Harvesting Ratings with Johannes Johnen
Evidence suggests lower prices lead to better ratings, but better ratings induce firms to charge higher prices in the future. We model that consumers are only willing to make the effort to rate a seller if this seller provides a sufficient value-for-money. Using this model, we explore how firms use prices to impact their own ratings. We show that firms harvest ratings: they offer lower prices in early periods to trigger consumers to leave a good rating in order to earn larger profits in the future. Because especially low-quality firms harvest ratings, harvesting makes ratings less-informative about quality. Based on this mechanism, (i) we argue that rating harvesting causes rating inflation; (ii) we show that a marketplace that facilitates ratings (e.g. through reminders, one-click ratings etc.) may get more ratings, but also less-informative ratings; (iii) a marketplace that screens the quality of sellers makes ratings less-informative if the screening is insufficient. Counter to the conventional wisdom that consumers benefit from ratings via the information they transmit, we show that consumers prefer somewhat, but never fully informative ratings. Nonetheless consumers prefer more-informative ratings than average sellers. We apply these results to characterise when a two-sided platform wants to facilitate ratings, and argue that efforts of major platforms to facilitate ratings did not just lead to less-informative ratings, but also shifted surplus from consumers to sellers.
Ratings with Heterogeneous Preferences with Jonathan Lafky
We examine how ratings are interpreted in the presence of heterogeneous preferences among both raters and consumers. Raters with altruistic motives should rate for the benefit of future consumers, however an ambiguity arises when preferences are heterogeneous. Multiple equilibria exist in which ratings reflect either the preferences of raters or the preferences of future consumers. In an online experiment, we examine how ratings are selected by raters and interpreted by consumers, and how two types of information influence equilibrium selection. We show how both raters and consumers update their evaluation of what a rating represents in each environment, doing so in similar ways.
Free and Open-Source Software: Coordination and Competition
Free and Open-Source Software (FOSS) are developed by a community of developers led by a coordinator. Coordinators balance the following trade-off: (i) more developers improve FOSS’ quality—a positive vertical differentiation effect; (ii) more developers lead to more diverse views, driving FOSS characteristics away from existing developers’ preferences—a negative horizontal differentiation effect. To attract more developers, coordinators may improve their level of coordination, increasing the marginal vertical network effect, or adopt more permissive Open-Source licenses, increasing the marginal horizontal network effect. Permissive Open-Source licenses can intensify competition when FOSS compete with proprietary software, resulting in lower prices. I study coordinators with different motivations: self-interested Founders, volunteering Altruists, and profit-driven Managers. Altruists and Managers fail to maximize total surplus, while Founders generate higher total surplus than Altruists.
Competition through ratings
This paper explores if and how platforms design recommendation systems. I show that monopolist platforms prefer recommendation systems that are more informative than value-for-money. Although more informative recommendation systems improve total surplus, monopolist platforms do not improve consumer surplus. When facing an entrant, an incumbent platforms prefers even more informative recommendations than a monopolist. I suggest that moves to regulate recommendation systems are unlikely to be welfare improving. The existing proposals for alternative recommendation systems decreases both total surplus and consumer surplus.