Crowdshipping is a new delivery paradigm that exploits the capacity of ordinary people who offer their own vehicles and free time to perform deliveries against compensation. In this work, we consider a peer-to-peer logistic platform where a company receives orders from its customers and assigns them to occasional drivers (ODs), or crowdshippers, who perform the delivery operations. We first investigate the problem of deciding how the orders should be partitioned into bundles, where a bundle is a set of orders assigned to the same OD. Then, we focus on the problem of determining the compensation associated with each bundle, with the purpose of minimizing the total delivery costs. The pricing scheme is based on the assumption that each OD is associated with a willingness-to-serve function, which is modeled as a random variable that gives the probability that the OD accepts to deliver the bundle given the compensation value. This random variable captures the estimation of the willingness-to-serve function that the company has elaborated, for example on the basis of historical data. If the compensation offered by the company is greater than or equal to the willingness-to-serve value, the OD performs the delivery, otherwise she/he refuses. In case no OD is available to deliver a bundle, then all packages in the bundle are offered to a third-party delivery company. We simulate two auction systems for the assignment of bundles to ODs: a static and a dynamic auction. In exhaustive simulation tests, we compare different pricing schemes as well as the two auction systems, and outline several managerial insights.
Bundles generation and pricing in crowdshipping
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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