Crowd-shipping delivery performance from bidding to delivering

Alireza Ermagun*, Amanda Stathopoulos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Crowd-shipping is an innovative delivery model using digital platforms to match the demand for shipments with supply using excess transport capacity and drivers from the crowd. This sharing economy delivery concept has attracted growing attention to address the pressing challenges of urban goods deliveries. Little is known about the actual performance of crowd-shipping platforms due to limited data-availability and operational transparency. A particular challenge is that part of the delivery outcome is determined in the platform's digital space related to bidding and matching of supply and demand, followed by a real-world delivery operation, typically carried out by non-expert couriers. This paper provides the first comprehensive analysis of the entire crowd-shipping process from the bidding stage, through shipment acceptance, pickup, and final delivery. Using parametric hazard modeling applied to a unique U.S. national database of 16,850 crowd-shipping delivery instances, we examine which factors play a role in each phase of the delivery process. The findings illustrate that shipping requests and packages, built environment, and socioeconomic characteristics have a variable impact on each delivery stage. In particular, posting in the morning or evening hours and for business-to-consumer shipments significantly accelerates the digital phase, but has no effects on the final delivery phase. Moreover, the results reveal that performance loss occurs non-uniformly in the platform process, with a more significant loss in delivery rates related to the digital posting and bidding. A more substantial loss of delivery speed performance occurs in converting from digital to real delivery in negotiating the pickup arrangement. Crowd-shipping companies will benefit from the research to improve the management of their peer-to-peer-based mechanism.

Original languageEnglish (US)
Article number100614
JournalResearch in Transportation Business and Management
DOIs
StateAccepted/In press - 2020

Keywords

  • Crowdsourcing
  • Delivery market
  • Freight management
  • Freight performance
  • Package distribution
  • Urban freight

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business and International Management
  • Transportation
  • Economics, Econometrics and Finance (miscellaneous)
  • Tourism, Leisure and Hospitality Management
  • Strategy and Management
  • Management Science and Operations Research

Fingerprint

Dive into the research topics of 'Crowd-shipping delivery performance from bidding to delivering'. Together they form a unique fingerprint.

Cite this