Theo K. Dijkstra

Learn More
The CANDECOMP/PARAFAC (CP) model decomposes a three-way array into a prespecified number of R factors and a residual array by minimizing the sum of squares of the latter. It is well known that an optimal solution for CP need not exist. We show that if an optimal CP solution does not exist, then any sequence of CP factors monotonically decreasing the CP(More)
A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While maintaining all the strengths of PLS, the consistent version provides two key improvements. Path coefficients, parameters of simultaneous equations, construct correlations, and indicator loadings are estimated consistently. The global goodness-of-fit of the(More)
Institute for Management Research, Radboud University Nijmegen, The Netherlands; Higher Institute of Statistics and Knowledge Management (ISEGI), Universidade Nova de Lisboa, Portugal; Faculty of Business Studies and Economics, University of Kaiserslautern, Germany; Faculty of Economic and Business, University of Groningen, The Netherlands; School of Media(More)
This paper resumes the discussion in information systems research on the use of partial least squares (PLS) path modeling and shows that the inconsistency of PLS path coefficient estimates in the case of reflective measurement can have adverse consequences for hypothesis testing. To remedy this, the study introduces a vital extension of PLS: consistent PLS(More)
The subject of factor indeterminacy has a vast history in factor analysis (Wilson, 1928; Lederman, 1938, Guttman, 1955). It has lead to strong differences in opinion (Steiger, 1979). The current paper gives necessary and sufficient conditions for observability of factors in terms of the parameter matrices and a finite number of variables. Five conditions(More)
This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited(More)
Partial Least Squares as applied to models with latent variables, measured indirectly by indicators, is well-known to be inconsistent. The linear compounds of indicators that PLS substitutes for the latent variables do not obey the equations that the latter satisfy. We propose simple, non-iterative corrections leading to consistent and asymptotically normal(More)
A and Marakas [ A3 Aguirre-Urreta M, Marakas G (2013) Research note—Partial least squares and models with formatively specified endogenous constructs: A cautionary note. Inform. Systems Res., ePub ahead of print September 5, http://dx.doi.org/10.1287/isre.2013.0493] aim to evaluate the performance of partial least squares (PLS) path modeling when estimating(More)
The subject of factor indeterminacy has a vast history in factor analysis Wil son Lederman Guttman It has lead to strong di erences in opinion Steiger The current paper gives necessary and su cient conditions for observability of factors in terms of the parameter matrices and a nite number of variables Five conditions are given which rigorously de ne(More)