We derive conditions on the learning environment - which encompasses both Bayesian and non-Bayesian processes - ensuring that an efficient allocation of resources is achievable in a dynamic allocation environment where impatient, privately informed agents arrive over time, and where the designer...

Arne Ryde Memorial Lectures Series List -- Contents -- About the Arne Ryde Foundation -- Acknowledgments -- 1 Introduction -- 2 The Sequential Assignment of Heterogeneous Objects -- 3 Dynamic Revenue Maximization with Heterogeneous Objects -- 4 The Stochastic and Dynamic Knapsack Model -- 5...

We analyze dynamic allocations in a model with uncertain demand and with unobservable arrivals. The planner learns along the way about future demand, but strategic agents, who anticipate this behavior, strategically choose the timing of their arrivals. We examine the conditions under which the...