Publication Details

Akter, S., Fosso Wamba, S. & Dewan, S. (2017). Why PLS-SEM is suitable for complex modeling? An empirical illustration in Big Data Analytics Quality. Production Planning and Control, 28 (11-12), 1011-1021.


The emergence of multivariate analysis techniques transforms empirical validation of theoretical concepts in social science and business research. In this context, structural equation modeling (SEM) has emerged as a powerful tool to estimate conceptual models linking two or more latent constructs. This paper shows the suitability of the partial least squares (PLS) approach to SEM (PLS-SEM) in estimating a complex model drawing on the philosophy of verisimilitude and the methodology of soft modelling assumptions. The results confirm the utility of PLS-SEM as a promising tool to estimate a complex, hierarchical model in the domain of big data analytics quality (BDAQ).

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