Relationship of Big Data Analytics Capability and Product Innovation Performance using SmartPLS 3.2.6: Hierarchical Component Modelling in PLSSEM
Partial Least Squares Structural Equation Modeling (PLS-SEM) is well-known as the second generation of multivariate statistical analysis to correlate the relationship between multiple variables namely the latent construct. Lately, the popularity using PLS-SEM is growing within the Variance-Based (VB...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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ExcelingTech Publishers
2018
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/24446/1/IJSCM%207%201%202018%2051%2064.pdf http://repo.uum.edu.my/24446/ http://ojs.excelingtech.co.uk/index.php/IJSCM/article/view/1838 |
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| Summary: | Partial Least Squares Structural Equation Modeling (PLS-SEM) is well-known as the second generation of multivariate statistical analysis to correlate the relationship between multiple variables namely the latent construct. Lately, the popularity using PLS-SEM is growing within the Variance-Based (VB) SEM community.There is still a great number of researcher finding VB-SEM results reporting a daunting task. Ultimately, an advanced PLS-SEM analysis utilizing product innovation performance example with SmartPLS 3.2.6 tool.Higher order construct or hierarchical component modelling is seen as an advanced tool towards the parsimony of the research variables conceptualization. |
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