This research is motivated by the extraordinary increase in the use of intermodal shipments in recent years for both domestic and global movement of freight. Three mathematical models, which explore the dynamics of intermodal hub-and-spoke networks, are presented. These models use transportation costs, fixed location costs, modal connectivity costs, modal transit times and service time requirements, for three modes of transportation: road, rail and air. The objective is to compare the conventional over-the-road (OTR) networks with intermodal (IM) logistics networks over the financial, operational and service issues. This research extends the p-hub median approach of interacting hub network design to intermodal logistics domain. Intermodal shipments are classified as multiple class products with deterministic routings in a serial queuing network. Such an approach is used to model flow congestion at hubs and to study its impact on the hub network design. This research also develops and tests metaheuristic (Tabu Search) solution approaches. These solution approaches are benchmarked with tight lower bounds based on Lagrangian and linear relaxations. These benchmarking studies show that the metaheuristic solution approaches are suitable for solving large intermodal network design problems. In order to bring practical relevance to this work, real world data is used with the actual footprint of interstate highways, intermodal rail and air freight networks. Multiple research studies are conducted to gain useful insights into the issues related to the design and management of IM logistics networks. These studies show that the use of IM shipments can provide significant benefits in reducing total logistics costs. It is also shown that use of IM shipments requires re-alignment of a logistics network in terms of its network structure and service design. Overall, significant savings can be realized from the use of IM shipments, but operating an intermodal logistics network requires a high degree of planning and managerial control.