A dynamic crowdshipping model and daily travel behavior

Using a dynamic optimization model, we study the transaction of pickup/delivery activities between two groups of individuals: carriers and requesters, in a P2P crowdshipping model. Based on their value of time, requesters set maximum willingness to pay for their parcels to be picked up and delivered and carriers, make an offer depending on the changes that needs to be made to their original itinerary. The proposed model was tested for Los Angeles and Orange Counties, with 27% of successful matches, also demonstrating the impacts of crowdshipping on regional travel behavior and shifts in space-time distribution of the demand.