Inferring balking behavior from transactional data

Balking is the act of not joining a queue because the prospective arriving customer judges the queue to be too long. We analyze queues in the presence of balking, using only the service start and stop data utilized in Larson's Queue Inference Engine. Using an extension of Larson's congestion probability calculation to include balking we present new maximum likelihood, nonparametric, and Bayesian methods for inferring the arrival rate and balking functions. The methodology is applicable to businesses that wish to estimate lost sales because of balking arising from queueing-type congestion. The techniques are applied to a small transactional data set for illustrative purposes.