Clinching Auctions with Online Supply

TL;DR

This paper introduces an online auction mechanism for perishable goods like internet ad inventory, ensuring incentive compatibility and Pareto optimality without prior supply knowledge, especially with buyers' budget constraints.

Contribution

It presents an adaptive clinching auction that is supply-monotonic, incentive-compatible, and Pareto-optimal in an online supply setting with budget-constrained buyers.

Findings

The auction is individually rational and incentive-compatible.

It achieves Pareto optimality without knowing total supply in advance.

The model applies to online ad allocation and sponsored search scenarios.

Abstract

Auctions for perishable goods such as internet ad inventory need to make real-time allocation and pricing decisions as the supply of the good arrives in an online manner, without knowing the entire supply in advance. These allocation and pricing decisions get complicated when buyers have some global constraints. In this work, we consider a multi-unit model where buyers have global {\em budget} constraints, and the supply arrives in an online manner. Our main contribution is to show that for this setting there is an individually-rational, incentive-compatible and Pareto-optimal auction that allocates these units and calculates prices on the fly, without knowledge of the total supply. We do so by showing that the Adaptive Clinching Auction satisfies a {\em supply-monotonicity} property. We also analyze and discuss, using examples, how the insights gained by the allocation and payment rule can be applied to design better ad allocation heuristics in practice. Finally, while our main technical result concerns multi-unit supply, we propose a formal model of online supply that captures scenarios beyond multi-unit supply and has applications to sponsored search. We conjecture that our results for multi-unit auctions can be extended to these more general models.