## 4 Results
In Table 4, the results of the structural model and the results of the mediation analysis are shown. The control variables (size and age) were eliminated, as they were not significant for the dependent variable. To contrast the hypotheses of mediation, the direct effects model (Figure 2) between senior management support and BIM effectiveness was first assessed, which was certainly significant. Secondly, the model with mediated effects was evaluated (Figure 3), introducing the following mediating variables: technological learning and collaborative culture. Finally, the VAF (variance accounted for) value was calculated in the mediator model to determine the mediation strength. Figure 3 represents the model of mediated effects to contrast hypotheses H2 (+) and H3 (+). Table 4 shows the results of the structural model with direct effects (Figure 2) and with mediated effects (Figure 3). Again, Table 4 shows that there was no collinearity between the variables of the model, since the VIF values were under 3. The results in Table 4 were obtained under a one-tailed Student's t test distribution, because the hypotheses with a (+) sign were stated. In addition, shown in Table 4 are the values of the path  
\begin{table} \begin{tabular}{c c} \hline \hline
**Direct Effects Model** & **Path Coefficient *\(\beta\)* (T-Value)** \\ \hline VIF (SMS \(\rightarrow\) BIME) = 2.1263 & C = 0.698 *** (14.959) \\ BIM Effectiveness & R\({}^{2}\) = 0.487 \\ \hline Mediated effects model & Coefficient Path *\(\beta\)* (T-valor) \\ \hline VIF (SMS \(\rightarrow\) TL) = 1.0000 & A = 0.672 *** (11.325) \\ VIF (TL \(\rightarrow\) BIME) = 1.6145 & B = 0.310 ** (2.090) \\ VIF (SMS \(\rightarrow\) CCD) = 1.0000 & a\({}^{\prime}\) = 0.592 *** (10.512) \\ VIF (CCU \(\rightarrow\) BIME) = 1.9113 & b\({}^{\prime}\) = 0.418 ** (42.254) \\ VIF (SMS \(\rightarrow\) BIME) = 2.1263 & c\({}^{\prime}\) = 0.213 *N (1.560) \\ Technological learning & R\({}^{2}\) = 0.350 \\ Collaborative culture & R\({}^{2}\) = 0.451 \\ BIM effectiveness & R\({}^{2}\) = 0.648 \\ \hline \hline \end{tabular}   
coefficients \"\(\beta\)\" (T-value) for each path. To estimate the path coefficients, a Bootstrap resampling procedure was performed with 5000 subsamples. Table 4 shows the R\({}^{2}\) value for technological learning (R\({}^{2}\) = 0.350), collaborative culture (R\({}^{2}\) = 0.451), and BIM effectiveness (R\({}^{2}\) = 0.648). The higher the value of R\({}^{2}\), the more predictive power exists in the model. According to [85], R\({}^{2}\) values (0.67, 0.33, and 0.10) were considered as prediction reference values (substantial, moderate, and weak). According to [86], R\({}^{2}\) values (0.75, 0.50, and 0.25) were considered as values (substantial, moderate, and weak). Therefore, the values obtained are relevant to explain BIM effectiveness. The model with mediated effects verified that H1 (+) was proved in the model with direct effects and H2 (+) and H3 (+) were demonstrated in the model with mediated effects. Table 5 shows the contrast of hypotheses for the model of mediated effects, and the VAF value was calculated to know the type of mediation. The strength of the mediation was calculated through VAF. According to [87], if the VAF value is greater than 80% it is complete mediation and if the VAF value is between 20% and 80% it is partial mediation. Therefore, as the VAF value was 68.15%, the relationship between senior management support and BIM effectiveness was a partially mediated relationship by technological learning and by the collaborative culture in a multiple way. The direct effects model explained 48.7% of the variance of BIM effectiveness, and the model with mediating effects explained 68.4% of the variance of BIM effectiveness. Therefore, it is very important that management support not only technological projects, but also a collaborative culture and technological learning, as it has been demonstrated that, if management fosters both in the BIM team, the capacities to use this technology improve.