Adv Data Anal Classif DOI 10.1007/s11634-017-0302-1 REGULAR ARTICLE Non-symmetrical composite-based path modeling Pasquale Dolce 1 · Vincenzo Esposito Vinzi 2 · Natale Carlo Lauro 3 Received: 13 February 2017 / Revised: 5 November 2017 / Accepted: 7 November 2017 © Springer-Verlag GmbH Germany, part of Springer Nature 2017 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 direc- tions, 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 vari- ability, 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. Keywords PLS path modeling · Non-symmetrical analysis · Predictive composite- based methods Mathematics Subject Classification 62H99 B Pasquale Dolce pasquale.dolce@unina.it 1 University of Naples Federico II, Napoli, Italy 2 Department of Information Systems, Decision Sciences and Statistics, ESSEC Business School of Paris, Cergy-Pontoise Cedex, France 3 Department of Economics and Statistics, University of Naples Federico II, Napoli, Italy 123