Dynamic Revenue Maximization with Heterogeneous Objects
Dynamic Revenue Maximization with Heterogeneous Objects
In this chapter the authors study the revenue maximizing allocation of several heterogeneous, commonly ranked objects to impatient agents with privately known characteristics who arrive sequentially. There is a deadline after which no more objects can be allocated. The authors first characterize implementable allocation schemes, and compute the expected revenue for any implementable, deterministic and Markovian allocation policy. The revenue-maximizing policy is obtained by a variational argument which sheds more light on its properties than the usual dynamic programming approach. Finally, the authors use their main result in order to: a) derive the optimal inventory choice; b) explain empirical regularities about pricing in clearance sales.
Keywords: Revenue maximization, deadline effect, allocation and price dynamics
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