A Decision Analysis of Multi-Attributed Queueing Systems

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The research funded by this proposal extends research under a previous NSF grant. The research combines empirical case research with modeling methods to develop (1) a behavioral multi-attribute understanding of queues, (2) new performance measures for queueing applications that incorporate the behavioral attributes, and (3) develop and test a new class of management science queueing models. The working laboratories for the research include a retail branch of the U.S. Postal Service, a major retail bank and a national department store chain. The longer range outcome of this research include new directions for research on queueing theory and a prescriptive methodology for very significant productivity improvements in congested service systems that would increase customers' utility of the queueing experience at costs for less than required to add servers or technology to speed service.