This thesis is concerned with queueing models where demand is allowed to exceed the system capacity, and also with the capacity sizing and pricing problem for heterogeneous products and resources under demand uncertainty. Our aim is to improve productivity and profitability. In the first part of the thesis, we consider the dynamic assignment of servers to tasks in queueing networks where demand may exceed the capacity for service. The objective is to maximize the system throughput. We use fluid limit analysis to show that several quantities of interest, namely the maximum possible throughput, the maximum throughput for a given arrival rate, the minimum arrival rate that will yield a desired feasible throughput, and the optimal allocations of servers to classes for a given arrival rate and desired throughput, can be computed by solving linear programming problems. We develop generalized round robin policies for assigning servers to classes for a given arrival rate and desired throughput, and show that our policies achieve the desired throughput as long as this throughput is feasible for the arrival rate. We conclude with numerical examples that illustrate the points discussed and provide insights into the system behavior when the arrival rate deviates from the one the system is designed for. In the second part of the thesis, we consider the effects of inspection and repair stations on the production capacity and product quality in a serial line with possible inspection and repair following each operation. We consider multiple defect types and allow for possible inspection errors that are defect dependent. We construct a profit function that takes into account inspection, repair, and goodwill costs, as well as the capacity of each station. Then we compare the profitability of different inspection plans and discuss how to identify the optimal inspection plan. Finally, in the third part of the thesis, we consider the capacity and pricing decisions made by a monopolistic firm producing two heterogeneous products under demand uncertainty. The objective is to maximize profit. Our model incorporates dedicated and flexible resources, product substitutability, and processing rates that may depend on the product and on the resource type. We provide the optimum prices and production quantities as functions of resource capacities and demand intercepts. We also show that investment in flexible capacity is only desirable when it is optimal to invest in dedicated capacities for both products, and obtain upper bounds for the costs of the dedicated capacities that need to be satisfied for investment in the flexible resource. We conclude with numerical examples that illustrate the points discussed and provide insights into how the optimal capacities and expected production quantities, prices, and profit depend on various model parameters.