The Enigma of Arrivals
Yesterday morning found me at a TRB panel, “Building the 21st Century Transportation System,” moderated by NYC’s own Janette Sadik-Khan. There were a number of interesting details offered — e.g., that J.S.K. had played rugby at Occidental College (she was abroad the year Barack Obama was there) a good skill set I think for navigating Gotham politics; or that Portlanders drive 4 fewer miles per day than other places in the U.S.; or that Seattle is high on the safety benefits of “advanced stop bars” — but one small anecdote that caught my attention in particular was offered by Fred Hansen, of Portland’s Tri-Met.
Talking about the city’s “Transit Tracker” program, which allows people to get real-time info on bus arrivals via their cell phones, Hansen mentioned a study that had been done in the U.K. of a similar program. What was noteworthy was that people using the service felt that the bus service itself had improved, that more buses were running, that they were running closer to schedule, even though none of this was empirically true.
I have a particular interest in the fluid nature of time, and the way travel, queuing, and even routing can play additive and subtractive games with this. Paco Underhill, for example, notes that people who wait in airport lines overestimate the time they waited by some 50 percent. I’ve also seen it noted that a train trip with a transfer feels longer to people than it really is, that people overestimate the time it will take to walk somewhere and underestimate the time it will take to drive somewhere. Of course, one of the masters of managing time is Disney, with its posted wait times (just posting the time makes it feel shorter for people) at queues, wait times which are then inflated — so the payoff at the end is even better: That wasn’t long at all!
The lesson here, I suppose, is that perception can be just as important as reality in crafting the “customer experience,” a lesson that applies as much to public transit as it does to the Magic Kingdom.
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This entry was posted on Wednesday, January 14th, 2009 at 5:00 pm and is filed under Etc., Traffic Psychology. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.
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January 14th, 2009 at 9:11 pm
Another key to Disney’s magic is that you won’t frequent enough to get used to the inflated queue times.
January 15th, 2009 at 8:52 am
8 principles of waiting psychology (Maister, 1985)
1. Waits with unoccupied time seem longer (passivity is boring)
2. Pre-process waits are felt to be longer than active process time (when does it start?)
3. Arousal and anxiety makes waits seem longer
4. Uncertainty makes waits seem longer (when will we reach ..?)
5. Unexplained waits seem longer (why waiting?)
6. Unfair waits seem longer than fair waits (why others may go?)
7. Valuable service waits seem shorter
8. Solo waits seem longer than waiting in own group
Maister, D. (1985). The psychology of waiting lines. In Czepiel, J.A., Solomon, M.R., Sureprenant, C.F. (eds): The service encounters: managing employees / customer interaction in service business. Lexington: Heath
January 16th, 2009 at 2:12 pm
Being a Portlander and heavy user of Tri-Met, I really like Transit Tracker. One of the unstated benefits is making the arrival vagaries of individual bus lines apparent. One line I ride frequently has the habit of getting stacked up with a number of buses coming within a short period of time followed by a significant wait for it to happen all over again.
On the other hand, we had quite a snowstorm (for us) here a month ago and Transit Tracker totally failed (as did Tri-Met in my opinion).
January 16th, 2009 at 2:37 pm
There is an urgent need to quantify these insights and begin building them into the computer models used to estimate ridership. Such models routinely put heavy penalties on waiting and transferring, based on real experience with situations where these things are really unpleasant. A generation of modelers has internalized these factors and can recite them with the same confidence that they have in real facts of mathematics.
This is a crucial issue in transit development, because these models drive Federal funding decisions, and often also influence decisions at state and local levels.