The roles of initial trust and perceived risk in public’s acceptance of automated vehicles

By Tingru Zhang, D. Tao, Xingda Qu, Xiaoyan Zhang, R. Lin, Wei Zhang. Transportation Research Part C: Emerging Technologies, 2019

737 citations recorded by the source corpus.

Abstract The purpose of this study was to explore factors affecting users’ acceptance of automated vehicles (AVs, Level 3). A theoretical acceptance model was proposed by extending the Technology Acceptance Model (TAM) with new constructs: initial trust and two types of perceived risk (i.e., perceived safety risk [PSR] and perceived privacy risk [PPR]). It was hypothesized that initial trust was built upon perception factors (i.e., perceived usefulness [PU], perceived ease of use [PEOU], PSR, and PPR) and was a key determinant of AV acceptance. The validity of the model was confirmed with a structure equation modeling analysis based on data collected from 216 survey samples. Results revealed that initial trust was the most critical factor in promoting a positive attitude towards AVs, which, together with PU, determined users’ intention to use AVs. Initial trust could be enhanced by improving PU and reducing PSR associated with AVs. Theoretically, these findings suggest that initial trust offers another and probably more important pathway for other factors to impact consumers’ adoption of systems with uncertainty. Practically, the findings provide guidance for designing interventions aimed at improving public’s acceptance towards AVs.

Subfields: Information Systems and Management, Social Psychology, Transportation

View Paper: https://www.semanticscholar.org/paper/7a47b9b32c74b67da880a99b5cb49eca2ca7ed40

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems and Management

1. B. van Arem
2. Riender Happee
3. Miltos Kyriakidis
4. Sina Nordhoff

In Social Psychology

1. Miltos Kyriakidis
2. Tyron Louw
3. B. van Arem
4. Sina Nordhoff
5. Riender Happee
6. Natasha Merat
7. J. D. de Winter

In Transportation

1. Xueqin Wang
2. Guanqiu Qi
3. Lanhui Cai
4. B. van Arem
5. Kum Fai Yuen

Citations in the corpus

• A multi-level model on automated vehicle acceptance (MAVA): a review-based study (2019, background): “…between subjective norm (equivalent to social influence) and the perceived benefits (equivalent to performance expectancy, see Xu et al., 2018; Zhang et al., 2019), and ease of use of automated driving technology (equivalent to effort expectancy), and a positive relationship between…”
• Factors influencing autonomous vehicle adoption: an application of the technology acceptance model and innovation diffusion theory (2020, background): “Extensive research has been conducted to investigate the e ff ects of PEOU and PU on behavioural intention across multiple fi elds (Wu et al. 2019; Zhang et al. 2019).”
• 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): “Main effects of the UTAUT2 constructs on behavioural intention In order to predict the acceptance of conditional automation, the TAM and TPB were applied (Buckley et al., 2018; Kaye et al., 2019; Xu et al., 2018; Zhang et al., 2019).”