Research
Working Papers
Harvesting Ratings with Johannes Johnen
Download Paper
Web Appendix
Fun Graphics
Abstract
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.
Cite as: Johnen, J. and Ng, R. (2024). Harvesting Ratings. CRC TR 224 Discussion Paper No. 509.
Free and Open-Source Software: Coordination and Competition
Download Paper
Fun Graphics to come!
Abstract
Free and Open-Source Software (FOSS) are developed by a community of developers led by a coordinator. To attract more developers, coordinators may increase FOSS quality by improving coordination. However, more developers create more diverse views, and permissive FOSS licenses mean additional developers drive FOSS characteristics away from the preferences of existing developers. Permissive FOSS licenses induce competition, leading to lower prices, but lower the incentive to coordinate FOSS, leading to lower quality FOSS serving only niche markets. I study coordinators with different motives: self-interested Founders; volunteering Altruists; profit-driven Managers, showing that permissive licenses only favour Managers.
Cite as: Ng, R. (2024). Free and Open-Source Software: Coordination and Competition. CRC TR 224 Discussion Paper No. 585.
Ratings with Heterogeneous Preferences with Jonathan Lafky
Draft available, do reach out!
Abstract
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.
Some Works In Progress
Competition through Recommendations
Coming to you this summer fall!
Abstract
Consumers rely on recommendations of platforms when purchasing products. I examine a platform's decision to provide product recommendations which are informative of value-for-money. More informative recommendations have two effects: (i) a screening effect, where lower quality firms exit the platform; and (ii) a ranking effect, where consumers interact more with higher quality firms. Of the remaining firms, screening benefits higher quality firms, while ranking benefits only the highest quality firms. Both effects increase consumer surplus, attracting more consumers to the platform. However, more informative recommendations lead to fierce price competition between firms. Hence, a platform has to balance volume and commission fees. When facing competition, a platform's recommendation becomes more informative when it's competitor has a more informative recommender system.