In the construction industry, the optimal selection of contractors and suppliers of building materials plays a decisive role in the quality, cost, and time of project implementation. Decision-making in this area is usually accompanied by considering multiple indicators such as price, quality, reliability, work experience, and technical ability. The present study examines and integrates the application of the
Analytic Hierarchy Process (AHP) method as one of the powerful tools of multi-criteria decision-making in the process of selecting contractors and suppliers of building materials. By reviewing two international case studies in Taiwan and Indonesia and analyzing the approaches used in them, the strengths and weaknesses of the performance of this method in practical and industrial conditions have been evaluated. The results show that the use of the AHP model increases transparency, reduces the risk of inappropriate selection, and improves project quality control. This method also allows the integration of quantitative and subjective data and, by prioritizing indicators, makes project managers' decision-making more logical and systematic. Finally, suggestions are presented for more effective implementation of AHP in construction projects and development of indigenous models based on the conditions of the construction industry.In the construction industry, the optimal selection of contractors and suppliers of building materials plays a decisive role in the quality, cost, and time of project implementation. Decision-making in this area is usually accompanied by considering multiple indicators such as price, quality, reliability, work experience, and technical ability. The present study examines and integrates the application of the
Analytic Hierarchy Process (AHP) method as one of the powerful tools of multi-criteria decision-making in the process of selecting contractors and suppliers of building materials. By reviewing two international case studies in Taiwan and Indonesia and analyzing the approaches used in them, the strengths and weaknesses of the performance of this method in practical and industrial conditions have been evaluated. The results show that the use of the AHP model increases transparency, reduces the risk of inappropriate selection, and improves project quality control. This method also allows the integration of quantitative and subjective data and, by prioritizing indicators, makes project managers' decision-making more logical and systematic. Finally, suggestions are presented for more effective implementation of AHP in construction projects and development of indigenous models based on the conditions of the construction industry.
