Abstract
Consumers often consult the reviews of their peers before deciding whether to purchase a new experience good; however, their initial quality expectations are typically set by the product's observable attributes. This paper focuses on the implications of social learning for a monopolist firm's choice of product design. In our model, the firm's design choice determines the product's ex ante expected quality, and designs associated with (stochastically) higher quality incur higher costs of production. Consumers are forward-looking social learners, and may choose to strategically delay their purchase in anticipation of product reviews. In this setting, we find that the firm's optimal policy differs significantly depending on the level of the ex ante quality uncertainty surrounding the product. In comparison to the case where there is no social learning, we show that (i) when the uncertainty is relatively low, the firm opts for a product of inferior design accompanied by a lower price, while (ii) when the uncertainty is high, the firm chooses a product of superior design accompanied by a higher price; interestingly, we find that the product's expected quality decreases either in the absolute sense (in the former case), or relative to the product's price (in the latter case). We further establish that, contrary to conventional knowledge, social learning can have an ex ante negative impact on the firm's profit, in particular when the consumers are sufficiently forward-looking. Conversely, we find that the presence of social learning tends to be beneficial for the consumers only provided they are sufficiently forward-looking.
Original language | English |
---|---|
Pages (from-to) | 1502-1519 |
Number of pages | 18 |
Journal | Management Science |
Volume | 65 |
Issue number | 4 |
DOIs | |
State | Published - 1 Apr 2019 |
Keywords
- Applied game theory
- Bayesian social learning
- Product design
- Product quality
- Strategic consumer behavior
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research