## 5 Discussion  
This study's primary contribution lies in enhancing the database through a combination of empirical findings and surveys. These results were largely qualitative but complemented by quantitative techniques employed during the survey process. The vast amount of data collected through a well-structured questionnaire was then analyzed to identify key decision-making factors relevant to constructability assessments in infrastructure projects. This allowed the identification of critical data points and informed the development of a hybrid MCDA approach, which serves as a robust decision-making tool within the CRP at the feasibility stage of infrastructure projects.  
A significant innovation of this research is the introduction of a customizable Decision Support System for constructability analysis. This system is designed to accommodate various stakeholders' and clients' objectives, thus providing a tailored approach for addressing complex decision-making scenarios. The integration of CRP in the early project phases, specifically during feasibility, enables the identification and resolution of potential conflicts between criteria early in the project lifecycle, which is crucial for the long-term success of large infrastructure projects.  
In this study, a hybrid MCDA methodology was applied, incorporating well-established methods such as TOPSIS, SAW, COPRAS, PROMETHEE, CODAS, and VIKOR. These tools were used to rank alternatives and analyze the optimal outcomes. To effectively combine the results from multiple MCDA methods, the Borda Count method was employed to aggregate the rankings, thereby providing a more reliable and comprehensive decision-making framework. This multi-method approach is particularly advantageous as it mitigates the weaknesses of individual MCDA techniques while leveraging their strengths, resulting in a more balanced and robust solution.  
Figure 11: Comparison of individual MCDA tools result.  
The case study applied in this research adhered closely to the proposed methodology, illustrating how this comprehensive approach can be used to make informed decisions in complex project scenarios. By developing a customized decision matrix based on real project data, the study demonstrates the importance of adapting the decision-making framework to suit the specific conditions and objectives of each project. The flexibility of the DSS ensures that it can be tailored to exclude irrelevant factors or those with negligible influence on the decision-making process. This customization makes the DSS a valuable tool for guiding project managers in making well-informed decisions during the feasibility phase.  
The approach presented in this research provides a systematic framework for analyzing large-scale infrastructure projects with multiple alternatives and conflicting attributes. It is particularly useful in scenarios where uncertainties and unresolved variables present significant challenges. By integrating diverse MCDA tools and offering a comprehensive decision-making process, the proposed DSS can help project managers identify optimal solutions in the early stages of a project, thereby improving the efficiency and effectiveness of decision-making.  
Ultimately, the findings of this research will benefit both project managers and decision-makers by enabling them to prioritize, predict, and optimize their plans for infrastructure projects. Additionally, the broader engineering sector stands to benefit from this research, as it offers a valuable framework for evaluating alternatives in the feasibility stage, thus improving the project's performance during both construction and operational phases.