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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.

The magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty, and risk of large-scale infrastructure projects. This fact made it increasingly tough to "go alone" into a contractor. As a consequence, joint venture contractors with diverse strengths and weaknesses cooperatively bid for bidding. Understanding project complexity and making decision on the optimal joint venture contractor is challenging. This paper is to study how to select joint venture contractors for undertaking large-scale infrastructure projects based on a multiattribute mathematical model. Two different methods are developed to solve the problem. One is based on ideal points and the other one is based on balanced ideal advantages. Both of the two methods consider individual difference in expert judgment and contractor attributes. A case study of Hong Kong-Zhuhai-Macao-Bridge (HZMB) project in China is used to demonstrate how to apply these two methods and their advantages.

Two kinds of evaluative criteria are associated with Public-Private Partnership (PPP) infrastructure projects, i.e., private evaluative criteria and public evaluative criteria. These evaluative criteria are inversely related, that is, the higher the public benefits; the lower the private surplus. To balance evaluative criteria in the Two-Sided Matching (TSM) decision, this paper develops a quantitative matching decision model to select an optimal matching scheme for PPP infrastructure projects based on the Hesitant Fuzzy Set (HFS) under unknown evaluative criterion weights. In the model, HFS is introduced to describe values of the evaluative criteria and multi-criterion information is fully considered given by groups. The optimal model is built and solved by maximizing the whole deviation of each criterion so that the evaluative criterion weights are determined objectively. Then, the match-degree of the two sides is calculated and a multi-objective optimization model is introduced to select an optimal matching scheme via a min-max approach. The results provide new insights and implications of the influence on evaluative criteria in the TSM decision.

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