You raise some interesting issues, certainly worth considering when purchasing a residence or speculating land value. Your analysis reminds me of the young man who attempted to answer the question, “can a pedestrian traverse all seven bridges over the river Pregel, and return to their starting point without repeating a bridge crossing?” The young man was Euler, the father of graph theory. Urban planning (along with graphing theory, management science, and operations research) considers the points you raised, and indeed approaches problems regarding optimal network paths (max flow, accessibility, shortest path, and related costs) using some mathematical rigor. For example, one can model Accessibility as such:

Accessibility = ???Network Paths?* f(travel cost)

I think when contrasting San Carlos and Palo Alto, you might find it a worthwhile exercise to expand your definition of “Destination Points” to places of employment, schools, libraries, hospitals, emergency services, light commerce areas, and public transportation depots. Different cities have different goals and constraints in mind when planning urban or suburban development.

Urban planning combined with policy analysis is quite interesting. Consider a small town with local food shops and no supermarkets. Did you know price dispersion (standard deviation of price) increases among various foods between local shops and supermarkets? So while there may be close to no variance in the price of apples between a local shop and a supermarket, there is significant price dispersion between two exact bags of frozen food, and likewise between identical bags of rice, gallons of milk, and boxes of tea, to name a few commodities. When a community has five coffee shops, for instance, all equally accessible, expect price dispersion to approach zero. Alternatively, a community with five coffee shops that are not all equally accessible, ceteris paribus, will compete on price. When it become difficult to compete on price (totally elastic market), the cafés will compete on quality, and the consumer benefits. There is a good reason why Palo Alto has so many quality cafes, they price dispersion is low, geographically speaking (although price is high in absolute terms), and the cafés are forced to compete on quality to stay in business. One a side note – one reason Starbucks places stores so close together is reduce distribution costs, for instance (supply-side reasoning). While the average home buyer does not consider (nor should they) price dispersion and distribution costs when buying a house, I raise these points as they speak to a larger issue in the aggregate. Culture.

The first and foremost difference I notice when contrasting Palo Alto and San Carlos is culture. The accessibility factor, you notice in Palo Alto, I would argue, fosters an environment where price dispersion is minimized and businesses compete on quality. This invites a reinforcing effect where consumers willing to pay a ‘premium’ for quality or superior goods frequent these “quality” businesses. As such, real estate values increase (business rents increase), and business must continue competing on quality to win business (can’t lower costs because operating income is too low), and only new business that can offer higher levels of quality enter the market, et cetera. This phenomenon, I would argue, creates a filter that excludes numerous participants from engaging in marketing activities (i.e. buying stuff), yielding an environment requiring market participants with high discretionary income. The net result is a self-reinforcing social system perpetuating social exclusion.