“…While VB-SEM forms the relationship among latent variables by illustrating the quantity of variance explained, CB-SEM explains the relationship between latent and observed variables and confirms the theoretical rationale determined by the model based on the covariance matrices. Due to distinct statistical advantages of CB-SEM over VB-SEM (Tripathi and Jha, 2018), CB-SEM has been successfully employed to investigate causal relationships in a variety of complex systems, for example, the effects of empowering leadership, directive leadership, and initiating structure on innovation (Hoang et al, 2019), the effect of firm age and size on profitability and productivity (Cyril and Singla, 2021), the effects of CSR on firm performance and innovation (Shih, 2022), delay in power transmission projects (Pall et al, 2022), risks assessment (Mohamed et al, 2022), and sustainable procurement (Messah et al, 2022). Therefore, the use of CB-SEM in this study is supported by its soundness and application.…”