Improving Performance of Semi-automated Queues Through Enhancement of Existing Self-service Technologies
Open Access DepositedCustoms and Border Protection (CBP) uses three self-service technologies to reduce wait time at airport customs checkpoints when returning to the United States (US). This research develops a linear regression model to measure the impact to queueing time for each self-service technology in use. The linear regression model built within this praxis shows the expected queueing time when supplied with an airport, passenger load, staffing posture, and the automation technologies in use at the specified airport. While the model as presented applies specifically to US CBP checkpoints at international airports, a model like this is applicable to a wide range of industries where self-service queues can be implemented to speed up the queueing process. Airport operations managers will use this tool to understand the impact of adding or removing a technology from their airport ecosystem. At CBP checkpoints, Automated Passport Control showed an immediate reduction in wait time for 66% of airports and a transient improvement for 90% of airports with an average decrease in wait time of 30%. Mobile Passport Control did not show an immediate reduction in wait time when installed but showed a transient improvement at 61% of airports. Global Entry showed neither immediate nor transient improvement in airport wait times. Congressional mandate requires removal of Automated Passport Control from international airports over security concerns. Operations managers should be concerned with this mandate because the results from this research show that wait times will increase with the removal of this automated self-service technology.
- All rights reserved
Notice to Authors
If you are the author of this work and you have any questions about the information on this page, please use the Contact form to get in touch with us.