@inproceedings{7f00e3b3d85e4950ab84bddfd4f76746,
title = "Matching drivers and transportation requests in crowdsourced delivery systems",
abstract = "While the sales volume of e-commerce transactions is growing rapidly, the traditional concept of packages delivery has been challenged by innovative approaches such as crowdsourced delivery. Using individuals, for example commuters, to deliver packages from senders to receivers can provide several economic and environmental benefits. This paper illustrates an algorithm that automates and optimizes the assignment of drivers to transportation requests by matching them based on transportation routes and time constraints. We evaluated our algorithm by using a simulated setting based on mobility data recorded in a major German city. This paper contributes to theory by giving guidance for future research on matching algorithms for crowdsourced delivery systems and to practice by illustrating an algorithm that can be adapted by existing and new crowdsourced delivery platforms.",
keywords = "Crowdsourced Delivery, Dynamic Matching, Flow Networks, Matching Algorithm, Sharing Economy",
author = "Setzke, {David Soto} and Maximilian Schreieck and Manuel Wiesche and Christoph Pfl{\"u}gler and Sven Fr{\"o}hlich and Helmut Krcmar",
note = "Publisher Copyright: {\textcopyright} 2017 AIS/ICIS Administrative Office. All Rights Reserved.; America�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017 ; Conference date: 10-08-2017 Through 12-08-2017",
year = "2017",
language = "English",
series = "AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation",
publisher = "Americas Conference on Information Systems",
booktitle = "AMCIS 2017 - America's Conference on Information Systems",
}
