Pricing Models for Crowdsourced Logistics Platforms: A Two-Sided Market Perspective

Abstract

The application of the crowdsourcing model to instant delivery has achieved remarkable success. Various crowdsourced logistics platforms have successfully addressed the challenges of last-mile delivery in urban areas by eliciting the active involvement of the public. This study takes a dual-market perspective and, considering the high requirements of instant delivery for timeliness, introduces two crucial factors: platform subsidies and the degree of public involvement. We establish a pricing model based on the Hotelling model and conduct in-depth research on the platform’s maximum profit and equilibrium pricing under different user attribution conditions. This study reveals that when the dispatching party has a single attribution, the platform can increase profits by reducing the intensity of cross-network externalities or increasing user transfer costs. In cases where the dispatching party has partial multiple attributions and the receiving party has a single attribution, lowering network externalities, increasing platform subsidies, enhancing public involvement, improving platform technical matching rates, and increasing the expected order quantity of the dispatching party all effectively increase the platform’s maximum profit. When both sides of users have partial multiple attributions, increasing public involvement increases the platform’s maximum profit. This research provides new theoretical support for the pricing strategy of crowdsourced logistics platforms.