IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v69y2016i10p4552-4564.html
   My bibliography  Save this article

The elephant in the room: Predictive performance of PLS models

Author

Listed:
  • Shmueli, Galit
  • Ray, Soumya
  • Velasquez Estrada, Juan Manuel
  • Chatla, Suneel Babu

Abstract

Attempts to introduce predictive performance metrics into partial least squares (PLS) path modeling have been slow and fall short of demonstrating impact on either practice or scientific development in PLS. This study contributes to PLS development by offering a comprehensive framework that identifies different dimensions of prediction and their effect on predictive performance evaluation with PLS. This framework contextualizes prior efforts in PLS and prediction and highlights potential opportunities and challenges. A second contribution to PLS development lies in proposed procedures to generate and evaluate different types of predictions from PLS models. These procedures account for the best practices that the new framework identifies. An outline of the many powerful ways in which predictive PLS methodologies can strengthen theory-building research constitutes a third contribution to PLS development. The framework, procedures, and research guidelines hopefully form the basis for a more informed and unified development of the rigorous theoretical and practical applications of PLS.

Suggested Citation

  • Shmueli, Galit & Ray, Soumya & Velasquez Estrada, Juan Manuel & Chatla, Suneel Babu, 2016. "The elephant in the room: Predictive performance of PLS models," Journal of Business Research, Elsevier, vol. 69(10), pages 4552-4564.
  • Handle: RePEc:eee:jbrese:v:69:y:2016:i:10:p:4552-4564
    DOI: 10.1016/j.jbusres.2016.03.049
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296316301217
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2016.03.049?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dijkstra, Theo, 1983. "Some comments on maximum likelihood and partial least squares methods," Journal of Econometrics, Elsevier, vol. 22(1-2), pages 67-90.
    2. Monecke, Armin & Leisch, Friedrich, 2012. "semPLS: Structural Equation Modeling Using Partial Least Squares," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i03).
    3. C. Vale & Vincent Maurelli, 1983. "Simulating multivariate nonnormal distributions," Psychometrika, Springer;The Psychometric Society, vol. 48(3), pages 465-471, September.
    4. Lam, J. -P. & Veall, M. R., 2002. "Bootstrap prediction intervals for single period regression forecasts," International Journal of Forecasting, Elsevier, vol. 18(1), pages 125-130.
    5. R. J. Ball, 1963. "The Significance of Simultaneous Methods of Parameter Estimation in Econometric Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 12(1), pages 14-25, March.
    6. Tenenhaus, Michel & Vinzi, Vincenzo Esposito & Chatelin, Yves-Marie & Lauro, Carlo, 2005. "PLS path modeling," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 159-205, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Reinartz, Werner & Haenlein, Michael & Henseler, Jörg, 2009. "An empirical comparison of the efficacy of covariance-based and variance-based SEM," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 332-344.
    2. José Roberto Frega & Alex Antonio Ferraresi & Carlos Olavo Quandt & Claudimar Pereira da Veiga, 2018. "Relationships Among Knowledge Management, Organisational Innovativeness and Performance: Covariance-Based Versus Partial Least-Squares Structural Equation Modelling," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-19, March.
    3. Paul, Michael & Hennig-Thurau, Thorsten & Groth, Markus, 2015. "Tightening or loosening the “iron cage”? The impact of formal and informal display controls on service customers," Journal of Business Research, Elsevier, vol. 68(5), pages 1062-1073.
    4. Anan F. Srouji & Suzan R. Abed & Madher E. Hamdallah, 2019. "Banks performance and customers' satisfaction in relation to corporate social responsibility: mediating customer trust and spiritual leadership: what counts!," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 19(3), pages 358-384.
    5. 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.
    6. Marko Sarstedt & Jun-Hwa Cheah, 2019. "Partial least squares structural equation modeling using SmartPLS: a software review," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 196-202, September.
    7. Donny Oktavian Syah, 2019. "Identifying vertical partnership among automotive component companies: empirical evidence from automotive industry in Jabodetabek, Indonesia," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-25, December.
    8. Florian Schuberth & Jörg Henseler & Theo K. Dijkstra, 2018. "Partial least squares path modeling using ordinal categorical indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 9-35, January.
    9. Michel Tenenhaus & Arthur Tenenhaus & Patrick J. F. Groenen, 2017. "Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 737-777, September.
    10. 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.
    11. Nitzl, Christian, 2016. "The use of partial least squares structural equation modelling (PLS-SEM) in management accounting research: Directions for future theory development," Journal of Accounting Literature, Elsevier, vol. 37(C), pages 19-35.
    12. Divakaran, Pradeep Kumar Ponnamma & Palmer, Adrian & Søndergaard, Helle Alsted & Matkovskyy, Roman, 2017. "Pre-launch Prediction of Market Performance for Short Lifecycle Products Using Online Community Data," Journal of Interactive Marketing, Elsevier, vol. 38(C), pages 12-28.
    13. Pasquale Dolce & Cristina Davino & Domenico Vistocco, 2022. "Quantile composite-based path modeling: algorithms, properties and applications," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 909-949, December.
    14. Pasquale Dolce & Natale Lauro, 2015. "Comparing maximum likelihood and PLS estimates for structural equation modeling with formative blocks," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 891-902, May.
    15. Jörg Henseler & Marko Sarstedt, 2013. "Goodness-of-fit indices for partial least squares path modeling," Computational Statistics, Springer, vol. 28(2), pages 565-580, April.
    16. Necmi Kemal Avkiran, 2018. "An in-depth discussion and illustration of partial least squares structural equation modeling in health care," Health Care Management Science, Springer, vol. 21(3), pages 401-408, September.
    17. Natarajan, Thamaraiselvan & Balasubramaniam, Senthil Arasu & Stephen, Gladys & Jublee, Daniel Inbaraj & Kasilingam, Dharun Lingam, 2018. "The influence of audience characteristics on the effectiveness of brand placement memory," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 134-149.
    18. Cheng-Po Lai, 2019. "Personality Traits and Stock Investment of Individuals," Sustainability, MDPI, vol. 11(19), pages 1-20, October.
    19. Pagliara, Francesca & Russo, Lucia & Aria, Massimo, 2021. "Measuring retailers’ perceptions of new metro stations inauguration," Land Use Policy, Elsevier, vol. 104(C).
    20. Annie Tubadji & Peter Nijkamp, 2015. "Cultural impact on regional development: application of a PLS-PM model to Greece," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(3), pages 687-720, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:69:y:2016:i:10:p:4552-4564. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.