Performance measurement of construction suppliers under localization, agility, and digitalization criteria: Fuzzy...

The suppliers' performance plays a vital role, with a domino effect, in project success, organizational competitiveness, protecting supply chain and construction industry from disruptions and PESTEL risks (political, economic, social, technological, environmental, and legal). Therefore, measuring the performance of the construction suppliers has become the primary focus of project-oriented organizations and the core of business decision-making, especially during global megatrends. The question that may arise here is, "How can the performance of the construction suppliers be determined under uncertainties considering the post-COVID-19 era?" Organizations need eligible suppliers for the rapid recovery of the supply chain and construction sector at this critical stage. Given the importance of the issue, this study aims to propose a novel approach for measuring the performance of construction suppliers using the fuzzy ordinal priority approach (OPA-F). OPA-F is a recent development in multiple criteria decision-making (MCDM) that can determine the criteria weights for performance measurement using fuzzy linguistic variables. We do not always have access to a complete data set in real-world situations and business environments. Nevertheless, OPA-F can handle this dilemma, even with incomplete input data. This research intends to consider three main aspects of the construction suppliers, known as (L-A-D) capabilities, including localization, agility, and digitalization. In this regard, we bring up a case study from the construction industry to demonstrate the application of the proposed framework. The findings show that the most critical criterion is "digitalization" for the case study. This criterion covers "supply chain automation" and "virtualization and dematerialization" of services/products. The proposed approach is practical and straightforward, particularly for academicians and decision-makers; it can also incorporate uncertainties.