The coefficients of the criteria-weight.

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。全球咖啡豆产业当前面临多重挑战：新冠疫情对其供应链（Supply Chain, SC）造成的长期冲击、主要咖啡产区遭遇极端天气、价格波动加剧以及运输成本持续上涨。约旦高度依赖咖啡进口——咖啡作为一类关键农产品，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现状，并通过缩短交付提前期与降低运输成本，优化其咖啡供应链的运营绩效。本研究首先结合模糊层次分析法（Fuzzy Analytic Hierarchy Process, FAHP）与模糊理想解法（Fuzzy Technique for Order of Preference by Similarity to Ideal Solution, TOPSIS）两种方法，基于既定评价标准对供应商进行排序并筛选最优供应商。随后，本研究提出采用离散事件仿真（Discrete Event Simulation, DES）方法开展分析，以提升约旦咖啡供应链的运营效率。本研究采用真实企业的运营数据，对所提出的研究方法进行实证研究、应用与效果评估。本研究的决策流程纳入决策者与专家意见作为输入依据，从而实现对供应商的全面且均衡的评价。本研究基于模糊多准则决策（Fuzzy Multi-Criteria Decision Making, FMCDM）结果与仿真模型的集成，对多种不同场景进行评估与对比。研究结果明确了最优与表现最差的供应商，并指出埃塞俄比亚在多项评价指标中占据领先地位。研究结论提出可通过缩短交付提前期、降低运输成本、加大技术投入以及培育持续改进文化，来提升供应链的运营效率与稳定性，以更好地适配市场环境变化。本研究对约旦咖啡供应链的当前现状开展了全面分析，并提出了相应的发展优化路径。最后，本文针对约旦咖啡供应链的现存问题提出改进建议，并展望了未来的研究方向。