We analyze maximization of revenue in the dynamic and stochastic knapsack problem where a given capacity needs to be allocated by a given deadline to sequentially arriving agents. Each agent is described by a two-dimensional type that reflects his capacity requirement and his willingness to pay...

We model leadership selection, competition, and decision making in teams with heterogeneous membership composition. We show that if the choice of leadership in a team is imprecise or noisy - which may arguably be the case if appointment decisions are made by non-expert administrators - then it...

We use the tools of mechanism design, combined with the theory of risk measures, to analyze how a cash constrained owner of an asset with known stochastic returns raises capital from a population of investors that differ in their risk aversion and budget constraints. The issuer partitions the...

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...