How do Online Product Rankings Influence Sellers’ Pricing Behavior?
Products that are displayed more prominently on e-commerce platforms are more likely to be found and purchased by consumers. A product’s default positioning, however, may depend on the seller’s pricing decision. By conditioning a product’s position on its price, ranking algorithms can thus intensify, or weaken the extent of price competition between sellers. Using scraped data from hotels displayed on Expedia, I find that for a given hotel, a lower price implies a more prominent position in the ranked list of results. I provide a structural framework that allows to simulate how changes in the ranking algorithm influence hotel and platform profits, consumer surplus, and welfare. To perform these counterfactual simulations, I employ my estimates jointly with demand parameters obtained from a sequential search model by Ursu (2018).
(Paper available upon request.)