# Dynamic BIM Adoption Impact on Contract Cost Variance Factors Using PLS-SEM Techniques
## 5 Conclusions  
This paper delves into examining how adopting BIM impacts the factors of CCV over time. The methodology consists of three consequential steps to achieve the paper's aim. The first step was to develop the causal model based partially on the data obtained by Alsugair (2022) and historical data of 94 projects using PLS-SEM; the essential CCV factors with their interdependencies were listed. The second step was to establish an annual rate of BIM adoption in KSA and identify the factors that BIM influenced. The questionnaire was distributed to the BIM experts. The third step was to determine the relative importance of CCV-caused groups over time based on the results of the first and second steps. The main findings revealed that Project Characteristics directly influence Contract Cost Variance and an indirect effect through Contractual Procedures. Additionally, External Factors, Contractual Procedures, and Estimator Performance directly impact Contract Cost Variance during the bidding stage. On the other hand, Information Quality indirectly affects Contract Cost Variance during the bidding stage through its impact on Estimator Performance. BIM influences improving IQ, CP, and EP. The PC has significant factors and is not influenced by BIM. The PC will decrease with time and reach 15.00%, 11.45%, and 9.47% in 2023, 2030, and 2037, respectively. The EP will record the first rank of the group factors on the CCV, while the IQ and CP will be the second and third of the group factors on the CCV, respectively. It is expected that the importance of the factors of these groups will increase with time. The relative weights of CP, EP, and IQ in 2023 are 22.9%, 25.15%, and 21.65%, respectively, and they will increase to 24.12%, 28.34%, and 24.38%, respectively, in 2030. In addition, the relative weight of these groups for 2037 is 24.59%, 30.25%, and 26.03%, respectively, in 2037. The CP, EP, and EF have directly influenced CCV. However, the PC and IQ indirectly impact the CCV through CP and EP. For this study's limitations, the study mentions using data from 94 projects and a survey conducted in 2022. The reliance on prior survey data may introduce biases or outdated information. Regarding the temporal scope, this study projects the impact of BIM adoption until 2037. Long-term projections may face uncertainties due to changing technology landscapes and industry dynamics. This study's results provide a framework for the interdependencies of factors that change with time. In addition, the results assist stakeholders in the construction industry in increasing the accuracy of the contract cost by capturing the most CCV factors. Conceptualization, K.S.A.-G., N.M.A. and H.F.A. ; Data curation, A.M.A. ; Formal analysis, N.M.A. ; Funding acquisition, K.S.A.-G., A.M.A. and S.I.A. ; Investigation, S.I.A. ; Methodology, K.S.A.-G., N.M.A. and H.F.A. ; Project administration, K.S.A.-G., A.M.A. and S.I.A. ; Resources, K.S.A  
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