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    Influencing Greater Adoption of Eco-Driving Practices Using an Associative Graphical Display

    Source: Journal of Mechanical Design:;2020:;volume( 142 ):;issue: 003
    Author:
    Potvin-Bernal, J.
    ,
    Hansma, B.
    ,
    Donmez, B.
    ,
    Lockwood, P.
    ,
    Shu, L. H.
    DOI: 10.1115/1.4045968
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Substantial energy savings during the use phase of internal combustion and electric automobiles can be achieved by increasing eco-driving behavior, particularly reduced acceleration and braking. However, motivating widespread adoption of this behavior is challenging due to incompatibility with drivers’ values and priorities, and disassociation between drivers’ actions and observable consequences. Informational approaches, e.g., training programs and educational campaigns, are either difficult to scale up or largely ineffective, with drivers reluctant to make long-term changes. Alternatively, behavior can be influenced by redesigning the context within which the behavior occurs. Such an intervention must be effective across demographics and underlying behaviors to achieve ubiquity. The current study investigates the perceived effect on the driving style of a simple graphical dashboard display depicting an animated coffee cup. This display incorporates associative mental models and contextual relevance to increase the salience of inefficient vehicle movements and nudge drivers to adopt smoother driving. An online Amazon Mechanical Turk survey (92 participants) revealed a significant preference for the coffee-cup over a dial-gauge display when controlling for demographic variables. This result offers a preliminary indication that a behavioral nudge may be effective in influencing drivers to adopt eco-driving practices.
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      Influencing Greater Adoption of Eco-Driving Practices Using an Associative Graphical Display

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    contributor authorPotvin-Bernal, J.
    contributor authorHansma, B.
    contributor authorDonmez, B.
    contributor authorLockwood, P.
    contributor authorShu, L. H.
    date accessioned2022-02-04T14:34:54Z
    date available2022-02-04T14:34:54Z
    date copyright2020/01/30/
    date issued2020
    identifier issn1050-0472
    identifier othermd_142_3_031117.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4273956
    description abstractSubstantial energy savings during the use phase of internal combustion and electric automobiles can be achieved by increasing eco-driving behavior, particularly reduced acceleration and braking. However, motivating widespread adoption of this behavior is challenging due to incompatibility with drivers’ values and priorities, and disassociation between drivers’ actions and observable consequences. Informational approaches, e.g., training programs and educational campaigns, are either difficult to scale up or largely ineffective, with drivers reluctant to make long-term changes. Alternatively, behavior can be influenced by redesigning the context within which the behavior occurs. Such an intervention must be effective across demographics and underlying behaviors to achieve ubiquity. The current study investigates the perceived effect on the driving style of a simple graphical dashboard display depicting an animated coffee cup. This display incorporates associative mental models and contextual relevance to increase the salience of inefficient vehicle movements and nudge drivers to adopt smoother driving. An online Amazon Mechanical Turk survey (92 participants) revealed a significant preference for the coffee-cup over a dial-gauge display when controlling for demographic variables. This result offers a preliminary indication that a behavioral nudge may be effective in influencing drivers to adopt eco-driving practices.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleInfluencing Greater Adoption of Eco-Driving Practices Using an Associative Graphical Display
    typeJournal Paper
    journal volume142
    journal issue3
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4045968
    page31117
    treeJournal of Mechanical Design:;2020:;volume( 142 ):;issue: 003
    contenttypeFulltext
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