Sustainable supplier selection for prefabricated megaprojects during COVID-19: a novel large group decision-making model

Prefabrication in construction has broad development prospects owing to its sustainability and strong support from the government. Prefabricated components, as the primary part of prefabrication megaprojects, affect the project completion and performance directly. Therefore, selecting appropriate prefabricated component sustainable suppliers (PCSSs) is a paramount task for the success of prefabricated megaprojects. This study expounds on the characteristics of PCSS selection from three aspects, namely the difference between prefabricated and traditional ones, sustainability requirements, and the impact of COVID-19, and indicates the issues that should be considered when choosing PCSS. An evaluation criterion is extracted and applied to the primary data from 4 PCSSs and 45 decision makers (DMs) of a prefabricated megaproject. Finally, a novel intuitionistic fuzzy large-group decision-making model is proposed. This model considers criterion weights and DM weights, as well as hesitation, ambiguity and consistency. The results indicate that the proposed model has strong robustness and can meet the decision-making needs of different DMs. The model extends the body of knowledge in the context of supply chain disruptions and digital bidding during the COVID-19 pandemic based on its more comprehensive criteria for the PCSS selection and new approaches for the weighting and uncertain evaluation throughout the decision-making process.

Automated summary

Prefabrication in construction has a promising future due to its sustainability and government support. Selecting the right sustainable suppliers for prefabricated components is crucial for the success of such projects. This study explores the characteristics of supplier selection, considering differences from traditional components, sustainability requirements, and the impact of COVID-19. A novel decision-making model is proposed, incorporating criteria weights, decision maker weights, and factors such as hesitation and ambiguity. The model proves robust and adaptable to different decision makers, contributing to the understanding of supply chain disruptions and digital bidding during the pandemic.