The conclusion here has an unfounded moral lesson: "The model suggests why competitors always seem to locate so close to each other and compete on real estate.

The conclusion here has an unfounded moral lesson: "The model suggests why competitors always seem to locate so close to each other and compete on real estate. Think about big burger chains, supermarkets, and video stores. You will almost always see them clustered even though it would be nicer if they spread out." How do you know it would be nicer if they spread out? You'd waste money (and carbon emissions) shipping resources to remote businesses that aren't profitable, or at least not as profitable as they could be if they were closer and easier to ship to. As a reductio ad absurdum, you can't build and maintain a gas station in Antarctica just so that it would "nicer" if someone happened to be there on vacation with their snowmobile. The reason there's no gas stations in Antarctica is the same reason there's so few in Wyoming. It's also the reason they're all clustered around high-traffic areas immediately outside of major cities. If you can't calculate from empirically established methods a "socially optimal equilibrium" that doesn't directly imply that we should be building gas stations in Antarctica, you don't know that the current distribution is suboptimal. More generally, there's a lesson for policymakers here: you shouldn't endeavor to destroy established equilibria that you don't understand. Otherwise, kudos to the author for a pretty neat example and visualization. People who do stuff like this are awesome.