# Developing Internet Online Procurement Frameworks for Construction Firms
## 4 Data Interpretations and Analysis
### User Satisfaction as Second Dependent Variable  
Table 3 shows the multiple stepwise regression analysis results pertaining to user satisfaction as the dependent variable. The value of unstandardized regression coefficient (B), standardized regression coefficient (\(\beta\)) and degree of significance (p-value) of each predictor, df, R, R2, adjusted R2, significance, and Durbin-Watson value for all the predictors in the linear regression analysis for user satisfaction are presented in Table 3. The R2 value is 0.408 indicating 40.8% variance in user satisfaction is explained by the three predicting variables. The F-value for this model is 27.346 and is significant (p \(<\) 0.05). The multiple correlation coefficient, R, for this model is 0.639 (R \(>\) 0.50), indicating a strong  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Predicting Variable**} & \multicolumn{2}{c}{**Dependent Variable: Project Management Success**} \\ \cline{2-4}  & **Unstandardized** & **Standardized** & **Sig.** \\  & **Coefficient (B)** & **Coefficient (\(\beta\))** & **(\(p\)-Value)** \\ \hline
1) Incorporation of e-procurement policy into existing procurement policy & 0.243 & 0.315 & 0.001 \\ \hline
2) IT consultant supports during the implementation process & 0.201 & 0.233 & 0.009 \\ \hline
3) Willingness of the organization to change & 0.156 & 0.218 & 0.012 \\ \hline
4) Defines the level each stakeholder can get involved & 0.166 & 0.208 & 0.014 \\ \hline
5) Project activity properly coordinated and monitored & \(-\)0.203 & \(-\)0.246 & 0.006 \\ \hline n & & 123 & \\ \hline df & & 5117 & \\ \hline F & & 14.571 & \\ \hline R & & 0.619 & \\ \hline R\({}^{2}\) & & 0.384 & \\ \hline Adjusted R\({}^{2}\) & & 0.357 & \\ \hline Sig. & & 0.000 & \\ \hline Durbin-Watson & & 1.921 & \\ \hline \hline \end{tabular} Note: significant when \(p<0.05\).  
\end{table}
Table 2: Stepwise hierarchical regression models (project management success).  
association between the predicting variables and the dependent variable. The R2 value of about 0.37 is considered high according to [68], which indicates that the regression line fits the data set well and that there is a strong linear relationship between the predicting variables and the dependent variable. The Durbin-Watson value of 1.847 indicates that the serial correlation of residual falls within the acceptable range of 1.5 and 2.5, suggesting that the conditions of no autocorrelation problem [56] and observations being independent of predicted values [2; 10] are satisfied. Three predicting variables are found to be significant in explaining user satisfaction, which are the reinforcement of the commitment of employees (X1), the establishment of appropriate milestones for the project (X2), and the willingness of the organization to change (X3). As depicted in Table 3, the predicted model generates Equation (2):  
\[\text{User Satisfaction}=1.293+0.227(\text{X1})+0.247(\text{X2})+0.160(\text{X3}) \tag{2}\]  
Table 3 also shows that the largest beta coefficient (\(\beta\)) at 0.287 is with the item \"reinforcement of the commitment of the employees\". This predictor has the strongest unique contribution to explaining the dependent variable. The \(\beta\)-value at 0.271 for the predictor \"establishment of appropriate milestones is the second highest, followed by the predictor \"willingness of the organization to change\" at 0.213.