Market Design for Capacity Sharing in Networks
Author(s)
Amin, Saurabh
Jaillet, Patrick
Pulyassary, Haripriya
Wu, Manxi
Date Issued
November 21, 2025
Journal
ACM Transactions on Economics and Computation
Publisher
ACM
Citation
Saurabh Amin, Patrick Jaillet, Haripriya Pulyassary, and Manxi Wu. 2025. Market Design for Capacity Sharing in Networks. ACM Trans. Econ. Comput. Just Accepted (November 2025).
Version
Final published version
Abstract
We study a market mechanism that sets edge prices to incentivize strategic agents to efficiently share limited network capacity. In this market, agents form coalitions, with each coalition sharing a unit capacity of a selected route and making payments to cover edge prices. Our focus is on the existence and computation of market equilibrium, where challenges arise from the interdependence between coalition formation among strategic agents with heterogeneous preferences and route selection that induces a network flow under integral capacity constraints. To address this interplay between coalition formation and network capacity utilization, we introduce a novel approach based on combinatorial auction theory and network flow theory. We establish sufficient conditions on the network topology and agents' preferences that guarantee both the existence and polynomial-time computation of a market equilibrium. Additionally, we identify a particular market equilibrium that maximizes utilities for all agents and is equivalent to the classical Vickrey-Clarke-Groves mechanism. Furthermore, we extend our results to multi-period settings and general networks, showing that when the sufficient conditions are not met, an equilibrium may still exist but requires more complex, path-based pricing mechanisms that set differentiated prices based on agents' preference parameters.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivatives
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3777901
