Marketing

Usability

Value of time

Engineering

Transport engineering

Neuroscience

Service (business)

Environmental economics

Microeconomics

Travel time

Economics

Computer science

Time horizon

Business

Discrete choice

Willingness to pay

Psychology

Econometrics

Environmental science

Finance

Perception

Technology acceptance model

Human–computer interaction

Multinomial logistic regression

Machine learning

Transportation Research Part A Policy and Practice

Technological advances have recently led to the development of urban air mobility (UAM), an alternative transportation mode with several concepts including vehicles operated by on-demand fully-automated vertical take-off and landing aircraft (VTOL) for intra-city passenger transportation. However, despite a growing interest in UAM, understanding users’ perceptions to it remains limited. This research aims to identify and quantify the factors affecting the adoption and use of UAM, based on relevant tools from the literature, such as recurring factors in studies on aerial vehicle concepts, ground autonomous vehicles, but also acceptance models, such as the Technology Acceptance Model by Davis et al. (1989). A stated-preference survey was developed to assess the perception of users in terms of adoption time horizon, including options such as the first six years of the service’s implementation, “unsure”, and “never”. The obtained results were evaluated using exploratory factor analyses, and the specification and estimation of suitable discrete choice models, multinomial logit models (MNLs) and ordered logit models (OLMs), with adoption time horizon as dependent variable. Findings revealed the importance of safety and trust, affinity to automation, data concerns, social attitude, and socio-demographics for adoption. Factors, such as the value of time savings, the perception of automation costs, and service reliability, were also found to be highly influential. There was also an indication that skeptical respondents, i.e. answering “unsure”, had a behavior similar to late and non-adopters, i.e. adoption time horizon higher than six years or answering “never”. The summarized results were represented in an extended Technology Acceptance Model for urban air mobility, and provided insights for policymakers and industrial stakeholders.

Factors affecting the adoption and use of urban air mobility