Queue abandonment is predicted by wait duration and its predictability, by how visible the expected wait is to the customer, and by perceived rather than objective waiting time 12. Queuing theory separates two abandonment behaviours: balking, where the customer never joins the queue, and reneging, where the customer leaves a queue after joining it and before receiving service 1.
Metrics associated with reneging
- Long or unpredictable wait times are a frequent signal behind high reneging rates 1.
- Lack of updates during the wait is another indicator, and real-time updates, progress indicators and clear service expectations help customers stay committed 1.
- Poor alignment between demand and staffing shows up in high reneging rates as well 1.
Metrics associated with balking
- Poor visibility into expected wait times is a common driver of high balking rates 1.
- Service capacity that does not match demand also raises balking 1.
- A gap between perceived effort and service value contributes to balking 1.
- Crowded spaces, slow movement and unclear flow trigger balking, particularly in high-volume settings 1.
Why perceived wait matters
Effective queue management requires evaluating the service system beyond objective waiting times 2. Customers' emotional responses to waiting are negatively influenced by their perceived wait times, which affects service appraisal and can lead to abandonment of the service 2. Balking is operationally hard to track because the customer never enters the system, so measurement of balking has to rely on entry-point observation rather than queue records 1.