What do people want? An analysis of citizens’ willingness to use Advanced Air Mobility in Italy

ABSTRACT

This paper investigates the drivers of citizens’ willingness to use Advanced Air Mobility (AAM) systems, focusing on individual and regional features. We analyse Italian data using a multinomial logit model. Our results show that individuals’ job positions, flying habits, and prior experience with drones positively influence such willingness. We also find that regional features matter, with respondents living in poorly-connected and less innovative regions being more willing than others to use AAM.

KEYWORDS:

• Advanced Air Mobility
• willingness to use
• individual and regional features
• Italy

JELCLASSIFICATION CODES:

• R41
• O33
• O18

Acknowledgments

We thank the ‘Drones and Advanced Aerial Mobility Observatory’ at Politecnico di Milano for data access and the valuable comments; we are also grateful to professors Marco Lovera and Massimiliano Guerini, who offered precious advice.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ Advanced Air Mobility extends the concept of Urban Air Mobility, including private, long-range, and thin-haul flights (Federal Aviation Administration, 2022, accessed October 10^th 2022: www.faa.gov/uas/advanced_operations/urban_air_mobility).

² The first commercial operations in European cities are expected in 2025 (EASA 2021).

³ For a punctual examination of multinomial logit models please refer to Greene (2011), 763).

⁴ Considering the hierarchical nature of the variables, we estimate a generalized structural equation model as a robustness check (Skrondal and Rabe-Hesketh 2003).

⁵ https://www.osservatori.net/it/ricerche/osservatori-attivi/droni-e-mobilita-aerea-avanzata, accessed October 10^th 2022.

⁶ We considered the following drone applications: substance dispensing; warehouse inventory; inspections and surveys; search and rescue; security and surveillance; entertainment; transport of goods; transport of biomedical products; transport of people; maintenance.

⁷ This variable is retrieved from the Italian Community Innovation Survey 2018.

⁸ We measure the level of utilization of public transportation as the natural logarithm of the number of people moving with public transportation over the total number of movers, and CO2 emissions as the natural logarithm of the number of equivalent tonnes emitted (in thousands).

⁹ For the sake of brevity, we did not include these control variables in the tables. Results are available from the authors upon request.

¹⁰ Source: https://lab24.ilsole24ore.com/qualita-della-vita-2019/classifiche-complete.php, accessed October 10^th 2022.