TY - JOUR
T1 - Motivation to interaction media
T2 - The impact of automation trust and self-determination theory on intention to use the new interaction technology in autonomous vehicles
AU - Xie, Yubin
AU - Zhou, Ronggang
AU - Chan, Alan Hoi Shou
AU - Jin, Mingyu
AU - Qu, Miao
N1 - Publisher Copyright:
Copyright © 2023 Xie, Zhou, Chan, Jin and Qu.
PY - 2023/2/8
Y1 - 2023/2/8
N2 - Introduction: This research investigated the effects of three psychological needs (competence, autonomy, and relatedness) of self-determination theory (SDT) and automation trust on the intention of users to employ new interaction technology brought by autonomous vehicles (AVs), especially interaction mode and virtual image. Method: This study focuses on the discussion from the perspective of psychological motivation theory applied to AV interaction technology. With the use of a structured questionnaire, participants completed self-report measures related to these two interaction technologies; a total of 155 drivers’ responses were analyzed. Result: The results indicated that users’ intentions were directly predicted by their perceived competence, autonomy, and relatedness of SDT and automation trust, which jointly explained at least 66% of the variance in behavioral intention. In addition to these results, the contribution of predictive components to behavioral intention is influenced by the type of interaction technology. Relatedness and competence significantly impacted the behavioral intention to use the interaction mode but not the virtual image. Discussion: These findings are essential in that they support the necessity of distinguishing between types of AV interaction technology when predicting users’ intentions to use.
AB - Introduction: This research investigated the effects of three psychological needs (competence, autonomy, and relatedness) of self-determination theory (SDT) and automation trust on the intention of users to employ new interaction technology brought by autonomous vehicles (AVs), especially interaction mode and virtual image. Method: This study focuses on the discussion from the perspective of psychological motivation theory applied to AV interaction technology. With the use of a structured questionnaire, participants completed self-report measures related to these two interaction technologies; a total of 155 drivers’ responses were analyzed. Result: The results indicated that users’ intentions were directly predicted by their perceived competence, autonomy, and relatedness of SDT and automation trust, which jointly explained at least 66% of the variance in behavioral intention. In addition to these results, the contribution of predictive components to behavioral intention is influenced by the type of interaction technology. Relatedness and competence significantly impacted the behavioral intention to use the interaction mode but not the virtual image. Discussion: These findings are essential in that they support the necessity of distinguishing between types of AV interaction technology when predicting users’ intentions to use.
KW - automation trust
KW - autonomous vehicles
KW - interaction technology
KW - motivation
KW - self-determination theory
UR - https://www.scopus.com/pages/publications/85148662749
U2 - 10.3389/fpsyg.2023.1078438
DO - 10.3389/fpsyg.2023.1078438
M3 - 文章
AN - SCOPUS:85148662749
SN - 1664-1078
VL - 14
JO - Frontiers in Psychology
JF - Frontiers in Psychology
M1 - 1078438
ER -