Ratings and Reciprocity with Johannes Johnen
Evidence suggests online ratings and reviews are motivated by reciprocity. We incorporate a standard model of reciprocity into a model of ratings to capture 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’ reciprocal behaviour and obtain a good rating and larger profits in the future. Because also low-quality firms harvest ratings, reciprocity makes ratings less-informative about quality. Based on this mechanism, (i) we argue that reciprocity-based ratings cause 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. We show that even as ratings become less-informative, consumers can benefit from lower prices. 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 thereby undermines the informativeness of ratings and harms consumers.
Ratings with Heterogeneous Preferences with Jonathan Lafky
We ask how ratings are interpreted in the presence of heterogeneous preferences among both raters and consumers. Considering an environment in which ratings are provided for products with two dimensions of quality, and where both raters and consumers have heterogeneous preferences over each dimension. Under the assumption that raters are altruistic, raters should attempt to maximise the expected utility of consumers. However, an ambiguity arises in the presence of heterogeneous preferences. Multiple equilibria exist, one in which ratings serve as an expression of the rater’s preferences, and one in which ratings are instead an expression of expected consumers preferences. And we show how 3 different types of information design can help guide equilibrium selection.
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. 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, altruistic, and profit-driven. Altruistic and profit-driven coordinators fail to maximize total surplus, while self-interested coordinators generate higher total surplus than altruistic coordinators.
Competition through ratings