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Improving the performance of the coffee supply chain using integrating fuzzy MCDM and simulation methods
Ghazi M Magableh1, Abdullah F Al-Dwairi2, Ahmad Alhamouri2
1Industrial Engineering Department, Yarmouk University, Irbid, Jordan.
Plos One
|June 18, 2025
Summary
This study enhances Jordan
Area of Science:
- Supply Chain Management
- Operations Research
- Agricultural Economics
Background:
- Global coffee supply chains face challenges like pandemic disruptions, adverse weather, and rising costs.
- Jordan's economy heavily depends on coffee imports, highlighting the need for supply chain optimization.
- Limited prior research exists on Jordan's coffee supply chain performance.
Purpose of the Study:
- To evaluate Jordan's current coffee supply chain (SC).
- To improve coffee SC performance by reducing lead time and shipping costs.
- To identify optimal suppliers and enhance overall SC efficiency.
Main Methods:
- Combined Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for supplier evaluation.
- Discrete Event Simulation (DES) to analyze and enhance SC efficiency.
- Utilized real company data and expert decision-maker input.
Main Results:
- Identified key suppliers, with Ethiopia showing strong performance indicators.
- Demonstrated the potential to reduce lead time and shipping costs through proposed methods.
- Evaluated various scenarios to compare performance improvements.
Conclusions:
- The integrated FAHP-TOPSIS and DES methodology provides a robust framework for SC analysis.
- Recommendations include optimizing supplier selection, investing in technology, and fostering continuous improvement.
- The study offers actionable insights for enhancing Jordan's coffee SC stability and efficiency.
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