This is just a quick note to summarize and reflect on a recent reading I had – specifically Chapter 1 (“Desire for Movement”) of J.M. Thomson’s Modern Transport Economics.
In this chapter, Thomson walks through several economics-inspired theories on what drives demand for transportation generally. He notes that there are several core reasons why transport is necessary for both people and goods, including: increasingly specialized regional production of goods, establishment of political control, the proliferation of cultural opportunities, etc. Ultimately, he notes that transportation tends to attract facilities, as much as facilities attract transportation infrastructure. I thought this was a great foreshadowing of the concept of transit-oriented development, which I look forward to diving into deeper.
He notes that demand elasticity for transport varies widely – high for those with access to cars, inelastic for cargo shipping, dependent on factors like journey-time, service frequency, residential density, etc. He notes that growth in population is probably the main generator of person-journeys, and while the number of journeys per head hasn’t grown that much over the years, journey distances are increasingly significant as travel requires less time and money. Hence, there is virtually no limit to the potential demand for transport (curve BB below), unlike for typical consumption of goods (curve AA).
I thought the exercise to imagine “infinite mobility” where all user costs of transport were zero was an insightful one, and agree that this is already happening to some extent in the modern era for those with enough wealth to make use of private jets. While the author suggests that the consequences of increased travel volume may be dire for cities, that assumes that people are transported in the same ways they are today – that is, taking up the same amount of physical space or emitting the same amount of carbon with each trip. If we were to combine the imaginary zero-cost mobility with no negative externalities (imagine teleportation with no energy consumption for instance), the impact on cities in terms of things like roadway congestion may be mitigated.
Thomson looks at the problem of congestion at locations specifically, noting that there is an optimal number of users for any given location (marked as P below). This is exceeded when an location becomes so crowded such that the private benefit gained by each additional user is less than that which is lost by existing users – making the location just barely worth going to.
He suggests that limiting transportation facilities to the location may be a way of controlling the problem of overuse, but of course other methods exist to reduce the number of users (pricing, queuing, staggering, etc.). I can see this being a problem with major tourist destinations today but would argue that this is a premature concern for things like local parks or markets. In the latter context, suggesting there is an “optimum” that shouldn’t be exceeded is borderline exclusionary, and I would hope management of those facilities would attempt other ways of accommodating more visitors rather than reducing transport facilities.
The author also briefly describes the challenges with demand fluctuations, how varying peak requirements lead to inefficiencies in system design. While this is true for any system that experiences peaked usage, transport is an area where there may be some predictability, i.e. in weekday journeys to/from work, weekend trips, and seasonal fluctuations. I can see Caltrain being a local example of this, with surprisingly frequent service during rush hours but unusable frequencies at other times. I would argue that a system designed in this way is less valuable to everyone due to its schedule complexity, and the solution would be to provide more predictable service to locations less oriented towards peaked trip patterns (i.e. places with 24/7 activity).