Coopetition Against an Amazon

TL;DR

This paper explores optimal data-sharing strategies among competing firms, including scenarios with a dominant external competitor like Amazon, revealing conditions that influence the extent of cooperation based on competitive pressures.

Contribution

It introduces simple, threshold-based data-sharing schemes that are proven to be optimal or near-optimal in competitive settings involving an external data-rich competitor.

Findings

Threshold rules effectively induce optimal data-sharing.

Stronger outside competition can lead to increased data sharing.

Situations exist where external competition reduces data sharing.

Abstract

This paper studies cooperative data-sharing between competitors vying to predict a consumer's tastes. We design optimal data-sharing schemes both for when they compete only with each other, and for when they additionally compete with an Amazon -- a company with more, better data. We show that simple schemes -- threshold rules that probabilistically induce either full data-sharing between competitors, or the full transfer of data from one competitor to another -- are either optimal or approximately optimal, depending on properties of the information structure. We also provide conditions under which firms share more data when they face stronger outside competition, and describe situations in which this conclusion is reversed.