This paper shows that a rm may benefit from restricting capacity so as to trigger herding behavior from consumers, in situations where such behavior is otherwise unlikely. We consider a setting with social learning, where consumers observe sales from previous cohorts and update beliefs about product quality before making their purchase. A capacity constraint directly limits sales but also results in coarser information: upon observing a sellout, consumers attach positive probability to all levels of demand that exceed the constraint. The resulting discrete jump in beliefs following a sellout benefits the firm, and can make it optimal to restrict capacity.
Abstract: We consider a general model of a market for differentiated goods, in which firms are located in marketplaces: shopping malls or platforms. There are search frictions between the marketplaces, but not within them. Marketplaces differ in their size. We show that consumers prefer to start their search from the largest marketplace and continue in the descending order of their size. We show that the descending search order is the only search order which can be a part of an equilibrium for any market cofiguration. Despite charging lower prices, firms at larger marketplaces earn higher profits, and under free entry all firms cluster at one place. If a marketplace determines the price of entry, the equilibrium marketplace size depends negatively on search costs.