Applying systems thinking and the cognitive cycle to identify approaches to improve wait times in systems with low customer abandonment

System managers can benefit from applying systems thinking and the cognitive cycle to queueing systems where customers have involuntary, infinite patience, and the number of servers is state-dependent. In these queueing systems, customers do not or cannot renege, and further, the system may not lend itself to analysis under Markovian assumptions. Under these circumstances, managers tasked with improving system performance need methods of identifying improvement strategies that queueing theory may not make readily apparent. We develop a generic system dynamics (SD) queueing model, which reveals variables that may be significant contributors to queueing performance but may not be explicitly considered in traditional queueing models. The SD model identifies three classes of variables associated with the cognitive cycle, i.e., system customers and servers perform functions related to detection, interpretation, and action. Via simulation, we apply the generic model to passport inspection stations at John F. Kennedy International Airport then develop a matrix, which demonstrates options for addressing system performance beyond increasing the number of servers.