## 5 Evaluation
### Expert Assessment  
An evaluation of the proposed framework was conducted through an expert review aimed at addressing questions Q1 to Q22. The panel comprised both academic and industry professionals who met the following two main eligibility criteria: over 10 years of experience in the field, and proven expertise in Lean Construction, Building Information Modeling (BIM), and Emerging Technologies. A total of 20 experts were invited to contribute to the study, of whom 12 agreed to participate. Participants were presented with the framework's structure, components, and intended application for review and assessment with a 5-point Likert-scale questionnaire (1 = Strongly Disagree, 5 = Strongly Agree). Table 10 outlines the professional profiles of the participating experts. \begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt}} \hline \hline \multirow{2}{*}{**ID**} & \multicolumn{2}{c}{**SEQUAL Quality Dimension**} & \multirow{2}{*}{**Question**} \\ \hline Q9 & Semantic & The framework effectively addresses common industry challenges such as cost overruns, project delays, and inefficiencies. \\ Q10 & Pragmatic & The framework is too complex to be practically implemented in real-world projects. \\ Q11 & Pragmatic & The proposed BIM, Lean tools, and Emerging Technologies are appropriately selected for each construction phase. \\ Q12 & Pragmatic & The framework offers a structured approach to optimizing construction performance in terms of the selected KPIs: cost efficiency and savings, time efficiency and delivery, productivity and resource utilization, waste reduction, quality and safety, stakeholder satisfaction and collaboration and process optimization and automation. \\ Q13 & Social & The framework promotes collaboration and coordination between stakeholders (e.g., project managers, contractors, clients, designers...). \\ Q14 & Social & The framework facilitates better decision-making processes by ensuring transparent information flow. \\ Q15 & Social & The framework is not flexible enough to be applied across different construction project types (residential, infrastructure, industrial, etc.). \\ Q16 & Deontic & The framework aligns with the best international practices, industry regulations, and compliance standards for construction management, ensuring regulatory adherence. \\ Q17 & Deontic & The framework effectively identifies and mitigates project risks, uncertainties, and performance constraints, supporting proactive decision making. \\ Q18 & Deontic & The framework supports sustainable construction practices, ensuring lifecycle efficiency and reducing resource waste. \\ Q19 & Deontic & The integration of technologies within the framework enhances automation, digitalization, and real-time decision making in construction projects. \\ Q20 & Deontic & The framework is flexible and scalable, allowing for modifications and adjustments based on project size, complexity, and evolving technological trends. \\ Q21 & Deontic & The framework serves as a solid foundation for future research, enabling continued development in construction management. \\ \hline \hline \end{tabular}
\end{table} 
Table 9: _Cont._To enhance the representativeness of the results, the expert panel was purposefully selected to reflect a diverse distribution across professional roles, sectors, and geographies. Of the twelve experts, six are industry-based professionals, including directors, consultants, and Lean/BIM managers, while six are affiliated with academia, providing a balanced academic-industry perspective. The panel also reflects geographical diversity, with members from Europe (Spain, Germany, and Italy), the Middle East (Saudi Arabia), North America (USA), and South America (Chile). Professionally, the participants represent the architecture, civil engineering, construction management, and digital innovation domains, ensuring comprehensive expertise in Lean Construction, BIM, and Emerging Technologies. This multidisciplinary and multi-regional representation strengthens the external validity of the framework evaluation.