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Title:

Matching supply and demand in crowdshipping: A theoretical framework

Accession Number:

01763862

Record Type:

Component

Abstract:

The emergence of internet and smartphones had played an important role in the increase of on-demand economy. Crowdshipping (CS)  is an emerging trend that is expected to reduce the externalities caused by Urban Freight Transport (UFT).  However, modelling the CS services, predicting their market share and their effect in the network is not a trivial task. CS matches the demand created by freight transport companies with the available capacity offered by passengers. Currently a gap exists in the literature on models that integrate the decisions related to the supply and the choices that identify the demand and matches them in the real-time. This paper presents a theoretical methodological framework that proposes an innovative collection of preference data in order to develop choice models that identify the need willingness of commuters to crowdship. In parallel it calculates the demand and proposes the development of a real-time matching simulator for the assignment of packets to crowdshippers and then to the network.

Supplemental Notes:

This paper was sponsored by TRB committee AT025 Standing Committee on Urban Freight Transportation.

Report/Paper Numbers:

TRBAM-21-03959

Language:

English

Corporate Authors:

Transportation Research Board

Authors:

Kourounioti, Ioanna
Tsouros, Ioannis
Georgakis, Panos
Salas, Angelica
de Bok, Michiel
Tsirimpa, Athena
Pagoni, Ioanna
Thoen, Sebastiaan
Eggers, Larisa
Polydoropoulou, Amalia
Tavassy, Lóránt

Pagination:

16p

Publication Date:

2021

Conference:

Transportation Research Board 100th Annual Meeting

Location: Washington DC, United States
Date: 2021-1-5 to 2021-1-29
Sponsors: Transportation Research Board; Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References

Subject Areas:

Data and Information Technology; Freight Transportation; Operations and Traffic Management

Source Data:

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-03959

Files:

TRIS, TRB, ATRI

Created Date:

Dec 23 2020 11:13AM