Vol.73, No.2, 2022, pp.4003-4015, doi:10.32604/cmc.2022.030209
Fuzzy MCDM for Improving the Performance of Agricultural Supply Chain
  • Le Thi Diem My1, Chia-Nan Wang1, Nguyen Van Thanh2,*
1 Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan
2 Faculty of Commerce, Van Lang University, Ho Chi Minh City, Vietnam
* Corresponding Author: Nguyen Van Thanh. Email:
Received 21 March 2022; Accepted 07 May 2022; Issue published 16 June 2022
Fertilizer industry in Vietnam and globally have entered the saturation phase. With the growth rate slowing down, this poses challenges for the development impetus of the fertilizer industry in the next period. In fact, over the past few decades, Vietnam’s crop industry has abused excessive investment in chemical fertilizers, with organic fertilizers are rarely used or not at all, limiting crop productivity, increasing pests and diseases. To develop sustainable agriculture, Vietnam’s crop industry must limit the use of chemical fertilizers, increase the use of environmentally friendly organic and natural mineral fertilizers to produce clean agricultural products which is safe. Therefore, it is necessary to consider and choose the right supplier to ensure the goal of sustainable development. Spherical Fuzzy Analytic Hierarchy Process (SF-AHP), and the combinative distance-based assessment (CODAS) are new Multicriteria Decision Making (MCDM) method which can be used to solve supplier selection problem. This paper uses an effective solution based on a combined the concept of triple bottom line (TBL), SF-AHP and CODAS approach to help agriculture companies that need to select the best fertilizer supplier. This research can support supply chain managers to achieve supply chain systems that reduce not only sourcing costs, but also develop sustainable agriculture.
Fuzzy theory; MCDM model; fertilizer; agricultural supply chain; optimization
Cite This Article
L. Thi Diem My, C. Wang and N. Van Thanh, "Fuzzy mcdm for improving the performance of agricultural supply chain," Computers, Materials & Continua, vol. 73, no.2, pp. 4003–4015, 2022.
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