Abstract
Over the last decade, platforms have emerged in numerous industries and often transformed them, posing new challenges for transportation research. Platform providers such as Uber, Uber Freight, Blackbuck, or Lyft mostly do not have immediate control over the physical resources needed to move people or goods. They often operate in a multi-sided market setting, where it is crucial to design clear incentives to motivate a third party to engage in collaboration. As a consequence, collaboration incentives become an integral part of decision support models for platform providers and they need to be developed at the operational level and applied dynamically. Naturally, this involves a trade-off between the interests of platform providers, shippers, and carriers. In this work, we investigate the real-world case of a platform provider operating as an intermediary between shippers and carriers in a less-than-truckload (LTL) business. We propose a new mixed-integer programming (MIP) formulation for the underlying collaborative pickup and delivery problem with time windows (PDPTW) that minimizes the price the platform pays to the carriers and enforces collaboration incentives for carriers through individual rationality constraints. This is facilitated by a dynamic pricing approach which ensures that carriers are better off collaborating than working on their own. The pricing is bounded by the costs and market conditions to keep the price range reasonable. We explore possible policies to be implemented by the platform and find that their business remains profitable when individual rationality is enforced and the platform could even guarantee increased profit margins to the carriers as incentives.
Highlights
Over the last decade, platforms have emerged in numerous industries and often transformed them, posing new challenges for transportation research
Collaboration incentives become an essential part of decision support models for platform providers, and they need to be developed at an operational planning level and applied dynamically
Transportation research, still lacks operational planning approaches that explicitly incorporate the objectives of platform providers as well as transportation service providers
Summary
Transportation platforms have been investigated seriously for about 10 years and have recently been receiving increased attention from academics. While early works have primarily focused on applications, conceptual models, and policies, recent research considers platform characteristics for operational and tactical decision support for collaboration. Though this field seems still to be in its infancy, several studies have proposed platformspecific dynamic pricing and incentive creation approaches, sometimes considering allocation methods known in cooperative game theory. Works on collaborative transportation platforms have predominantly focused on the analysis of requirements and drivers for collaboration as well as the development of conceptual models for platforms, often by investigating particular application cases. Using allocation schemes, these studies consider collaboration incentives but do not apply a dynamic pricing approach or consider a platform provider as part of the collaborative problem.
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