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https://hdl.handle.net/10356/173289
Title: | Public acceptance of autonomous vehicles: examining the joint influence of perceived vehicle performance and intelligent in-vehicle interaction quality | Authors: | Koh, Le Yi Yuen, Kum Fai |
Keywords: | Engineering::Civil engineering | Issue Date: | 2023 | Source: | Koh, L. Y. & Yuen, K. F. (2023). Public acceptance of autonomous vehicles: examining the joint influence of perceived vehicle performance and intelligent in-vehicle interaction quality. Transportation Research Part A: Policy and Practice, 178, 103864-. https://dx.doi.org/10.1016/j.tra.2023.103864 | Journal: | Transportation Research Part A: Policy and Practice | Abstract: | Many nations' transportation strategies have highlighted the potential of autonomous vehicles and have made plans to slowly phase them into societies over the next decade. Consequently, public acceptance of autonomous vehicles is crucial, and this study will be applying the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and Computers as Social Actors as the theoretical backbone. Five hundred valid survey responses from people residing in Singapore were collected and structural equation modeling was utilized to confirm the theoretical model. From the results, all of the identified constructs from UTAUT2 and Computer as Social Actors are significant. The performance expectancy of autonomous vehicles and interaction quality of the intelligent in-vehicle interaction technology also mediate public acceptance of autonomous vehicles. Moreover, among the constructs, interaction quality, social influence, and performance expectancy have the greatest total effect on the acceptance of autonomous vehicles. Accordingly, regular feedback sessions must be conducted to ensure consumer-centric improvements in interaction quality and performance expectancy of autonomous vehicles. Furthermore, test drives and collaborative educational campaigns can be organized to generate positive word of mouth about the vehicles among the public. | URI: | https://hdl.handle.net/10356/173289 | ISSN: | 0965-8564 | DOI: | 10.1016/j.tra.2023.103864 | Schools: | School of Civil and Environmental Engineering | Rights: | © 2023 Elsevier Ltd. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | CEE Journal Articles |
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