Utility computing models have long been the focus of academic research, and with the recent success of commercial cloud providers, computation and storage is finally being realized as the fifth utility. Computational economies are often proposed as an efficient means of resource allocation , however adoption has been limited due to a lack of performance and high overheads. In this paper, we address the performance limitations of existing economic allocation models by defining strategies to reduce the failure and reallocation rate, increase occupancy and thereby increase the obtainable utilization of the system. The strategies considered include overbooking, advanced reservation, just-in-time bidding, and using substitute providers for service delivery. The proposed strategies have been implemented in a distributed metascheduler and evaluated with respect to Grid and cloud deployments. Several diverse synthetic workloads have been used to quantity both the performance benefits and economic implications of these strategies. The high utilization strategies proposed in this paper are designed to minimize the impact of these factors to increase occupancy and improve system utilization.