Crowdshipping and Same‐day Delivery: Employing In‐store Customers to Deliver Online Orders
Iman Dayarian and
Martin Savelsbergh
Production and Operations Management, 2020, vol. 29, issue 9, 2153-2174
Abstract:
Same‐day delivery of online orders is becoming an indispensable service for large retailers. We explore an environment in which in‐store customers supplement company drivers and deliver online orders on their way home. We consider a highly dynamic and stochastic same‐day delivery environment in which online orders as well as in‐store customers willing to make deliveries arrive throughout the day. Studying settings in which delivery capacity is uncertain is novel and practically relevant. Our proposed approaches are simple, yet produce high‐quality solutions in a short amount of time that can be employed in practice. We develop two rolling horizon dispatching approaches: a myopic one that considers only the state of the system when making decisions, and one that also incorporates probabilistic information about future online order and in‐store customer arrivals. We quantify the potential benefits of a novel form of crowdshipping for same‐day delivery and demonstrate the value of exploiting probabilistic information about the future. We explore the advantages and disadvantages of this form of crowdshipping and show the impact of changes in environment characteristics, for example, online order arrival pattern, company fleet size, and in‐store customer compensation on its performance, that is, service quality and operational cost.
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)
Downloads: (external link)
https://doi.org/10.1111/poms.13219
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:popmgt:v:29:y:2020:i:9:p:2153-2174
Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1937-5956
Access Statistics for this article
Production and Operations Management is currently edited by Kalyan Singhal
More articles in Production and Operations Management from Production and Operations Management Society
Bibliographic data for series maintained by Wiley Content Delivery ().