Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence

Juan Feng (), Xin Li () and Xiaoquan (Michael) Zhang ()
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Juan Feng: Department of Information Systems, College of Business, City University of Hong Kong, Kowloon, Hong Kong
Xin Li: Department of Information Systems, College of Business, City University of Hong Kong, Kowloon, Hong Kong
Xiaoquan (Michael) Zhang: Department of Decision Sciences and Managerial Economics, Business School, Chinese University of Hong Kong, New Territories, Hong Kong

Information Systems Research, 2019, vol. 30, issue 4, 1107-1123

Abstract: Prior 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.

Keywords: pricing; online product reviews; analytical model; empirical study (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orisre:v:30:y:2019:i:4:p:1107-1123

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