Informational cues and willingness-to-pay for driverless cars

This study examines the influence of social factors on willingness-to-pay (WTP) for autonomous vehicles (AVs), framing social influence through informational cues received from mass media, social media, market penetration, and word-of-mouth (WOM) from social contacts. The impact of WOM is moderated based on the trust level associated with social contacts. We proposed a behavioural framework that links informational cues to AV consideration, and models AV selection as a function of that consideration. Model parameters are estimated using data from a representative sample of 862 Sydney residents, and a latent class approach is used to capture taste heterogeneity. Thanks to the structure of the proposed framework, WTP for automation is estimated conditional on the status of informational cues. The framework offers novel insights into the dynamics of innovation diffusion and the timing of policy interventions. When informational cues are weak and market uptake remains limited, external support may be particularly relevant during the early stages of diffusion. As market uptake increases and the technology generates stronger confirmatory signals through trusted networks, the need for policy support may gradually diminish as diffusion becomes increasingly supported by market experience and social reinforcement.

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Publication Details

Journal
Travel Behaviour and Society
Published
2026-10-28
DOI
https://doi.org/10.1016/j.tbs.2026.101431
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
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article

Informational cues and willingness-to-pay for driverless cars

Milad Ghasri, Akshay Vij
Travel Behaviour and Society
Transportation and Mobility Innovations
article

Informational cues and willingness-to-pay for driverless cars

Milad Ghasri, Akshay Vij
article en

Abstract

This study examines the influence of social factors on willingness-to-pay (WTP) for autonomous vehicles (AVs), framing social influence through informational cues received from mass media, social media, market penetration, and word-of-mouth (WOM) from social contacts. The impact of WOM is moderated based on the trust level associated with social contacts. We proposed a behavioural framework that links informational cues to AV consideration, and models AV selection as a function of that consideration. Model parameters are estimated using data from a representative sample of 862 Sydney residents, and a latent class approach is used to capture taste heterogeneity. Thanks to the structure of the proposed framework, WTP for automation is estimated conditional on the status of informational cues. The framework offers novel insights into the dynamics of innovation diffusion and the timing of policy interventions. When informational cues are weak and market uptake remains limited, external support may be particularly relevant during the early stages of diffusion. As market uptake increases and the technology generates stronger confirmatory signals through trusted networks, the need for policy support may gradually diminish as diffusion becomes increasingly supported by market experience and social reinforcement.

Travel Behaviour and SocietyVol. 46
University of Canberra (AU), UNSW Sydney (AU), UNSW Canberra (AU), Adelaide University (AU), The University of Adelaide (AU)
Sustainable cities and communities
Openalex Percentile: Top 23%
Transportation and Mobility Innovations
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Informational cues and willingness-to-pay for driverless cars — Milad Ghasri, Akshay Vij · Travel Behaviour and Society (2026) | TGRS Research Map | TGRS