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Join us to hear from Huiyi Guo, Texas A&M University, presenting, "Learning by Consuming: Optimal Pricing for a Divisible Good". 

Abstract
We study the revenue-maximizing mechanism when a buyer’s value evolves because
of learning-by-consuming. The buyer chooses the initial consumption based on his rough
valuation. Consuming more induces a finer valuation estimate, after which he determines
the final consumption. The seller faces the tradeoff that selling more initially makes selling
the rest more profitable but on a smaller base. The optimum is a try-and-decide contract.
In equilibrium, a higher first-stage valuation buyer chooses more initial consumption and
enjoys a lower second-stage per-unit price. Methodologically, we address the difficulty that
without the single-crossing condition, monotonicity plus envelope condition is insufficient
for incentive compatibility. Our results help to understand contracts with learning features,
e.g., course packages with included sessions and leasing agreements for experience goods