期刊
PRODUCTION PLANNING & CONTROL
卷 28, 期 11-12, 页码 1011-1021出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/09537287.2016.1267411
关键词
PLS-SEM; big data; big data analytics quality; business value; satisfaction
The emergence of multivariate analysis techniques transforms empirical validation of theoretical concepts in social science and business research. In this context, structural equation modelling (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.
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