Assessing the characteristics and outcomes of perceived usefulness and ease of use for autonomous vehicle adoption

Wei Peng · Kathryn Robinson-Tay

19 citations0/0 files storedTransportation Research Part F Traffic Psychology and Behaviour

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Technology Adoption and User Behaviour Human-Automation Interaction and Safety Transportation and Mobility Innovations

Abstract

• The perceived usefulness of autonomous vehicles is explained by both functional and non-functional characteristics. • The perceived ease of use of autonomous vehicles is measured by functionality and financial accessibility. • Knowledge was negatively associated with perceived usefulness but positively with ease of use of autonomous vehicles. • Trust in autonomous vehicles was positively related to perceived usefulness but negatively related to ease of use. • Perceived usefulness was linked to adoption intention and support for research and policy. Autonomous vehicles have the potential to improve public safety and change the transportation landscape, but their public acceptance is not sufficiently understood. Grounded in the Technology Acceptance Model (TAM), this research proposed and validated measurement models to identify the primary factors of perceived usefulness (PU) and perceived ease of use (EU) associated with autonomous vehicles. Also, we proposed a path model to examine the relationships between PU, EU, individual differences, and acceptance. This cross-sectional study sampled 323 U.S. adults from an online panel. The result showed that PU was explained by the safety, transportation functions, societal impact, epistemic value, and emotional value of autonomous vehicles. EU was explained by complexity, observability, and desire for trial. In the path model, knowledge showed a negative relationship with PU but a positive one with EU. PU was related to trust, adoption intention, and support for research and policy. EU was related to PU, car authority identity, and trust. We discussed the theoretical implications of our findings and practical applications related to this emerging technology.

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References

1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error 1999Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 2012Principles and Practice of Structural Equation Modeling 2007Confirmatory factor analysis for applied research 1998Not So Different After All: A Cross-Discipline View Of Trust 2009The Technology Acceptance Model: Its past and its future in health care 2014Technology acceptance model: a literature review from 1986 to 2013

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