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    Erratum: “Sensitivity of Vehicle Market Share Predictions to Discrete Choice Model Specificationâ€‌ [Journal of Mechanical Design, 136(12), 121402]

    Source: Journal of Mechanical Design:;2016:;volume( 138 ):;issue: 005::page 57001
    DOI: 10.1115/1.4032974
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Finally, we observe that some of the models with the best predictive accuracy have coefficients with unexpected signs—likely biased due to correlation with unobserved attributes. Despite good prediction accuracy in existing markets, where attribute correlations are similar from year to year, these models may misguide design efforts if the designer makes changes that do not follow correlations in the marketplace. For example, the sign of the coefficient for the gallons per mile (gpm) attribute of the best predictive logit model is negative, suggesting that consumers prefer lower fuel economy, all other attributes being equal. In fact, consumers may purchase vehicles with lower fuel economy because of other features of those vehicles unobserved by the modeler (e.g., size, performance, or styling attributes not captured in the model). The model predicts well if the new market retains such correlations, but a designer who lowers fuel economy alone is not likely to obtain the outcome predicted by the model. Thus, accuracy of predictions in existing markets is not a sufficient condition for use in design.
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      Erratum: “Sensitivity of Vehicle Market Share Predictions to Discrete Choice Model Specificationâ€‌ [Journal of Mechanical Design, 136(12), 121402]

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    date accessioned2017-05-09T01:30:59Z
    date available2017-05-09T01:30:59Z
    date issued2016
    identifier issn1050-0472
    identifier othermd_138_05_057001.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/161787
    description abstractFinally, we observe that some of the models with the best predictive accuracy have coefficients with unexpected signs—likely biased due to correlation with unobserved attributes. Despite good prediction accuracy in existing markets, where attribute correlations are similar from year to year, these models may misguide design efforts if the designer makes changes that do not follow correlations in the marketplace. For example, the sign of the coefficient for the gallons per mile (gpm) attribute of the best predictive logit model is negative, suggesting that consumers prefer lower fuel economy, all other attributes being equal. In fact, consumers may purchase vehicles with lower fuel economy because of other features of those vehicles unobserved by the modeler (e.g., size, performance, or styling attributes not captured in the model). The model predicts well if the new market retains such correlations, but a designer who lowers fuel economy alone is not likely to obtain the outcome predicted by the model. Thus, accuracy of predictions in existing markets is not a sufficient condition for use in design.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleErratum: “Sensitivity of Vehicle Market Share Predictions to Discrete Choice Model Specificationâ€‌ [Journal of Mechanical Design, 136(12), 121402]
    typeJournal Paper
    journal volume138
    journal issue5
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4032974
    journal fristpage57001
    journal lastpage57001
    identifier eissn1528-9001
    treeJournal of Mechanical Design:;2016:;volume( 138 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian