Learning and Hierarchies in Service Systems

Motivated by diverse application areas such as healthcare, call centers, and crowdsourcing, we consider the design and operation of service systems that process tasks with types that are ex ante unknown, and employ servers with different skill sets. Our benchmark model involves two types of tasks, Easy and Hard, and servers that are either Junior or Senior in their abilities. The service provider determines a resource allocation policy, i.e., how to assign tasks to servers over time, with the goal of maximizing the system’s long-term throughput. Information about a task’s type can only be obtained while serving it. In particular, the more time a Junior server spends on a task without service completion, the higher her belief that the task is Hard and thus needs to be rerouted to a Senior server. This interplay between service time and task-type uncertainty implies that the system’s resource allocation policy and staffing levels implicitly determine how the provider prioritizes between learning and actuall...

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