We build a model of online behavioral manipulation driven by AI advances. A platform dynamically offers one of n products to a user who slowly learns product quality. User learning depends on a product's "glossiness,' which captures attributes that make products appear more attractive than they...

We develop and estimate a model of consumer search with spatial learning. Consumers make inferences from previously searched objects to unsearched objects that are nearby in attribute space, generating path dependence in search sequences. The estimated model rationalizes patterns in data on...

Data on sales of memory modules are used to explore several aspects of e-retail demand. There is a strong relationship between e-retail sales to a given state and sales tax rates that apply to purchases from online retailers. This suggests that there is substantial substitution between online...

Search frictions can explain why the "law of one price" fails in retail markets and why even firms selling commodity products have pricing power. In online commerce, physical search costs are low, yet price dispersion is common. We use browsing data from eBay to estimate a model of consumer...

Despite substantial efforts to help consumers search in more intuitive ways, text search remains the predominant tool for product discovery online. In this paper, we explore the effects of visual and textual cues for search refinement on consumer search and purchasing behavior. We collaborate...

For some kinds of goods, rarity itself is valued. "Fashionable'" goods are demanded in part because they are unique. In this paper, we explore the economics of rare goods using auctions of limited-edition shoes held by an e-commerce platform. We model endogenous entry and bidding in multi-unit...