Urban Air Mobility: Predictive Modelling on the Behavior of Air-Service Bookings in Metropolitan Areas

The demand for a ride to work without running into the inefficiencies of traffic in a bustling, metropolitan area beckons for a system to tackle on-the ground traffic congestion, thus fueling the need for Urban Air Mobility (UAM). The instant gratification culture, notably its effect on Generation Z, has given way to the nature of impulsive decision making. The 2020 COVID-19 crisis, with its use of tap-to-gratify technology, highlights passengers preferring late booking. This last-minute airport reorganization crisis spearheaded our research goal to create a more user-personalized assessment of cancellation rates. Our research highlights that there will be a market in the 2030s for UAM, short-distance air transportation, and the world must prepare for the challenges that come with this new market. Through a two-part model, we obtained two randomized sets of profiles of user-specific and ridership attributes and their relationship with cancellations. Recommendations for future research include factoring this personalized aspect into cancellation projections to provide reasoned user discounts as well as a remedy for the scheduling chaos that stems from the airport organizational crisis.