Psychology of Queueing & Disneyland

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I went on vacation last week to Disneyland.  We had a lot of fun.  It was also a time to learn how organizations like Disneyland deal with queueing challenges, especially with systems under high stress and load.  In this post, I want to cover the Psychology of Queueing and how Disneyland satisfies several of the positive properties.

There are a few key behavioral responses or reactions to queues, or waiting. Below are the propositions:

1. Unoccupied time feels longer than occupied time.
2. Process-waits feel longer than in-process waits.
3. Anxiety makes waits seem longer.
4. Uncertain waits seem longer than known, finite waits.
5. Unfair waits are longer than equitable waits.
6. The more valuable the service, the longer the customer is willing to wait.
7. Solo waits feel longer than group waits.

In almost every ride at Disneyland, they provide the following metric at the beginning of the ride:

The message above signals to the customer approximately how long she or he is expected to wait.  This strategy satisfies property 4 of the Psychology of Queueing — it is no longer an uncertain wait, but a finite (albeit seemingly long) wait.  This helps to manage the customer’s expectations or helps the customer decide whether he or she is willing to wait or willing to move on to a different ride.  This visual display is a simple, yet powerful move that helps the customer.

Now, to arrive at the average wait time above, requires some understanding of the physics of queueing.  The physics of queueing that helps us approximate the average wait time is below:

1. λ = Arrival Rate, or more specific, the time between arrivals.  For most queues, we can assume that the arrival distribution can be approximated by a Poisson distribution; which means that the time between arrivals are not deterministic, but random.
2. μ = Service Rate, or more specific the time for a arrival to be serviced.

So, we get the following to conclude the average wait time:

T_w = (λ / μ(μ – λ))

The calculation is simple, yet powerful.  Couple the physics of queueing with a positive approach in the psychology of queueing, then you’ll better manage the expectations of your customers, better forecast the load and requirements of a system, and better predict requirements on labor or resources.

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