## 1 Introduction
In addition, non-revenue-generating activities must be considered when planning to meet dynamic demands; for example, movements due to scheduling conflicts are less likely in conventional scheduled air transportation, but more likely in ODAM transportation [9]. Pilot availability, certification risk, vehicle mass, and trip cost must all be carefully balanced as well [19]. ODAM research in the Munich metropolitan area was performed using simulations as Munich is Germany's most congested metropolitan area. However, the proposed vertiport locations in the study did not consider size restrictions or capacity restraints (e.g., vehicle take-offs and landings per hour) in their simulations. Moreover, future research should examine how external shocks such as global pandemics impact air mobility networks [20]. Therefore, future air mobility models should consider capacity constraints to identify and quantify delays, events, availability, etc. The current system will need to be transformed, making the development of innovative network management methods and tools a research priority [1]. A U.S. study found that the costs related directly or indirectly to delays were approximately USD 40,700 million [21]. Modern life relies on a variety of transportation options. Although the mobility and vehicular options and capabilities are enormous in comparison with even a few decades ago, the challenges have also grown, particularly in terms of the population density in major cities around the world. One of the reasons for this increase in population density is the lack of cost- and time-efficient transportation options for daily commuting. Different mobility options have various advantages and disadvantages. For their quantification, indicators must be established, and their parameters measured, such as transportation lead times, battery charging processes and lead times, required financial investments and operational costs, origin and destination flexibility, environmental impact, persons per trip, etc. Considering all these factors along with many others, the development of holistic models is sorely needed for theoretical as well as for practical applications to design, manage, and understand real-world mobility needs while considering a sustainable set of indicators. Therefore, this study focused on developing an air mobility management model, first, in terms of generic air mobility and, second, for ODAM. Afterwards, the conceptual model was partially applied to a system dynamics simulation for electric aviation aircraft units within a network of vertiports with on-demand mobility requests by users. The goal was to identify bottlenecks, define measures, and, as a result, improve the potential of a networked system of aircraft to match the demand with its capabilities, its available stations and their capacities, and its maintenance performance. Moreover, the study applied a generic holistic concept for electric aviation in a regional area containing fifteen locations, one of which was a major metropolitan area where the central parking, charging, and maintenance hub was located, while the others presented small vertiports with parking and charging capabilities. The goal of the proposed approach was for the development of a holistic management model for air mobility, its application for ODAM in an electric aviation network, and its capability to manage dynamic capacity constraints by identifying, quantifying, and reacting to bottlenecks and delays at the different vertiports. The simulation model had to manage multiple locations and their amenities (e.g., parking availability, charging bays, etc.) while handling typical transport issues such as customer requests for transport that could not be accommodated as well as insufficient landing locations for incoming aircraft. The main contribution of this research was to identify service issues that could affect customer satisfaction and operational costs.