The topic is interesting but this analysis/write up is very weak. I have a bunch of question but here are some:
1. Why only two data points? That doesn't really provide us with enough information to make a judgement about ubers surge pricing algorithm.
2. Why not look at an example where an increase in demand is not predictable (ie end of a concert) if this issue was mentioned as a weakness in the first example in the study.
3. Is it really the case that NYC cab drivers are sitting at home monitoring surge pricing at 11pm before deciding whether to get in their car and drive to Manhattan or wherever there is high demand for rides in the city to start giving rides? It seems most likely the case that drivers would assume there would be some surge and would already be on the road esp in a place like NYC on New Year's Eve. It's not clear to me that this data point really works. I can't imagine a driver is sitting with his family celebrating nye and waiting for surge pricing somewhere in NYC before hopping in his car to give a ride.