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PLS and Success Factor Studies in Marketing

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Part of the book series: Springer Handbooks of Computational Statistics ((SHCS))

Abstract

While in consumer research the “Cronbach’s α – LISREL”-paradigm has emerged for a better separation of measurement errors and structural relationships, it is shown here that studies involving an evaluation of the effectiveness of marketing or organizational strategies based on structural relationships require the application of PLS. This is because we no longer distinguish between constructs and their reflecting measures but rather between abstract marketing policies (constructs) and their forming detailed marketing instruments (indicators). It is shown with the help of examples from literature that many studies of this type applying LISREL have been misspecified and would have better made use of the PLS approach. I also demonstrate the appropriate use of PLS in a study of success factors for e-businesses. I conclude with recommendations on the appropriate design of success factor studies, including the use of higher-order constructs and the validation of such studies.

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Author information

Authors and Affiliations

  1. Institute of Innovation Research, Christian-Albrechts-University at Kiel, Westring 425, 24098, Kiel, Germany

    Sönke Albers

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  1. Sönke Albers
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Correspondence to Sönke Albers .

Editor information

Editors and Affiliations

  1. Dept. Inf. Systems & Decision Sciences, ESSEC Business School of Paris, av. Bernard Hirsch, Cergy Pontoise CX, 95021, France

    Vincenzo Esposito Vinzi

  2. Bauer College of Business, University of Houston, Houston, 77204-6282, U.S.A.

    Wynne W. Chin

  3. Nijmegen School of Management, Radboud University, Nijmegen, Netherlands

    Jörg Henseler

  4. School of Economics & Management, BeiHang University, XueYuan Road 37, Beijing, 100083, China, People's Republic

    Huiwen Wang

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Albers, S. (2010). PLS and Success Factor Studies in Marketing. In: Esposito Vinzi, V., Chin, W., Henseler, J., Wang, H. (eds) Handbook of Partial Least Squares. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_19

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