Conflating Antecedents and Formative Indicators: A Comment on Aguirre-Urreta and Marakas

Edward E. Rigdon (), Jan-Michael Becker (), Arun Rai (), Christian Ringle, Adamantios Diamantopoulos (), Elena Karahanna (), Detmar W. Straub () and Theo K. Dijkstra ()
Additional contact information
Edward E. Rigdon: Department of Marketing, J. Mack Robinson College of Business, Georgia State University, Atlanta, Georgia 30303
Jan-Michael Becker: Department of Marketing and Brand Management, University of Cologne, Cologne 50923, Germany
Arun Rai: Center for Process Innovation and Department of Computer Information Systems, J. Mack Robinson College of Business, Georgia State University, Atlanta, Georgia 30303
Adamantios Diamantopoulos: Chair of International Marketing, University of Vienna, 1090 Vienna, Austria
Elena Karahanna: Department of Management Information Systems, Terry College of Business, University of Georgia, Athens, Georgia 30602
Detmar W. Straub: Professor, Georgia State University, Atlanta, Georgia 30303; Visiting Professor, Fox School of Business, Temple University, Philadelphia, Pennsylvania 19122; and Visiting Professor, Korea University Business School, Korea University, Seoul 136-701, Korea
Theo K. Dijkstra: University of Groningen, 9712 CP Groningen, The Netherlands

Information Systems Research, 2014, vol. 25, issue 4, 780-784

Abstract: Aguirre-Urreta and Marakas [Aguirre-Urreta MI, Marakas GM (2014) Research note—Partial least squares and models with formatively specified endogenous constructs: A cautionary note . Inform. Systems Res. 25(4):761--778] aim to evaluate the performance of partial least squares (PLS) path modeling when estimating models with formative endogenous constructs, but their ability to reach valid conclusions is compromised by three major flaws in their research design. First, their population data generation model does not represent “formative measurement” as researchers generally understand that term. Second, their design involves a PLS path model that is misspecified with respect to their population model. Third, although their aim is to estimate a composite-based PLS path model, their design uses simulation data generated via a factor analytic procedure. In consequence of these flaws, Aguirre-Urreta and Marakas' (2014) study does not support valid inference about the behavior of PLS path modeling with respect to endogenous formatively measured constructs.

Keywords: formative indicators; partial least squares; endogenous constructs (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (12)

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