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Non-symmetrical composite-based path modeling

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Abstract

Partial least squares path modeling presents some inconsistencies in terms of coherence with the predictive directions specified in the inner model (i.e. the path directions), because the directions of the links in the inner model are not taken into account in the iterative algorithm. In fact, the procedure amplifies interdependence among blocks and fails to distinguish between dependent and explanatory blocks. The method proposed in this paper takes into account and respects the specified path directions, with the aim of improving the predictive ability of the model and to maintain the hypothesized theoretical inner model. To highlight its properties, the proposed method is compared to the classical PLS path modeling in terms of explained variability, predictive relevance and interpretation using artificial data through a real data application. A further development of the method allows to treat multi-dimensional blocks in composite-based path modeling.

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Notes

  1. In particular, when new Mode A is applied, outer weights are normalized to unit length.

  2. Weights are then standardized such that the resulting composite has unit variance.

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Authors and Affiliations

  1. University of Naples Federico II, Napoli, Italy

    Pasquale Dolce

  2. Department of Information Systems, Decision Sciences and Statistics, ESSEC Business School of Paris, Cergy-Pontoise Cedex, France

    Vincenzo Esposito Vinzi

  3. Department of Economics and Statistics, University of Naples Federico II, Napoli, Italy

    Natale Carlo Lauro

Authors
  1. Pasquale Dolce
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  2. Vincenzo Esposito Vinzi
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  3. Natale Carlo Lauro
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Correspondence to Pasquale Dolce.

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Dolce, P., Vinzi, V.E. & Lauro, N.C. Non-symmetrical composite-based path modeling. Adv Data Anal Classif 12, 759–784 (2018). https://doi.org/10.1007/s11634-017-0302-1

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