Taking advantage of human nature can be a cost saving

Fare enforcement and the perception of risk

Not long ago, at Brentwood Station, I had a wonderful interaction with a some Calgary Transit peace officers. They were checking fares at the door, and I passed them on my way to the pub. A few hours later, on my way back, they were still there checking tickets. Since this happened to be the third time I’d had my ticket checked that day, I piped up and said “boy you guys are active today, eh?”. The peace officer, presumably sensing my post-pub joviality, narrowed his eyes in jest and said, conspiratorially, “we’re everywhere”.

That interaction got me thinking about how we enforce fares on the C-Train network. In Calgary, the system is not closed off by gates or limited access points. Part of the whole appeal of an LRT as opposed to a subway (aside from it’s construction and operating costs) is that it interfaces more openly with the surrounding community; people are able to access platforms from many directions in a casual way. Because of this, fare enforcement on the C-Train is done primarily by peace officers who board the train and check a car’s fare between stations.

This got me thinking – with a system like this, there is a clear trade-off: if you hire more transit officers you increase the coverage of your fare enforcement, which means either you write more tickets or more people pay the fare. This is beneficial to keeping the whole system as affordable as possible.

Yet by hiring officers you also increase labour costs, which can indirectly increase fares, which in theory can also increase the number of people who can’t or won’t pay.

The trade-off isn’t even that straightforward. You can measure “percentage of cars inspected” or even “percentage of daily trips enforced” and try and find the most efficient way to do that, but if you are clever you can take advantage of something called perceived risk.

Humans as individuals are surprisingly bad at evaluating risk. One major way in which we misjudge risk comes from our misconception of chance, where we assume that if something happens frequently in a certain period of time, it is less likely to happen later on, or vice versa. In the case of fare enforcement, people might assume that if they have their ticket checked three times in a day, they will not be checked tomorrow (or if they see one in the morning they won’t see one in the evening).

This understanding of human nature can lead to interesting and possibly counter-intuitive results. For example, I would suggest we shouldn’t spread officer coverage evenly across the network, or even evenly across the number of trips made. In fact, in a world where we like order and predictability in our planning, the most advantageous strategy may be to act as randomly as possible. In terms of taking advantage of this, the bottom line for efficient fare enforcement is this: if the perceived risk is higher than the actual risk, then we are making efficient use of human nature.

There is also another important question we must ask: what is the goal of transit enforcement? There are a number of plausible answers to this question, and I’ll address two of them here with the understanding that if a trade-off exists with respect to a goal, there should be a sweet spot that is the best trade-off.

To Catch a Fare Dodger

Suppose we are planning how to deploy transit officers, and the mandate is for us to catch all the people who haven’t paid and fine them. There are two approaches to this: first, you need to expand your coverage of the transit system and check as many tickets as possible, and second, if you also wish to deter this behaviour, you must increase the perceived risk of getting caught for those who may attempt to ride free. The first is an optimization problem, where the difference between the income from fines and the cost of paying transit officers is maximized. The second approach requires deploying transit officers as randomly as possible. The more unpredictable and random they are, the worse riders are at detecting patterns of enforcement, and the more likely those looking for patterns (in order to avoid them) will fall victim to our misconception of chance.

There are, of course, practical issues to this: enforcement during the morning commute on a crowded train can annoy a large amount of paying people, and transit officers being paid to wander through empty trains in the off-peak is also inefficient. Transit officers have a number of purposes, the first of which is presumably rider safety, so this inefficiency in fare enforcement can be offset by an officer’s other purposes.

Get Everyone to Pay Up

Perhaps the goal is slightly different: maximize the number of people who pay fares. One way to do this is increase the fines to astronomical amounts, but that would certainly violate the “punishment should fit the crime” mentality that laws have taken on. The best way to go about this is to raise the perceived risk as high as possible: have officers leave their vehicles clearly visible to riders even if they are not around (something Calgary Transit does, whether on purpose or not is unclear) and remind users that transit enforcement is active today. In terms of what we’ve talked about, this involves maximizing the difference between perceived and actual risk, while also minimizing the amount of labour required to do so.

Safety First

In the end, my guess is transit enforcement on an open system like Calgary’s C-Train is more about safety than it is about minimizing fare dodging. That being said, if transit officers never appeared or were unable to issue fines, people would gradually understand that paying is unnecessary, and the perceived (and actual) risk would be quite low. There is a balance to be struck, and it is likely that the number of officers required to provide “safety” coverage in order to respond to incidents quickly is sufficient to keep the perceived risk above the actual one. Whether it’s optimal, well that’s another question.

This post was adapted from it’s original appearance on Klumpentown

Willem Klumpenhouwer

Willem is a PhD student in transportation planning and engineering at the University of Calgary, working on improving transit schedule design. In his spare time, Willem does programming projects and is a volunteer and improviser at the Loose Moose Theatre.

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