# Evaluating a Proposed E-Government Stage Model in Terms of Personal Data Protection
## 3 Assessment Methodology
### AHP-SOAR Calculation  
The purpose of SOAR analysis is to quantitatively assess the criteria or elements of SOAR and determine their relative importance. This technique scans both the supply and demand sides. It will be challenging to assess the factors that have the most influence on decision making. Therefore, it is impossible to make an accurate decision using the SOAR analysis alone. The Analytical Hierarchy Process (AHP) and the computation of its Eigen values are combined with SOAR analysis in this study. A quantitative assessment of the impact of each element on decision-making will be provided using the AHP technique. The SOAR factors attributed to each SOAR group are represented at the lowest (third) level. This is shown in Figure 5. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline IR & **0** & **0** & **0.58** & **0.90** & **1.12** & **1.24** & **1.32** & **1.41** & **1.45** & **1.49** & **1.51** & **1.48** \\ \hline Matrix & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 \\ \hline \end{tabular}
\end{table} 
Table 3: Random Index Values Based on Matrix Scales [19]. The hierarchical structure of the evaluation process is achieved in this section. As explained in Figure 6, the AHP structure consists of different levels. The upper level is the main goal (G), which is evaluating proposed e-government stage model with considerations of protecting personal data. The level below the upper level (second level) represents the essential targets (T) of the proposed model such as:  
* T1: Improve security of personal information. * T2: Achieve trust to e-government services. * T3: Provide a reliable communication between the government and its stakeholders. Figure 6 shows the hierarchical structure of the AHP paired with the SOAR factors of the proposed e-government stage model. Figure 5: SOAR Group Factors for the Proposed Model. Figure 6: AHP Structure combined with SOAR Group Factors. To assess any system accurately, it is crucial to choose an appropriate and accurate approach to use. The methodology of this study mainly depends on two approaches that have roles in evaluating and determining the viability of the proposed stage model. Figure 7 shows the steps and the combination of the two approaches. Numerous factors need be taken into account. In AHP, the number of pairwise comparisons increases exponentially as the number of factors increases. As a result, the current method included four criteria for each of the four SOAR groups, but only four of these factors will be used in this scenario. It is important to remember that, in accordance with [20], no more than 10 components should be included in each SOAR category. One comparison matrix will be used at level one to provide pairwise comparisons of essential targets in relation to the assessment's goal. To determine the most important goal and use its values as a scaling factor, the first comparison matrix is 3 by 3 in size. In order to determine the scaling factors for the following level, pairwise comparisons of SOAR factors are performed inside each individual SOAR group, with respect to the targets. Following this, comparisons are made based on Saaty's scale, taking into account the relative importance of two elements' intensities, applying the verbal scale connected to the 1-9 scale, as shown in Table 2[21]. Additionally, it may accommodate both qualitative and quantitative data, as necessary by the AHP's pairwise comparison style. The local priorities of the elements are determined via the Eigen value technique using these comparisons as the input, as described in section (AHP). These rankings mirror the decision-makers' perceptions of the elements' pertinent importance. Pairwise comparisons at the next level were performed to determine which factor in the group had the greatest value. As a result, the first and second tiers' comparison matrices are, respectively, 3 by 3 and 4 by 4 in size.