## 6 Discussion  
To achieve the objectives of this study, SEM statistical technique were used. After running pooled CFA, the final measurement model resulted in Relative Chi-Sq (\(\leq\)3) = 1.814, CFI (\(\geq\)0.9) = 0.905, IFI (\(\geq\)0.9) = 0.906, RMSEA (\(\leq\)0.08) = 0.058; this indicates that the data fit the model. Moreover, all six constructs of the model have exhibited the required construct reliability, convergent validity, and discriminant validity. This indicates that the six-constructs model with 39 items had a good fit and exhibits the good construct reliability, convergent validity, and discriminant validity of the model prior to testing the research hypotheses. This model was developed based on the results of a systematic mapping study [23] and then soundly validated via the iterative method in [24]. Therefore,it was not necessary to apply EFA in this study. Nevertheless, we assume that some readers and researchers prefer to perform EFA before CFA, because CFA does not show how the items are grouped and loaded in each construct [69; 81]. Therefore, a detailed result for EFA is reported in the Supplementary Materials. The EFA results confirmed the measurement model structure used in this study. Finally, a set of hypotheses was formulated to establish a relationship between each customization approach and SaaS quality. The hypotheses were empirically tested to determine if customization has a significance impact on SaaS quality. The findings of the structural model assessment show that all customization approaches, bar the integration approach, significantly influence the quality of SaaS application. Moreover, it revealed that the impact of configuration and composition approaches on SaaS quality is positive, while the impact of other approaches is negative. The positive effects of the composition and configuration approaches could be attributed to the fact that numerous SaaS vendors offer built-in tools and support interfaces to allow such approaches to be implemented, as such facilities can boost application usage without changing the source code. In such customization approaches, the efforts needed to make changes will improve the maintainability and usability of the application by enabling the customers to performed some customization and maintenance jobs using the built-in tools and interfaces provided in these approaches. Since the maintainability and usability of SaaS application could be improved, the improvement in overall quality of SaaS could be considered as well. conversely, the negative influence of the modification and extension approaches on SaaS quality is attributed to the significant work necessary to implement the modification \begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Hypothesis** & **B** & **SE** & **Beta** & **C.R.** & **P** \\ \hline
**H1:** Configuration===\textgreater{}SaaS Quality & 0.419 & 0.061 & 0.589 & 6.838 & ** 0.000 \\
**H2:** Composition===\textgreater{}SaaS Quality & 0.301 & 0.064 & 0.330 & 4.692 & ** 0.000 \\
**H3:** Extension===\textgreater{}SaaS Quality & \(-\)0.108 & 0.045 & \(-\)0.144 & \(-\)2.385 & * 0.017 \\
**H4:** Integration===\textgreater{}SaaS Quality & 0.047 & 0.053 & 0.0520 & 0.882 & 0.378 \\
**H5:** Modification===\textgreater{}SaaS Quality & \(-\)0.328 & 0.067 & \(-\)0.386 & \(-\)4.923 & ** 0.000 \\ \hline \hline \end{tabular}  
* Significant at the 0.05 level. ** Significant at the 0.001 level.  
\end{table} 
Table 5: Hypothesis testing results. or extension changes to the application code. In the SaaS application environment, the operator must change the application code and perform a redeployment for each tenant. Therefore, these approaches are bound to have a negative impact as successful multi-tenancy must have a stable code foundation. A general observation of these findings is that all customization approaches that have a statistically significant effect on SaaS quality belong to the internal change category, whereas the integration approach belongs to the external change category as discussed in [82].