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The first method, PLS-SEM, was utilized in the research article “Influences of gender and product type on online purchasing” done by…
analyzed and the sample sizes for each of the two research papers, the data analysis methods needs to be effective to provide a comprehensive report on the findings.
These two articles cover all the key data analysis requirements. Furthermore, the data analysis section for both of these has been comprehensively outlined and explained to ensure the reader understanding the steps that were taken in order to generate results. An inspection on both articles shows that each article followed the systematic process required within the chosen technique.
Pascual-Miguel, Félix J., Ángel F. Agudo-Peregrina, and Julián Chaparro-Peláez (2015). "Influences of gender and product type on online purchasing." Journal of Business Research 68.7: 1550-1556.
Partial least squares path modeling (PLS-SEM) is among the favorite methods often utilized in business research. According to Hair, Sarstedt, Pieper, and Ringle (2012), PLS-SEM has gained significant popularity within the business research discipline over the last two decades. Several reasons have been given for this increased interest. The most consistent reasons being its resourcefulness in non-normal data, working with formative measures, accuracy in small sample sizes, and for studies that are focusing on prediction (Hair, Sarstedt, Pieper, & Ringle 2012). In the research by Pascual-Miguel, Agudo-Peregrina, and Chaparro-Peláez (2015), the method was chosen because of its ability to analyze complex models and for predictive purposes. With gender being an essential characteristic of the research, the authors took this into consideration and split the sample to carry out a multi-group analysis.
The Partial least squares path modeling (PLS-SEM) model is carried out in two-stage algorithm with the first stage consisting of five steps. In stage one an “iterative estimation of latent constructs” is carried out which includes the four steps that build upon approximation and estimation of latent construct scores and ...
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