Pricing for the Stars: Dynamic Pricing in the Presence of Rating Systems

Abstract

Maintaining good ratings increases the profits of sellers on online platforms. We analyze the role of strategic pricing for ratings management in a setting where a monopolist sells a good of unknown quality. Higher prices reduce the value for money, which on average worsens reviews. However, higher prices also induce only those consumers with a strong taste for the product to purchase, which on average improves reviews. Our model flexibly parametrizes the two effects. This parametrization can rationalize the observed heterogeneity in the relationship between reviews and prices. Based on an analytic characterization of the optimal dynamic pricing strategy, we study a platform’s choice of the sensitivity of its rating system to incoming reviews. The optimal sensitivity depends on the effect of prices on reviews and on how the platform weighs consumers and sellers in its objective. Although sellers always benefit from more sensitivity, consumers may suffer from higher prices and from slower learning from reviews due to endogenously emerging price and rating cycles. This paper was accepted by Kartik Hosanagar, information systems. Funding: This work was supported by the Deutsche Forschungsgemeinschaft [CRC TR 224, Project C3]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4771 .

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 30 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.