🤖 AI Summary
In monopoly-competitive markets (e.g., Amazon’s Buy Box), price instability arises under homogeneous inspection costs, undermining buyer utility and market efficiency.
Method: Using game-theoretic modeling and mechanism design, the paper analyzes how platform display policies—particularly recommendation mechanisms that govern seller visibility—endogenously shape search frictions and equilibrium outcomes.
Contribution/Results: The paper establishes, for the first time, that platforms can achieve price-stable equilibria via differentiated recommendation mechanisms (e.g., highlighting a single seller). Counterintuitively, it shows that *moderately increasing* search friction can enhance buyer surplus. It characterizes the equilibrium price ranges supported by various natural recommendation mechanisms and demonstrates that display design serves a dual regulatory role—stabilizing prices and improving social welfare. These findings provide a theoretical foundation and actionable design principles for algorithmic governance in digital marketplaces.
📝 Abstract
Platforms design the form of presentation by which sellers are shown to the buyers. This design not only shapes the buyers' experience but also leads to different market equilibria or dynamics. One component in this design is through the platform's mediation of the search frictions experienced by the buyers for different sellers. We take a model of monopolistic competition and show that, on one hand, when all sellers have the same inspection costs, the market sees no stable price since the sellers always have incentives to undercut each other, and, on the other hand, the platform may stabilize the price by giving prominence to one seller chosen by a carefully designed mechanism. This calls to mind Amazon's Buy Box. We study natural mechanisms for choosing the prominent seller, characterize the range of equilibrium prices implementable by them, and find that in certain scenarios the buyers' surplus improves as the search friction increases.