Measurement in the social sciences: where C-OAR-SE delivers and where it does not

Salzberger, Thomas; Sarstedt, Marko und Diamantopoulos, Adamantios (2016): Measurement in the social sciences: where C-OAR-SE delivers and where it does not. In: European Journal of Marketing, Bd. 50, Nr. 11: S. 1942-1952

Abstract

Purpose This paper aims to critically comment Rossiter’s “How to use C-OAR-SE to design optimal standard measures” in the current issue of EJM and provides a broader perspective on Rossiter’s C-OAR-SE framework and measurement practice in marketing in general.

Design/methodology/approach The paper is conceptual, based on interpretation of measurement theory.

Findings The paper shows that, at best, Rossiter’s mathematical dismissal of convergent validity applies to the completely hypothetical (and highly unlikely) situation where a perfect measure without any error would be available. Further considerations cast serious doubt on the appropriateness of Rossiter’s concrete object, dual subattribute-based single item measures. Being immunized against any piece of empirical evidence, C-OAR-SE cannot be considered a scientific theory and is bound to perpetuate, if not aggravate, the fundamental flaws in current measurement practice. While C-OAR-SE indeed helps generate more content valid instruments, the procedure offers no insights as to whether these instruments work properly to be used in research and practice.

Practical implications This paper concludes that great caution needs to be exercised before adapting measurement instruments based on the C-OAR-SE procedure, and statistical evidence remains essential for validity assessment.

Originality/value This paper identifies several serious conceptual and operational problems in Rossiter’s C-OAR-SE procedure and discusses how to align measurement in the social sciences to be compatible with the definition of measurement in the physical sciences.

• Dokumententyp: Zeitschriftenartikel
• Keywords: Psychometrics, Content validity, C-OAR-SE, Convergent validity, Predictive validity
• Fakultät: Betriebswirtschaft > Institut für Marketing
• Themengebiete: 300 Sozialwissenschaften > 330 Wirtschaft
• ISSN: 0309-0566
• Sprache: Englisch