A Directed Lazy Random Walk Model to Three-Way Dynamic Matching Problem

TL;DR

This paper introduces a new model for three-way dynamic matching involving agents from three populations with different preferences, analyzing how stable and efficient outcomes emerge over time.

Contribution

It extends dynamic matching theory to three-way matches with complex preferences, providing a novel analytical framework and demonstrating existence of stable solutions.

Findings

Stable and efficient outcomes can be achieved in three-way dynamic matching.

Preference structures significantly influence the matching dynamics.

The model characterizes transition probabilities and stationary distributions for complex matching environments.

Abstract

This paper explores a novel extension of dynamic matching theory by analyzing a three-way matching problem involving agents from three distinct populations, each with two possible types. Unlike traditional static or two-way dynamic models, our setting captures more complex team-formation environments where one agent from each of the three populations must be matched to form a valid team. We consider two preference structures: assortative or homophilic, where agents prefer to be matched with others of the same type, and dis-assortative or heterophilic, where diversity within the team is valued. Agents arrive sequentially and face a trade-off between matching immediately or waiting for a higher quality match in the future albeit with a waiting cost. We construct and analyze the corresponding transition probability matrices for each preference regime and demonstrate the existence and uniqueness of stationary distributions. Our results show that stable and efficient outcomes can arise in dynamic, multi-agent matching environments, offering a deeper understanding of how complex matching processes evolve over time and how they can be effectively managed.