Acceptance of Automated Road Transport Systems (ARTS): An adaptation of the UTAUT model

By R. Madigan, Tyron Louw, M. Dziennus, Tatiana Graindorge, E. Ortega, Matthieu Graindorge, Natasha Merat. 2016

304 citations recorded by the source corpus.

As research into innovative forms of automated transportation systems gains momentum, it is important that we develop an understanding of the factors that will impact the adoption of these systems. In an effort to address this issue, the European project CityMobil2 is collecting data around large-scale demonstrations of Automated Road Transport Systems (ARTS) in a number of cities across Europe. For these systems to be successful, user acceptance is vital. The current study used the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate the factors which might influence acceptance of ARTS vehicles, which were operational in two locations in Europe. The results indicate that the UTAUT constructs of performance expectancy, effort expectancy and social influence were all useful predictors of behavioural intentions to use ARTS, with performance expectancy having the strongest impact. However, it would appear that other factors are also needed in order for the model to strongly predict behavioural intentions in an automated transport context. Based on these findings, a number of implications for developers and ideas for future research are suggested.

Subfields: Automotive Engineering, Information Systems and Management, Transportation

View Paper: https://www.semanticscholar.org/paper/ba3f75b639d227a6869a4086ea2c6a90c806f9d7

How researchers see this paper

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In Automotive Engineering

1. Riender Happee
2. Sina Nordhoff

In Information Systems and Management

1. Michael A. Nees
2. Riender Happee
3. Sina Nordhoff

Citations in the corpus

• Acceptance of Self-driving Cars (2016, background): “…(e) perceived usefulness of automation; (f) perceived ease of use of automation; (g) experience with automation; and (h) intention to use automation (see Davis, Bagozzi, & Warshaw, 1989; Ghazizadeh et al., 2012; Madigan et al., 2016; Peng, Ghazizadeh, Lee, & Boyle, 2012; Venkatesh et al., 2003).”
• Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries (2020, methodology): “UTAUT2 has been tailored to the consumer context and explained a larger portion of the variance in behavioural intention to use automated vehicles (Madigan et al., 2017) than the TAM, TPB and UTAUT (Buckley et al., 2018; Madigan et al., 2016; Xu et al., 2018).”