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Interpretation of Formative Measurement in Information Systems Research1

Ronald T. Cenfetelli¹; Geneviève Bassellier²

¹ Sauder School of Business, The University of British Columbia, Vancouver BC V6T 1Z2, Canada; · ² Desautels Faculty of Management, McGill University, Montreal QC H3A 1G5, Canada

Within the Information Systems literature, there has been an emerging interest in the use of formative measurement in structural equation modeling (SEM). This interest is exemplified by descriptions of the nature of formative measurement (e.g., Chin 1998a), and more recently the proper specification of formatively measured constructs (Petter et al. 2007) as well as application of such constructs (e.g., Barki et al. 2007). Formative measurement is a useful alternative to reflective measurement. However, there has been little guidance on interpreting the results when formative measures are employed. Our goal is to provide guidance relevant to the interpretation of formative measurement results through the examination of the following six issues: multicollinearity; the number of indicators specified for a formatively measured construct; the possible co-occurrence of negative and positive indicator weights; the absolute versus relative contributions made by a formative indicator; nomological network effects; and the possible effects of using partial least squares (PLS) versus covariance-based SEM techniques. We provide prescriptions for researchers to consider when interpreting the results of formative measures as well as an example to illustrate these prescriptions.

DOI

10.2307/20650323

Volume

33 (4)

Pages

689-708

Language

en

Export

BibTeX

Sources

crossref