Effects of Delays and Technical Disruptions on Satisfaction of Airtaxi Passenger

As Innovative Air Mobility (IAM) systems move towards reality, a need arises to focus not only on operational metrics but also on passenger-centric service quality. While existing frameworks evaluate vertiport performance, they lack the resolution to capture the diverse perceptions of individual passengers undergoing delays and disruptions. In this work, we present a proof of concept for a satisfaction model in the form of an algorithm that bridges this gap by combining operational simulation with heuristic behavioural sensitivity. The algorithm simulates vertiport scenarios under varying environmental and technical disruptions, delays, and cancellations resulting from multiple factors. An algorithm is proposed in this work that assesses the impact of these disruptions on passenger sentiment, generating emotional classifications of satisfied, frustrated, and furious. The algorithm delivers adaptable passenger satisfaction assessments to support infrastructure design and stakeholder alignment for future IAM systems.