Using Item Response Theory to Measure Extreme Response Style in Marketing Research: A Global Investigation

Extreme response style (ERS) is an important threat to the validity of survey-based marketing research. In this article, the authors present a new item response theory-based model for measuring ERS. This model contributes to the ERS literature in two ways. First, the method improves on existing proc...

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Bibliographische Detailangaben
Veröffentlicht in:Journal of Marketing Research. - American Marketing Association. - 45(2008), 1, Seite 104-115
1. Verfasser: de Jong, Martijn G. (VerfasserIn)
Weitere Verfasser: Steenkamp, Jan-Benedict E. M., Fox, Jean-Paul, Baumgartner, Hans
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2008
Zugriff auf das übergeordnete Werk:Journal of Marketing Research
Schlagworte:item response theory response styles scale usage testlets systematic measurement error varying item parameters measurement invariance international marketing research Mathematics Business mehr... Applied sciences Information science Social sciences Education Political science
Beschreibung
Zusammenfassung:Extreme response style (ERS) is an important threat to the validity of survey-based marketing research. In this article, the authors present a new item response theory-based model for measuring ERS. This model contributes to the ERS literature in two ways. First, the method improves on existing procedures by allowing different items to be differentially useful for measuring ERS and by accommodating the possibility that an item's usefulness differs across groups (e.g., countries). Second, the model integrates an advanced item response theory measurement model with a structural hierarchical model for studying antecedents of ERS. The authors simultaneously estimate a person's ERS score and individual- and group-level (country) drivers of ERS. Through simulations, they show that the new method improves on traditional procedures. They further apply the model to a large data set consisting of 12,506 consumers from 26 countries on four continents. The findings show that the model extensions are necessary to model the data adequately. Finally, they report substantive results about the effects of socio-demographic and national-cultural variables on ERS.
ISSN:00222437