Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence
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AbstractPrior works offer compelling evidence that on the demand side of the market, user- generated online product reviews play a very important role in informing consumers’ purchase decisions. On the supply side, however, the interplay between online product reviews and firm strategies is less understood. We build an analytical model that differentiates products based on consumers’ preference for tastes (horizontal differentiation) or quality (vertical differentiation) and show that a firm is able to not only manipulate its pricing to influence online product reviews (thus influencing sales), but also adjust pricing dynamically in response to online word-of-mouth. Our model derives rich and testable results on possible price trajectories. To offer empirical support for the analytical predictions, we conduct a panel data study of prices and reviews. We adopt a difference-in-differences framework to address endogeneity challenges.
Acceptance Date28/10/2018
All Author(s) ListJuan Feng, Xin Li, Xiaoquan (Michael) Zhang
Journal nameInformation Systems Research
Volume Number30
Issue Number4
Pages1107 - 1123
LanguagesEnglish-United States
KeywordsPricing, Online Product Reviews, Analytical Model, Empirical Study

Last updated on 2021-26-09 at 01:14