The chicago dataset includes the cost of a ridehailing trip. This data is not available nationwide, so I will not be able to use that data directly in the model.
Assuming that it is deemed necessary to include some sort of fare variable, I can come up with something like a dollars per mile scalar to use for other cities. This scalar will need to be TOD specific and will need to be scaled based on the CPI for different years. The scalar will likely need to be tweaked based on the city size.
Doing something like this will add a lot of assumptions into the model that I'm not sure are necessary to take on.
The chicago dataset includes the cost of a ridehailing trip. This data is not available nationwide, so I will not be able to use that data directly in the model.
Assuming that it is deemed necessary to include some sort of fare variable, I can come up with something like a dollars per mile scalar to use for other cities. This scalar will need to be TOD specific and will need to be scaled based on the CPI for different years. The scalar will likely need to be tweaked based on the city size.
Doing something like this will add a lot of assumptions into the model that I'm not sure are necessary to take on.