity of crowdshipping, namely related to delivery variability and the temporal matching dynamics. Based on additional survey experiments the behavior of the main agents in the system is modeled with an emphasis on revealing acceptance and priorities of both occasional drivers and senders.
The research derives from a Partnership-for-Innovation (PFI) project funded by the NSF where a Chicago based research team (NU, UIC) is evaluating the capabilities of CROwd-sourced Urban Delivery (CROUD) in collaboration with a crowd-shipper technology firm.