A tripartite evolutionary game model for the last-mile crowd-sourced delivery system

The last mile crowd-sourcing system is a modern transportation management model that can reduce logistics providers' costs, meet customer demand for faster delivery, and control the environmental impact. This paper proposes a tripartite evolutionary game model to analyze the interactions among logistics providers, independent drivers, and customers in a crowd-sourced last-mile delivery system. By incorporating penalty and compensation mechanisms and two delivery types, this model captures the factors that influence players' decisions. Using replicator dynamics, we determine the evolutionary stable strategies of the dynamical system. Finally, we present some numerical simulations to investigate how the key parameters affect the long-term behavior of each group of players.