Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds recommendation-induced utility, low-rank heterogeneity, and flexible...

Algorithm- and data-based recommendation systems (DARS) have become a central component of the digital economy, shaping how users access, evaluate, and consume information and goods. These systems encompass both search rankings tailored to estimated user preferences and direct recommendations...