Many service organizations offer services through a network of interconnected units with customer flows between them, for example, hospitals and airports. The interconnected nature of the units, along with the highly variable customer arrival and service rates, makes efficiently coordinating capacity among units extremely challenging. Capacity decisions made in isolation will be sub-optimal from a system perspective. Information sharing among the units will lead to better coordination of capacities and minimize the ill-effects of variability. This research, comprised of three essays, focuses on the design and operation of service delivery networks from a capacity management and service offerings perspective, and concentrates on the themes of information sharing and coordinated capacity management. Data collected from a large hospital network is used to analyze these issues.;The first essay addresses capacity planning at the strategic level by considering the impact of competition on a network's service capacity decisions. For-profit physician-owned specialized hospitals are forcing larger healthcare system owned hospitals to reevaluate their strategic options. Using spatial models this competition is analyzed to evaluate when and how should a network hospital specialize some of its facilities. Results indicate that networks with a spatial advantage can compete successfully by making informed capacity choices.;The second essay deals with how to best use information to improve performance of a service network when capacity and service offerings are fixed. Sharing information leads to more effective coordination of capacities; however, such improvements are contingent upon the variability of demand and inbuilt resource flexibilities. A hospital is simulated and the value of sharing information is determined. It is shown that sharing patient information among units leads to a more effective use of flexible capacity, which results in improved system-wide performance as indicated by reduced blocking and reduced average and standard deviation of length of stays. The conditions and capacity management approaches that offer the greatest potential to exploit information and are therefore directly relevant to the practicing manager are determined.;The third essay focuses on understanding the effectiveness of queueing methods for measuring the performance of a service delivery network. The same hospital system that was simulated in Essay 2 is modeled as an open queueing network using queueing approximations developed in the literature for multi-class customers with general arrival and service time distributions. Results indicate that ignoring important issues such as blocking effects in the queueing network model of the hospital leads to inaccurate measures of system performance.
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