Citation

Keszey T. Transp. Res. C Emerg. Technol. 2020; 119: e102732.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.trc.2020.102732

PMID

unavailable

Abstract

This study aims to enrich autonomous vehicle (AV) adoption research and practice by being the first study to systematically review empirical studies on behavioural intention to use AVs, a key element in the adoption process. This review of the extant literature provides a synthesized overview of the current state of knowledge, develops a meta-framework to reconcile past research, identifies inconsistencies in prior results, and suggests areas for future research. To address these future directions, this study empirically extends the proposed meta-framework by testing impactful new variables. Structural equation modelling of survey data from 992 respondents in Hungary shows that drivers of behavioural intention to use AVs significantly differ among users with high and with low personal information technology innovativeness. The behavioural intention of innovative users is influenced by utilitarian and hedonic motivations, whereas laggards are driven by hedonic motivation, and a utilitarian motivation does not play a role. Innovative users' behavioural intention to use AVs is affected by specific technological fears (i.e., data privacy concerns), whereas those lagging are not influenced by specific, only by general concerns (i.e., overall technological anxiety). The study also shows how individual-level behavioural intention to use AVs interacts with expected societal-level outcomes (e.g., equal opportunity for mobility). The results shed light on the need for more research on the role of moderating variables, which are relatively unexplored in the extant literature yet can contribute to a better understanding of the differences in patterns between various groups of future users, offering important managerial implications.

Language: en

Keywords

Autonomous vehicle adoption; Behavioural intention to use; Data privacy concerns; Personal information technology innovativeness; Structural equation modelling; Systematic literature review