Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence

• 成果类型: Article
• 署名作者: Feng, Juan; Li, Xin; Zhang, Xiaoquan (Michael)
• 署名单位: City University of Hong Kong; City University of Hong Kong
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2019.0852
• 发表日期: 2019
• 页码: 1107-1123
• 关键词: word-of-mouth; consumer reviews; recommender systems; internet; search; MODEL; sales; COMPETITION; reputation; QUALITY

摘要

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.