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Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach
Author(s) -
Mahmoudi Amin,
Deng Xiaopeng,
Javed Saad Ahmed,
Zhang Na
Publication year - 2021
Publication title -
business strategy and the environment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.123
H-Index - 105
eISSN - 1099-0836
pISSN - 0964-4733
DOI - 10.1002/bse.2623
Subject(s) - topsis , analytic hierarchy process , multiple criteria decision analysis , sustainability , grey relational analysis , selection (genetic algorithm) , ideal solution , computer science , profitability index , flexibility (engineering) , pairwise comparison , operations research , function (biology) , management science , business , economics , mathematics , artificial intelligence , ecology , physics , management , mathematical economics , finance , evolutionary biology , biology , thermodynamics
Abstract Due to mounting environmental and social challenges, supplier selection has become one of the most critical tasks of project‐oriented organizations. Because supplier selection can affect the long‐term success and profitability of the organizations and their projects, directly, embracing sustainability can add value in the equation. Considering sustainability measures can positively guide project managers in making better decisions for the projects in the long term. Therefore, the current study attempts to provide a conceptual model for selecting the best supplier based on a sustainability framework in megaprojects. Meanwhile, decision‐making methods can be employed as a proper tool to find the best supplier. Ordinal priority approach (OPA) is a recent development in multiple criteria decision making (MCDM), while it has many benefits compared with other methods like analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). However, this method cannot consider multiple ranks during the decision‐making process, and using an uncertainty approach feels strongly. Grey systems theory (GST) can consider uncertainties with no need for large sample or proposing membership function. Hence, the current study employed the GST to consider multiple ranks for criteria and alternatives in the OPA method. This is the first time that a sustainable supplier selection framework has been presented for megaprojects with the aid of the Grey OPA (OPA‐G) method. Finally, a case study has been examined to evaluate the performance of the proposed approach. The results show that the proposed approach can be used in real‐world situations and it has acceptable performance under uncertainty conditions.