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Robust New Product Pricing
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DOI：10.1287/mksc.2015.0914.png)
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We study the pricing decision for a monopolist launching a new innovation. At the time of launch, we assume that the monopolist has incomplete information about the true demand curve. Despite the lack of objective information the firm must set a retail price to maximize total profits. To model this environment, we develop a novel two-period non-Bayesian framework where the monopolist sets the price in each period based only on a nonparametric set of all feasible demand curves. Optimal prices are dynamic as prices in any period allow the firm to learn about demand and improve future pricing decisions. Our main results show that the direction of dynamic introductory prices (versus static prices) depends on the type of heterogeneity in the market. We find that (1) when consumers have homogeneous preferences, introductory dynamic price is higher than the static price; (2) when consumers have heterogeneous preferences and the monopolist has no ex ante information, the introductory dynamic price is the same as the static price; and (3) when consumers have heterogeneous preferences and the monopolist has ex ante information, the introductory dynamic price is lower than the static price. Furthermore, the degree of this initial reduction increases with the amount of heterogeneity in the ex ante information.
Keyword:
non-Bayesian learning
ambiguity
pricing
new products
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10.1
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