A hybrid group decision model for green supplier selection: a case study of megaprojects. Issue 8 (10th May 2019)

• Record Type: Journal Article
• Authors: Liang, Ru; Chong, Heap-Yih
• Is Part Of: Engineering, construction and architectural management. Volume 26:Issue 8(2019)
• Page Start: 1712
• Page End: 1734
• Publication Date: 2019-05-10
• Subjects: Case study -- Supply chain management -- Strategic management -- Decision support systems; Construction industry -- Management -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Periodicals; Building -- Periodicals; 624.068
• DOI: 10.1108/ECAM-10-2018-0462
• Languages: English
• ISSNs: 0969-9988

Abstract

Abstract : Purpose: Green supplier selection is one of the crucial activities in green supply chain management. However, limited studies have addressed the vagueness and complexities during the selection process, particularly in multi-criterion decision-making (MCDM) circumstances. Hence, the purpose of this paper is to develop a group decision model using a modified fuzzy MCDM approach for green supplier selection under a complex situation. Design/methodology/approach: The proposed study develops a framework for sorting decisions in green supplier selection by using the hesitant fuzzy qualitative flexible multiple attributes method (QUALIFLEX). The synthetic consistent or inconsistent indexes were used to calculate all alternative suppliers by normalizing the hesitant fuzzy decision matrix. Findings: The proposed framework has been successfully applied and illustrated in the case example of CB02 contract section in Hong Kong–Zhuhai–Macau Bridge project. The results show various complicated decision-making scenarios can be addressed through the proposed approach. The synthetic (in)consistent indexes are able to calculate all alternative suppliers by normalizing the hesitant fuzzy decision matrix. Originality/value: The research contributes to improving accuracy and reliability decision-making processes for green supplier selection, especially under vagueness and complex situations in megaprojects.