Using a Cognitive Variable Framework Derived from Systems Dynamics to Develop Options for Addressing the Performance of Human Queues Open Access
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The human brain has been modeled using the cognitive cycle, a continuous loop of detection, interpretation, and action which guides decision-making and task performance. In human-driven queues, these elements can affect queuing performance. However, increasing the number of servers is the conventional strategy for improving the performance of queues. This practice can be expensive as system managers may be challenged with either absorbing the cost of additional servers or identifying alternatives that queueing theory does not explicitly highlight. This research demonstrates how system managers can combine systems thinking with the cognitive cycle in the context of queues. Specifically, this research describes a method of identifying improvement strategies in queueing systems where customers have involuntary, infinite patience, and the number of servers is state-dependent. This research develops a generic system dynamics (SD) queueing model which identifies three classes of variables associated with the cognitive cycle. These variables may be significant contributors to queueing performance. Via simulation, this research demonstrates the application of the generic model to passport inspection stations at John F. Kennedy International Airport then, using cognitive variables as a framework, systematically develops a matrix of improvement strategies.