# Developing Internet Online Procurement Frameworks for Construction Firms
## 4 Data Interpretations and Analysis
### Project Management Success as Dependent Variable  
Table 2 shows the multiple stepwise regression analysis for project management success as the dependent variable. The values of the unstandardized regression coefficient (B), standardized regression coefficient (\(\theta\)) 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 project management success are presented in Table 2. The R2 measures the proportion of total variance on the dependent variable that is accounted for by the set of predictors. It explains how the model fits the data set. The R2 value is 0.384, which indicates that 38.4% of the variance in e-procurement implementation success is explained by the five predicting variables. The F-value for this model is 14.571 and significant (p \(<\) 0.05). Moreover, the multiple correlation coefficient, R, for this model is 0.619 (R \(>\) 0.50), and this shows the strength of the association that these five predictors have with the dependent variable. An R2 value of about 0.37 is considered high according to [PERSON] [61]. Thus, it 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. A Durbin-Watson value at 1.921 indicates that the serial correlation of  
Figure 1: Scatter plot of variables in correlation analysis.  
Figure 2: Scatter plot of correlation and linearity.  
residual falls within the acceptable range of 1.5 and 2.5, thereby suggesting that the conditions of there being no autocorrelation problem [64] and the observations being independent of predicted values [65; 66; 67] are satisfied.  
Five predicting variables are found to be significant in explaining e-procurement implementation success based on project management success criteria. These are the incorporation of e-procurement policy into existing procurement policy (X1), IT consultant support during implementation process (X2), the willingness of the organization to change (X3), the definition of the level each stakeholder can get involved (X4), and project activity that is properly coordinated and monitored (X5). As depicted in Table 2, the predicted model generated from this study is shown in Equation (1):  
\[\text{Project management success}=1.612+0.243(\text{X1})+0.201(\text{X2})+0.156( \text{X3})+0.166(\text{X4})-0.203(\text{X5}) \tag{1}\]  
Table 2 also shows that the largest beta coefficient (\(\beta\)) relates the item \"incorporating e-procurement policy into existing procurement policy\" with the value of 0.315. This says that the item makes the strongest unique contribution to explaining the dependent variable when the variance explained by all other predicting variables in the model is controlled for. The \(\beta\)-value for the item \"IT consultant support during implementation process\" with the value of 0.233 is the second highest, followed by the item \"willingness of the organization to change\" with the value of 0.156. Ranked fourth is the item \"defines the level each stakeholder can get involved\" with the value of 0.166 and the item \"project activities properly coordinated and monitored\" with the value of \(-0.203\) is ranked last.