We study a dynamic pricing model of a fashion product under the presence of demand learning and strategic consumer behaviour. As typical to the sales of fashion goods, inventory is limited and there is a potential opportunity to resolve part of the demand uncertainty via early sales observations. Compared to a fixed-price strategy, responsive pricing offers two possible benefits to the retailer: the mere ability to offer different prices (segment the market), and the ability to respond to information (inventory status, and updated demand forecast).
Our results overwhelmingly demonstrate that the benefits of responsive pricing, in comparison to fixed-price strategies, tend to worsen as the market provides a higher potential for learning. We explain this counter-intuitive outcome by pointing to two phenomena: the spread effect, and the manipulation effect. We furthermore observe that if a seller would not have the ability to learn about the market, its performance could actually improve. This surprising result has significant ramifications for sellers of fashion products who consider upgrading their pricing systems to incorporate “accurate response” strategies.
Finally, we argue that despite the fact that price commitment completely eliminates the seller’s ability to learn, it appears to dominate responsive pricing almost across the board. But while performing better than responsive pricing, when the market size is highly uncertain and when the seller’s inventory is sufficiently large, price commitment is very limited in its ability to perform effective discrimination.