大型煤炭能源集团供应链运营现状、绩效评价与优化对策研究——以S集团为例 

摘要：煤炭是我国能源安全的 “压舱石”，其供应链的稳定与高效直接关系到能源保供水平与产业链整体成本。在 “双碳” 目标推进和煤炭市场价格宽幅波动的双重背景下，大型煤炭集团普遍面临采购、生产、物流、销售各环节协同不足、库存与资金占用偏高、物流成本刚性以及价格与安全风险叠加等突出问题，供应链韧性与运营效率亟待提升。本文以中部地区某特大型煤炭 — 能源 — 化工一体化国有企业集团（以下简称 “S 集团”）为案例对象，构建 “上游采购 — 中游洗选加工 — 下游销售配送 — 煤化工延伸” 四段式煤炭供应链分析框架；依据供应链运作参考模型（SCOR）与煤炭行业运营特征，提炼可靠性、响应性、成本、资产利用、协同与风险六个维度、14 项二级指标的绩效评价体系，采用熵权法确定客观权重，对 2019—2024 年供应链运营进行综合评价，并辅以成本构成、库存周转、物流结构与煤价灵敏度分析开展问题诊断。受数据可得性限制，全部运营数据均为基于煤炭行业公开统计特征构造的仿真示例数据，仅用于方法演示。研究发现：采购成本占供应链总成本的 62.85%，运输成本占约 10.00% 且随公路运输占比呈刚性；库存周转天数均值 17.3 天、旺季升至 20.7 天，库存与资金占用高度正相关（相关系数 0.996）；六年综合绩效得分由 39.45 分升至 53.03 分，累计提升 34.4%，但协同（38.91 分）与风险抵御（31.86 分）两维持续偏低，构成核心短板；煤价下跌 20% 时供应链利润下滑 44.2%，经营杠杆约 2.21，抗价格波动能力不足。据此提出纵向协同、数字化平台、库存与物流优化、全面风险管理四条路径，测算八项关键指标平均可改善 15.1%，其中信息共享水平改善 22.1%。研究为大型煤炭集团在能源转型背景下提升供应链韧性与运营效率提供了可操作的分析框架与决策参考。

关键词：煤炭供应链；供应链绩效评价；熵权法；SCOR 模型；供应链优化；案例研究

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Supply Chain Operations, Performance Evaluation and Optimization of Large Coal-Energy Groups: A Case Study of Group S

Abstract：As the "ballast stone" of China's energy security, coal supply chains directly affect energy supply reliability and overall industrial-chain costs. Amid the "dual-carbon" transition and sharp coal-price fluctuations, large coal groups face weak cross-stage coordination, high inventory and capital occupation, rigid logistics costs, and compounded price and safety risks, leaving supply-chain resilience and efficiency in urgent need of improvement. Taking a large state-owned coal-energy-chemical integrated group in central China (hereinafter "Group S") as the case, this paper builds a four-stage analytical framework covering upstream procurement, midstream washing and processing, downstream sales and distribution, and coal-chemical extension. Guided by the Supply Chain Operations Reference model (SCOR) and industry operating characteristics, a performance evaluation system with six dimensions and 14 secondary indicators—reliability, responsiveness, cost, asset utilization, coordination and risk—is constructed, with objective weights derived by the entropy weight method to evaluate operations over 2019–2024. All operational data are simulated from publicly available industry characteristics for methodological demonstration only. The results show that procurement accounts for 62.85% of total supply-chain cost and transportation about 10.00% with strong rigidity; the average inventory turnover is 17.3 days, rising to 20.7 days in peak seasons, and inventory correlates strongly with capital occupation (r=0.996). The composite performance score rises from 39.45 to 53.03 (up 34.4%), yet coordination (38.91) and risk resistance (31.86) remain the weakest dimensions. A 20% coal-price drop cuts supply-chain profit by 44.2%, implying an operating leverage of about 2.21. Four optimization paths are proposed, expected to improve eight key indicators by 15.1% on average, with information sharing improving by 22.1%. The study offers an actionable framework and decision reference for enhancing the supply-chain resilience and efficiency of large coal groups.

Keywords: coal supply chain; supply chain performance evaluation; entropy weight method; SCOR model; supply chain optimization; case study

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