A Framework for Subcontractor Selection in the Construction Industry

Abstract

The present condition of the construction industry imposes onerous responsibilities on contractors so they are very eager to subcontract some of their works. Subcontractors who directly handle a major portion of all construction activities have a highlighted role in the building industry, so suitable subcontractor selection has a direct effect on the productivity of construction operations. This paper aims to develop a comprehensive model for subcontractor selection based on the fuzzy preference selection index. The improvement of the proposed model lies in the fact that it has found a way to eliminate the weighting criteria phase in selecting the optimal subcontractor where weighting attributes is a challenging task. The consistency test is presented for investigating the accuracy of model results with the previous scientific work.

Subcontractor Selection Using the Integration of the Ahp and Promrthee Methods

“…Arslan et al (2008) developed a web-based subcontractor evaluation system (WEBSES) that enables main contractors to evaluate the subcontractors based on a combined criterion. Abbasianjahromi et al (2013) developed a comprehensive model for subcontractor selection based on the fuzzy preference selection index.…”

Supplier selection process in an integrated construction materials management model

“…A few methods, such as the FPSI method, have been developed to eliminate the weighting criteria through assigning relative importance of each (based on decision maker's opinions) [74].…”

Multi-criteria group decision-making using an extended edas method with interval type-2 fuzzy sets

“…Keshavarz Ghorabaee et al (2016b) extended the WASPAS method with IT2FSs and applied it to evaluation of green suppliers. Celik et al (2015) performed a comprehensive review of MCDM methods with interval type-2 fuzzy sets.…”

“…To handle the uncertainty of multi-criteria decision-making problems, the weights of criteria and the performance of alternatives are usually characterized by type-1 fuzzy sets that proposed by Zadeh (1965). Many researchers have studied the MCDM methods and problems in the type-1 fuzzy environment (Ecer, 2015;Karabasevic et al, 2016;Aliakbari Nouri et al, 2015;Li et al, 2015;Razavi Hajiagha et al, 2015). Mardani et al (2015) reviewed the MCDM methods and their applications in fuzzy environment.…”

“…Keshavarz Ghorabaee et al (2014) presented a new fuzzy ranking method and extended COPRAS (Complex Proportional Assessment) method in the context of IT2FSs to evaluate suppliers in a supply chain. Celik et al (2014) proposed an interval type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management. Balin and Baraçli (2015) developed a fuzzy MCDM methodology based on the IT2FSs for evaluating renewable energy alternatives in Turkey.…”