I provide an analysis of vertical relations in markets with imperfect competition at both layers of the supply chain and where exchange is intermediated either with wholesale prices or revenue-sharing contracts. Revenue-sharing is extremely attractive to firms that are able to set the revenue shares but often makes the firms that set retail prices worse off. This is so whether revenue-sharing lowers or raises industry profits. These results are strengthened when a market moves from “the wholesale model” of sales to “the agency model” of sales, which results in retailers setting revenue shares and suppliers setting retail prices. I also show that retail price-parity restrictions raise industry prices. These results provide a potential explanation for why many online retailers have adopted the agency model and retail price-parity clauses.

I propose a framework in which asymmetric multiproduct retailers compete for one-stop shoppers who have biased beliefs about their future purchase probabilities (and so make unplanned purchases). One firm carries a full portfolio of products while the other carries an incomplete but endogenous one. Using this framework, I examine the phenomenon of loss leading, the optimal product portfolio of the smaller firm, and the effects of banning loss leading. Among other results, I show that there is a nonpredatory (and possibly procompetitive) justification for the observation that such larger firms may charge below cost on the core product lines of their smaller rivals.

We investigate the ability of a platform to design its marketplace to promote competition, improve consumer surplus, and increase its own payoff. We consider demand‐steering rules that reward firms that cut prices with additional exposure to consumers. We examine the impact of these rules both in theory and by using simulations with artificial intelligence pricing algorithms (specifically Q‐learning algorithms, which are commonly used in computer science). Our theoretical results indicate that these policies (which require little information to implement) can have strongly beneficial effects, even when sellers are infinitely patient and seek to collude. Similarly, our simulations suggest that platform design can benefit consumers and the platform, but that achieving these gains may require policies that condition on past behavior and treat sellers in a nonneutral fashion. These more sophisticated policies disrupt the ability of algorithms to rotate demand and split industry profits, leading to low prices.

We propose a framework for analyzing transformations of demand. Such transformations frequently stem from changes in the dispersion of consumers' valuations, which lead to rotations of the demand curve. In many settings, profits are a U-shaped function of dispersion. High dispersion is complemented by niche production, and low dispersion is complemented by mass-market supply. We investigate numerous applications, including product design; advertising, marketing and sales advice; and the construction of quality-differentiated product lines. We also suggest a new taxonomy of advertising, distinguishing between hype, which shifts demand, and real information, which rotates demand.

Firms selling multiple quality-differentiated products frequently alter their product lines when a competitor enters the market. We present a model of multiproduct monopoly and duopoly using a general “upgrades” approach that yields a powerful analytical framework. We provide an explanation for the common strategies of using “fighting brands” and of product line “pruning.” The optimal strategy depends on whether entry prompts an incumbent to expand or contract its total output. We also present a general condition that guarantees that a monopolist will sell but a single product. Our model addresses other issues, including intertemporal price discrimination and “damaged goods.”