Heterogeneous Position Effects and the Power of Rankings

Abstract

Many online retailers and search intermediaries present products on ranked product lists. Because changing the ordering of products influences their revenues and consumer welfare, these platforms can design rankings to maximize either of these two metrics. In this paper, I study how rankings serving these two objectives differ and what determines this difference. First, I highlight that when position effects are heterogeneous, rankings can increase both revenues and consumer welfare by increasing the overall conversion rate. Second, I provide empirical evidence for this heterogeneity, highlighting that cheaper alternatives have stronger position effects. Finally, I quantify revenue and consumer welfare effects across the different rankings. To this end, I develop an estimation procedure for the search and discovery model of Greminger (2022) that yields a smooth likelihood function by construction. The results from the model show that rankings designed to maximize revenues can also increase consumer welfare. Moreover, these revenue-based rankings reduce consumer welfare only to a limited extent relative to a consumer-welfare-maximizing ranking.