Read the working paper
INSEAD Working Paper 2015/75/TOM
In this paper we explore models of repricing automation—that is, of price adjustments implemented by an algorithm in response to changes in demand, inventory, or competitors’ prices. Our setting is a typical online multi-seller platform (e.g., Amazon, eBay), where competing firms sell products differentiated by a single quality dimension (e.g., seller reputation) and where quality is proxied by an observable metric (e.g., rating score). We study the performance of different repricing algorithms as compared with equilibrium prices and also analyze the robustness of those algorithms. In particular, we investigate the possible “gaming” of the automated price response by a strategic seller with perfect knowledge of its competitor’s repricing scheme. Our analysis affirms the reasonableness of the simple structure exhibited by most repricing rules observed in practice yet also identifies their downsides.