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.
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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 r...
»