Crowdsourcing mode evaluation for parcel delivery service platforms

Lu Zhen, Yiwei Wu, Shuaian Wang, Wen Yi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

The fast-growing practice of e-commerce implies a strong increase in the urban parcel delivery, which in turn creates significant pressure on last-mile city logistics. Because the crowdsourced delivery offers greater flexibility and requires less capital investment than traditional delivery methods, it has been playing a more crucial role when faced with the growing demand for the urban parcel delivery. With the increasing maturity of the crowdsourced delivery and the fierce competition among platforms, the evaluation of different crowdsourcing modes for the urban parcel delivery becomes important. This study proposes six mathematical models to evaluate different operation modes of the crowdsourced delivery in a quantitative way. Several realistic factors, such as the latest service time for each task, task cancellation rate and range distribution of tasks, are also analyzed in this paper. Numerical experiments are conducted to validate the effectiveness of the proposed models and to analyze the impact of different modes. Some managerial implications are also outlined on the basis of the numerical experiments and sensitivity analysis to help crowdsourced companies to make scientific decisions.

Original languageEnglish
Article number108067
JournalInternational Journal of Production Economics
Volume235
DOIs
Publication statusPublished - May 2021

Keywords

  • Crowdsourced delivery
  • Crowdsourcing service platform
  • e-commerce
  • Parcel delivery

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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