A PARAMETRIC APPROACH TO PARTIAL LEAST SQUARE STRUCTURAL EQUATION MODELING OF MULTIGROUP ANALYSIS (PLS-MGA)

Recently, Partial Least Square Structural Equation Modeling (PLS-SEM) has become pervasive among the scholar in variety of areas to examine or predict selected variables in order to achieve the goals that have been set based on the issues faced by researchers. Thus, vary of method has been performed to ascertain the researchers attain the necessity of their survey in more holistic. The main objective of this empirical works to provide a step by step approach to anyone whom interested to perform a multi-group analysis (moderating effect). In particular, the author practice the parametric approach that has been proposed by previous research using two different methods of equal and unequal variances. For this instances, five variables selected which are Benefit, Barrier, Government, Challenge and Motivation introduced to practice of these both approach. All of these variables have been tested with the existence of moderating effect (gender variable) to identify whether of particular moderator variable has a potential to affect the impact of causal effect in PLS-SEM. Of rely on both differences methods, the PLS suggest that gender variable is not a main issue whether of improve or impairs the impact of the survey implemented