Abstract
Technological advances are bringing autonomous vehicles to the ever-evolving transportation system. Anticipating adoption of these technologies by users is essential to vehicle manufacturers for making more precise production and marketing strategies. The research investigates regulatory focus and consumer innovativeness with consumers" adoption of autonomous vehicles (AVs) and to consumers" subsequent willingness to pay for AVs. An online questionnaire was fielded to confirm predictions, and regression analysis was conducted to verify the model"s validity. The results show that a promotion focus does not have a significantly positive effect on the automation level at which consumers will adopt AVs, but a prevention focus has a significantly positive effect on conditional AV adoption. Consumer innovativeness, consumers’ novelty-seeking have a significantly positive relationship with high and full AV adoption, and consumers’ independent decision-making has a significantly positive effect on full AV adoption. The higher the level of automation at which a consumer adopts AVs, the higher the willingness to pay for them. Finally, using a neural network and decision tree analyses, we show methods with which to describe three categories for potential adopters of AVs.
Recommended Citation
Lee, Eun-Ju; Zafarzon, Nordirov; and Zhang, Jing
(2018)
"Using Predictive Analytics to Profile Potential Adopters of Autonomous Vehicles,"
Asia Marketing Journal: Vol. 20
:
Iss.
2
, Article 3.
Available at: https://doi.org/10.15830/amj.2018.20.2.65
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This work is licensed under a Creative Commons Attribution 4.0 License.
