The model won't tell you how likely these scenarios are, but one advantage of this class of model over black-box ML function-fitting is that you can do scenario planning. You can do models runs like "what happens if the price of oil shoots way up?" or "what happens if 50% of the cars are taxis?" (e.g. Uber-driven future) or "what happens if transit all of a sudden gains a huge perceived cost?" (e.g. respiratory-virus pandemic) in the third and fourth stages of the model. In the early stages of the model you can look at stuff like "what happens if firms abandon city centers?" or "what happens if 50% of white-collar work is done from home?" etc.