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

Author

Listed:
  • 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)

  • Christian M. Ringle

    (Institute of Human Resource Management and Organizations, Hamburg University of Technology (TUHH), Hamburg 21073, Germany; and University of Newcastle, Newcastle, NSW 2308, Australia)

  • 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)

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.

Suggested Citation

  • Edward E. Rigdon & Jan-Michael Becker & Arun Rai & Christian M. Ringle & Adamantios Diamantopoulos & Elena Karahanna & Detmar W. Straub & Theo K. Dijkstra, 2014. "Conflating Antecedents and Formative Indicators: A Comment on Aguirre-Urreta and Marakas," Information Systems Research, INFORMS, vol. 25(4), pages 780-784, December.
    • Handle: RePEc:inm:orisre:v:25:y:2014:i:4:p:780-784
    DOI: 10.1287/isre.2014.0543
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    References listed on IDEAS

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    1. Diamantopoulos, Adamantios & Riefler, Petra & Roth, Katharina P., 2008. "Advancing formative measurement models," Journal of Business Research, Elsevier, vol. 61(12), pages 1203-1218, December.
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    Cited by:

    1. Sarstedt, Marko & Hair, Joseph F. & Ringle, Christian M. & Thiele, Kai O. & Gudergan, Siegfried P., 2016. "Estimation issues with PLS and CBSEM: Where the bias lies!," Journal of Business Research, Elsevier, vol. 69(10), pages 3998-4010.
    2. Jose Benitez & Laura Ruiz & Ana Castillo & Javier Llorens, 2020. "How corporate social responsibility activities influence employer reputation: The role of social media capability," Post-Print hal-02462583, HAL.
    3. Rigdon, Edward E., 2016. "Choosing PLS path modeling as analytical method in European management research: A realist perspective," European Management Journal, Elsevier, vol. 34(6), pages 598-605.
    4. Miguel I. Aguirre-Urreta & George M. Marakas, 2014. "A Rejoinder to Rigdon et al. (2014)," Information Systems Research, INFORMS, vol. 25(4), pages 785-788, December.
    5. Ajamieh, Aseel & Benitez, Jose & Braojos, Jessica & Gelhard, Carsten, 2016. "IT infrastructure and competitive aggressiveness in explaining and predicting performance," Journal of Business Research, Elsevier, vol. 69(10), pages 4667-4674.
    6. Joseph F. Hair & G. Tomas M. Hult & Christian M. Ringle & Marko Sarstedt & Kai Oliver Thiele, 2017. "Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods," Journal of the Academy of Marketing Science, Springer, vol. 45(5), pages 616-632, September.
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    8. Schlittgen, Rainer & Ringle, Christian M. & Sarstedt, Marko & Becker, Jan-Michael, 2016. "Segmentation of PLS path models by iterative reweighted regressions," Journal of Business Research, Elsevier, vol. 69(10), pages 4583-4592.
    9. Liu, Yuqing & Schuberth, Florian & Liu, Yide & Henseler, Jörg, 2022. "Modeling and assessing forged concepts in tourism and hospitality using confirmatory composite analysis," Journal of Business Research, Elsevier, vol. 152(C), pages 221-230.
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