A multi-analytical approach to studying customers motivations to use innovative totally autonomous vehicles

Article

McLeay, F., Olya, H., Liu, H., Jayawardhena, C. and Dennis, C. 2022. A multi-analytical approach to studying customers motivations to use innovative totally autonomous vehicles. Technological Forecasting and Social Change. 174. https://doi.org/10.1016/j.techfore.2021.121252
TypeArticle
TitleA multi-analytical approach to studying customers motivations to use innovative totally autonomous vehicles
AuthorsMcLeay, F., Olya, H., Liu, H., Jayawardhena, C. and Dennis, C.
Abstract

Increasing technological innovation means level 5 fully autonomous vehicle pods (AVPs) that do not require a human driver are approaching reality. However, the adoption of AVPs continues to lag behind predictions. In this paper, we draw on Mowen's (2000) 3M model taking a multi-analytical approach utilising PLS-SEM and fuzzy set qualitative comparative analysis, to investigate how personality trait sets motivate consumers to adopt AVPs. Based on a survey of 551 US respondents, we identify four necessary traits and five combinations of traits that predict adoption. We contribute to consumer psychology theory by advancing the understanding of the motivational mechanisms of consumers’ adoption of autonomous vehicles that are triggered and operationalised by personality traits and conceptualising innovativeness as a complex multidimensional construct. From a managerial perspective, our findings highlight the significance of incorporating elements that are congruent with target customers’ personality traits, when designing, manufacturing and commercializing innovative products.

PublisherElsevier
JournalTechnological Forecasting and Social Change
ISSN0040-1625
Publication dates
Online06 Oct 2021
Print31 Jan 2022
Publication process dates
Deposited12 Oct 2021
Accepted25 Sep 2021
Output statusPublished
Accepted author manuscript
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Copyright Statement

© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

Digital Object Identifier (DOI)https://doi.org/10.1016/j.techfore.2021.121252
LanguageEnglish
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