Author(s): Abhijit Ghosh, Shuchi Gupta, Ruchi Singhal, Shekar Miryala, Neeraja kalluri and Manika Garg
This paper examines the associations among significant constructs by the application of Structural Equation Modeling (SEM) to establish the associations of variables and test the fit of the model in general. The main purposes are the identification of associations that are statistically significant, establishing the intensity of the associations, and verifying whether the suggested model is valid. A total of 100 samples were subjected to EFA and SEM analyses through AMOS with the use of Maximum Likelihood Estimation. Regression weights were high for some variables and not significant for others, thus reflecting the differential influence of the constructs. Variance estimates revealed the spread of data and pointed out where the model needed improvement. The history of minimization indicated gradual improvement over iterations, suggesting a good methodological approach. Model fit indices- CMIN/DF ratios and Chi-square values- indicate that the Default model is more representative of variable relationships, though not perfect. Overall, it is a far better model than the Independence model. The complexity in the interactions between constructs, found in this study, determines the need for modification and improvement of the fit model. This study opens vistas for further research in areas of phenomena under study and provides a basis for a more refined theoretical framework. It thus contributes to a better understanding of relationships among variables through rigorous analysis and targeted objectives, indicating the importance of continually optimizing the model in achieving practical and theoretical advancements.