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We study a multistage service process that adapts to system occupancy level. Using operational data from more than 140,000 patient visits to a hospital emergency department, we show that the system-level performance of the emergency department is an aggregation of several simultaneous server-level workload response mechanisms. We identify early task initiation as a between-stage adaptive response mechanism that occurs when an upstream stage initiates tasks that are normally handled by a downstream stage. We show that having some diagnostic tests ordered during the triage process reduces treatment time by 20 minutes, on average. However, ordering too many tests at triage can lead to an increase in the total number of tests performed on the patient. We also demonstrate the presence of other response mechanisms such as queuing delays for tasks such as medication delivery, and rushing as nurses spend less time with their patients when the queue length is high. This paper was accepted by Serguei Netessine, operations management.

We study queue abandonment from a hospital emergency department. We show that abandonment is not only in uenced by wait time, but also by the queue length and the observable queue ows during the waiting exposure. For example, observing an additional person in the queue or an additional arrival to the queue leads to an increase in abandonment probability equivalent to a fteen minute or nine minute increase in wait time respectively. We also show that patients are sensitive to being "jumped" in the line and that patients respond di erently to people more sick and less sick moving through the system. This customer response to visual queue elements is not currently accounted for in most queuing models. Additionally, to the extent the visual queue information is misleading or does not lead to the desired behavior, managers have an opportunity to intervene by altering what information is available to waiting customers.

The rise in online and multichannel retailing has pushed retailers to give increased attention to their order fulfillment operations. We study "chaotic storage" fulfillment systems in which dissimilar items are stored together in a single location. This necessitates a searching task as part of the picking process which has not been previously studied. We show that pick times increase by as much as 16% as the searching task becomes more difficult. However, the deleterious effect of searching decreases with pick worker experience.Using simulation, we show that pick times can be improved by incorporating distance, bin density, and picker experience into pick assignments and pick routing. Through properly combining the details of the task and the workers, order fulfillment productivity can be increased by approximately 5%.

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