Principal component analysis (PCA) is applied to characterize the underlying structures of the acceleration gain surface (AGS) of 15 midsize sedans and to link them with customer preference. The AGS can be characterized by two principal components (PCs), the first PC representing the overall slope of AGS and the second PC representing the linearity of AGS. Findings indicate that customer preference is associated with the AGS linearity. PCA thus proves itself a valuable method for translating the voice of the customer as well as for setting effective and efficient vehicle acceleration gain targets.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Principal component analysis of vehicle acceleration gain and translation of voice of the customer


    Beteiligte:
    Lee, Sangdon (Autor:in)


    Erscheinungsdatum :

    2008-02-01


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch