While millions of products are sold on its retail platform, Amazon.com itself stocks and sells only a very small fraction of them. Most of these products are sold by third-party sellers who pay Amazon a fee for each unit sold. Empirical evidence clearly suggests that Amazon tends to sell high-demand products and leave long-tail products for independent sellers to offer. We investigate how a platform owner such as Amazon, facing ex ante demand uncertainty, may strategically learn from these sellers' early sales which of the "mid-tail" products are worthwhile for its direct selling and which are best left for others to sell. The platform owner's "cherry-picking" of the successful products, however, gives an independent seller the incentive to mask any high demand by lowering his sales with a reduced service level (unobserved by the platform owner).
We analyze this strategic interaction between a platform owner and an independent seller using a game-theoretic model with two types of sellers—one with high demand and one with low demand. We show that it may not always be optimal for the platform owner to identify the seller's demand. Interestingly, the platform owner may be worse off by retaining its option to sell the independent seller's product, whereas both types of sellers may benefit from the platform owner's threat of entry. The platform owner's entry option may reduce consumer surplus in the early period, although it increases consumer surplus in the later period. We also investigate how consumer reviews influence the market outcome.
Jiang, Baojun, Kinshuk Jerath, and Kannan Srinivasan. "Firm Strategies in the 'Mid Tail' of Platform-Based Retailing." Marketing Science 30, no. 5 (2011): 757-775.
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