Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects

Aymeric Punel, Amanda Stathopoulos*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

143 Scopus citations

Abstract

Crowdshipping is a frontier in logistics systems designed to allow citizens to connect via online platforms and organize goods delivery along planned travel routes. The goal of this paper is to highlight the factors that influence the acceptability and preferences for crowdshipping. Through a survey using stated choice scenarios discrete choice models controlling for context and experience effects are specified. The results suggest that distinct preference patterns exist for distance classes of the shipment. In the local delivery setting, senders value transparency of driver performance monitoring along with speed, while longer shipments prioritize delivery conditions and driver training and experience. The model developed in this paper provides first key insights into the factors affecting preferences for goods delivery with occasional drivers.

Original languageEnglish (US)
Pages (from-to)18-38
Number of pages21
JournalTransportation Research Part E: Logistics and Transportation Review
Volume105
DOIs
StatePublished - Sep 2017

Funding

This research is based upon work supported by the National Science Foundation Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) Grant No. 1534138 Smart CROwdsourced Urban Delivery (CROUD) System.

Keywords

  • Acceptance
  • Crowdshipping
  • Discrete choice
  • Peer-to-peer delivery
  • Stated choice experiment
  • Urban freight

ASJC Scopus subject areas

  • Business and International Management
  • Civil and Structural Engineering
  • Transportation

Fingerprint

Dive into the research topics of 'Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects'. Together they form a unique fingerprint.

Cite this