Why would people in one city prefer to ride bicycles more than their neighbors in the town over? Why is it that Uber is viable in some cities but not others? Can we explain the choices we make when preferring one means of transportation over another in one unified theory? Well, it turns out we can. This article starts with a simple request for the TV remote and ends with an analysis of the MAAS’s chances of replacing private ownership of cars.
“Where there’s a will there’s a way.” she text me. But even when it comes to sex, as an urban economist I don’t respond well to binary options. “The longer the way, the lesser the will” I replied. Yes, I am that kind of geek.
I would like to talk about some market behaviors in the city that we usually disregard – sex and love. On these “markets” we are simultaneously both the service providers and the customers, no money is involved (yes… by all means, feel free to make your jokes here) and yet Supply and Demand of those are playing a role in the way our cities function.
What determines a city’s size and the area of its economic impact? What is the connection between ‘Hassle-distance’ and the theoretical gravity model I’ve demonstrated earlier? I want to elaborate more on the Suppression Zone of the city and I’ll tie it all together here.
Let’s continue with urban mathematics shall we? If you are fascinated with cities as I am it’s a path worth taking. This is the ‘WHY’. The deeper understanding of why the city behaves the way it does.
Let’s see what the model I have developed is actually teaching us. As a reminder, the model progresses up to “Nash equilibrium” for one product, with equal distribution of suppliers and customers. The model illustrates how a market failure was created, similarly to the model of the ice-cream vendors. In this article, I would like to show examples of the phenomena that the model produces.
OK, here it is, the most complicated part of the book. I’ll try to explain this urban mathematics thing as clearly as I can, but I guess I’ll need to re-write it few times. This article would probably be tricky to follow but fortunately, there are pictures.
So, deep breath…
My goal here is to find the mathematical equivalent of (don’t panic) Nash equilibrium on a large scale with many players. Just as in the example of the ice cream vendors, I am looking for the easiest way to explain why businesses are clustered in the city, using the simplest possible algorithm.
Hmm, sounds reasonable so far. Are you with me? let’s go.