Subsidizing Sequential Search

This paper explores a market model where competing firms use subsidies to reduce the cost of product inspection for consumers. Through a subsidy-sorting principle, the authors demonstrate that higher-quality firms naturally offer larger subsidies to signal their value and secure priority in the search order. This behavior results in a unique equilibrium where low-quality firms are ignored, intermediate firms distinguish themselves through increasing subsidies, and top-tier firms pool at the maximum subsidy cap. The study further examines how AI-mediated platforms can manipulate this dynamic by pricing "inspection tokens" to extract profit. While this platform intervention can lead to excessive search beyond what is socially optimal, it maintains consumer welfare by reallocating surplus from sellers to buyers and the platform itself. Ultimately, the research characterizes how monetary incentives can efficiently organize consumer attention and information revelation in digital marketplaces.