Multi-Criteria Decision-Making Methods in Fuzzy Decision Problems: A Case Study in the Frozen Shrimp Industry

Tiến sĩNguyễn Văn ThànhThạc sĩNguyễn Viết TịnhChia-Nan Wang, Jui-Chung Kao, Chih-Cheng Chen

Khoa Thương Mại

Thể loại: Bài báo

Sơ lược nội dung

The European Union (EU) is the largest shrimp consumer market in the world in terms of requirements for shrimp product imports. Therefore, other enterprises that export frozen shrimp to the EU must consider many criteria when choosing suppliers of raw shrimp. The difficulty of choosing suppliers of raw shrimp makes selecting raw material suppliers in the fisheries sector a multi-criteria decision-making problem. In such problems, the decision makers must review and evaluate many criteria—including qualitative and quantitative factors—to achieve an optimal result. While there have been multiple multi-criteria decision making models developed to support supplier selection processes in different industries, none of these have been developed to solve the particular problems facing the shrimp industry, especially as it concerns a fuzzy decision-making environment. In this research, the authors propose a Multi-Criteria Decision Making model (MCDM) including the Fuzzy Analytical Network Process (FANP) and Weighted Aggregated Sum Product Assessment (WASPAS) for the evaluation and selection process of shrimp suppliers in the fisheries industry. The model is applied to a real-world case study and the results show that Supplier 3 (SA3) is the most optimal supplier of raw shrimp. The contribution of this work is the employment of FANP and WASPAS to propose an MCDM for ranking potential suppliers in the fisheries industry in a fuzzy environment. The proposed approach can also be modified to support complex decision-making processes in fuzzy environments in different industries.

Thông tin chung
Thể loại
Bài báo
Năm xuất bản
25 Thg2 2021
Ngôn ngữ gốc
Tiếng Anh
Tạp chí công bố
Symmetry
Ấn phẩm số
Vol. 13 No. 3
Loại tạp chí
Danh mục ISI
Mã ISSN
2073-8994
Trang
370
Chất lượng
Q2

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