## 5 Results/Findings
### Assessment of Structural Model (Inner Model)  
To validate the statistical validity, a bootstrapping procedure of 5000 resamples was conducted to produce \(t\)-values and standard errors [50,58,59]. In this analysis, a structural model was tested to assess the causal relationships between on-the-job embeddedness, off-the-job embeddedness and the intention to remain in Malaysian construction companies with continuance commitment mediating variable. As described by the independent variables in the experiment, R\({}^{2}\) calculates the model's predictive accuracy and represents the percentage of uncertainty in the dependent variables. In comparison, path coefficients (8) reflect, as seen in Figure 3 and Table 5, the degree of change in the dependent variable for each independent variable. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Items** & **CC** & **FC** & **FO** & **ITS** & **LC** & **LO** & **SC** & **SO** \\ \hline Contiuance & & & & & & & & \\ Commitment & & & & & & & \\ Fit Community & 0.678 & & & & & & \\ Fit Organization & 0.347 & 0.489 & & & & & \\ Intention to Stay & 0.850 & 0.728 & 0.381 & & & & \\ Link Community & 0.778 & 0.815 & 0.295 & 0.766 & & & \\ Link Organization & 0.647 & 0.673 & 0.578 & 0.590 & 0.674 & & \\ Sacrifice Community & 0.812 & 0.720 & 0.301 & 0.826 & 0.853 & 0.648 & \\ Sacrifice Organization & 0.800 & 0.626 & 0.460 & 0.802 & 0.721 & 0.766 & 0.731 & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Discriminant validity results based on the heterotrait-monotrait ratio of correlations (HTMT). Figure 3: Evaluation of Structural Model through PLS Bootstrapping. Bootstrapping strategies were embedded in this analysis with SmartPLS 3 to conclude whether the route coefficients are statistically important or not. The \(t\)-values with each path coefficient were calculated using the bootstrapping technique, as stated in Table 5 and the subsequently created \(p\)-values. [PERSON] et al. (2018) suggested looking at the confidence interval to provide additional facts about the degree to which the population parameter dropped at a certain level of confidence. When seen in Table 5, zero is not included in all confidence intervals. The results showed that H1, on-the-Job embeddedness was positively related to intention to stay in the construction companies in Malaysia with (\(\beta\) = 0.138, \(t\) = 2.291) and also H2, off-the-Job Embeddedness was positively related to intention to stay in Malaysian construction companies with (\(\beta\) = 0.352, \(t\) = 5.055). The result in Table 5 indicated that H3 continuance commitment was positively related to the intention to stay in Malaysia's construction companies. H4, of this study on-the-job embeddedness was positively related to continuance commitment in Malaysian construction companies and H5, off-the-Job Embeddedness was positively related to continuance commitment in Malaysian construction companies respectively (\(\beta\) = 0.399, \(t\) = 6.333), (\(\beta\) = 0.303, \(t\) = 4.924) and (\(\beta\) = 0.542, \(t\) = 9.911). Another vital assessment of a structural model is for mediation analysis, according to [PERSON] et al. (2018), determining the direct and indirect interactions between the exogenous and endogenous latent variable. By performing mediating or moderating examination, this direct and indirect interaction can be investigated. It only examined the importance of mediating relationships in this section. This is based on the theoretical rationale that continuance commitment as a mediating force that has influenced people to stay in construction firms. However, the findings of the \(t\)-tests in the structural model revealed that the PLS path had a significant indirect coefficient between on-the-job embedding, continuance commit