Explicit Solutions for Variational Problems in the Quadrant
Queueing Systems: Theory and Applications
Heavy traffic approximations of large deviations of feedforward queueing networks
Queueing Systems: Theory and Applications
Queueing Systems: Theory and Applications
Heavy traffic resource pooling in parallel-server systems
Queueing Systems: Theory and Applications
Managing Business Process Flows
Managing Business Process Flows
Newsvendor Networks: Inventory Management and Capacity Investment with Discretionary Activities
Manufacturing & Service Operations Management
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Multimarket Facility Network Design with Offshoring Applications
Manufacturing & Service Operations Management
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We investigate how dynamic resource substitution in service systems impacts capacity requirements and responsiveness. Inspired by the contrasting network strategies of FedEx and United Parcel Service (UPS), we study when two service classes (e.g., express or regular) should be served by dedicated resources (e.g., air or ground) or by an integrated network (e.g., air also serves regular). Using call center terminology, the question is whether to operate two independent queues or one N-network. We present analytic expressions for the delay distributions and the value of network integration through partial resource pooling. These show how the value of network integration depends on service quality (speed and reliability of service) and demand characteristics (volume averages and covariance matrix). Our results suggest that network integration is of little value and operating dedicated networks is a fine strategy if the firm primarily serves express requests with high reliability and if the correlation with regular requests is not strongly negative. In contrast, network integration offers significant gains for firms serving primarily regular requests, almost independent of correlation. Our analysis provides the intuition behind these findings in terms of three main drivers of integration value: arrival pooling, the substitution effect, and the correlation effect.