The final ranking of five suppliers.

Coffee is one of the drinks that are consumed worldwide. The global coffee beans industry is currently facing several challenges, including The COVID19 pandemic’s long-term effects on their supply chains (SCs), adverse weather conditions affecting major coffee-producing regions, escalating price dynamics, and the increased in transportation costs. Jordan significantly relies on coffee imports, a critical agricultural product that constitutes an important part of local trade. Due to the lack of previous studies, the research aims to evaluate the current SC and improve Jordan’s coffee SC performance by reducing lead time and shipping cost. The research first uses the combined Fuzzy Analytic Hierarchy Process (FAHP) and The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the supplier and choose the best suppliers based on established criteria. Then, the research proposes an analysis with the goal of enhancing the efficiency of Jordan’s coffee SC by applying Discrete Event Simulation (DES). Real company data is utilized to study, apply and evaluate the methodology used. The decision-making process employ decision makers and expert opinion input, providing a comprehensive and balanced evaluation of suppliers. Different scenarios are evaluated and compared based on the integrations of the FMCDM results in the simulation model. The findings identify the best and least favorable suppliers, highlighting Ethiopia’s leadership in several indicators. The outcomes suggest reducing lead time and shipping costs, investing in technology, and establishing a culture of continuous improvement to improve efficiency, stability, and adapt to market conditions. The research provides a comprehensive analysis of the current state of the coffee SC and suggests opportunities for development. Finally, recommendations to improve the current coffee SC in Jordan and directions for future research are discussed.咖啡是全球消费规模最大的饮品之一。当前全球咖啡豆产业面临多重挑战：新冠疫情大流行对其供应链（Supply Chain，SC）造成的长期冲击、主要咖啡产区遭遇的恶劣天气、价格波动持续加剧以及运输成本不断攀升。约旦高度依赖咖啡进口，而咖啡作为关键农产品，是当地贸易的重要组成部分。鉴于此前相关研究的匮乏，本研究旨在评估约旦当前的咖啡供应链，并通过缩短前置时间与运输成本，提升其咖啡供应链的绩效。本研究首先结合模糊层次分析法（Fuzzy Analytic Hierarchy Process，FAHP）与模糊理想解相似排序法（Fuzzy Technique for Order of Preference by Similarity to Ideal Solution，TOPSIS）对供应商进行排序，并基于既定评选标准选出最优供应商；随后，本研究提出采用离散事件仿真（Discrete Event Simulation，DES）开展分析，以优化约旦咖啡供应链的运行效率。研究利用真实企业数据对所提出的方法论进行验证、应用与评估。决策流程吸纳了决策者与专家的意见输入，实现了对供应商的全面且均衡的评估。研究将模糊多准则决策（Fuzzy Multiple Criteria Decision Making，FMCDM）的结果整合至仿真模型中，对多种场景开展评估与对比。研究结果明确了表现最优与最差的供应商，凸显出埃塞俄比亚在多项指标上的领先地位。研究结论建议通过缩短前置时间与运输成本、加大技术投入以及培育持续改进的文化，以提升供应链的效率与稳定性，更好地适配市场环境变化。本研究对约旦当前咖啡供应链的现状进行了全面剖析，并提出了相应的发展机遇。最后，本文讨论了改善约旦当前咖啡供应链的具体建议，以及未来的研究方向。