There is extensive theoretical literature that looks at factors that make people more or less likely to change their opinions as additional information is gathered. People whose opinions are less likely to change in response to information may have strong anchoring effects (commitments to initial opinions) or may support their initial opinion by selectively processing information to confirm their initial opinion (confirmation bias). Selectively processing information can also result in opinion polarization where opinions become more extreme as additional information is provided. While theoretical literature has been relatively abundant on this topic, there has been limited empirical evidence with transportation-related opinions as to how anchoring effects and confirmation bias may affect changing opinions and possible opinion polarization. The intent of the current paper is to provide some initial evidence of changing opinions and possible polarization as it relates to the potential adoption of autonomous vehicles, which will likely be a key element in future sustainable transportation strategies. Specifically, the paper studies how people’s initial autonomous-vehicle adoption likelihoods change after being asked a common set of questions that leads them through an assessment of factors involved in adoption. A series of discrete outcome models were estimated to determine the factors that influence the likelihood of people changing their initial opinions. Although the empirical models identified many variables associated with opinion change, it is argued that traditional transportation surveys may not be gathering the type of data needed to truly understand how people’s transportation-related decisions evolve in response to new information.


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    Title :

    The effect of information on changing opinions toward autonomous vehicle adoption: An exploratory analysis


    Contributors:


    Publication date :

    2020-06-02


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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