Supply Chain Analytics最新文献_第5页

A systematic review of food accessibility in the food supply chains 对食品供应链中食品可及性的系统审查

Supply Chain Analytics

Pub Date : 2025-07-20 DOI: 10.1016/j.sca.2025.100149

Bochi Liu , Mengfei Chen , Mohamed Kharbeche , Laoucine Kerbache , Mohamed Haouari , Xi Gu , Wenyuan Wang , Weihong Guo Grace

Food accessibility, covering physical, economic, and social dimensions, is a core pillar of food security and depends strongly on food supply chains (FSCs). Previous reviews usually examined FSCs without discussing accessibility, or discussed accessibility outside the FSC context. We close that gap by making the first systematic review that explicitly links the two topics. We screened 136 studies and conducted bibliometric-performance and science-mapping analyses to identify research topics and trends. We synthesized diverse definitions and measurements of food accessibility, analyzed barriers affecting food accessibility, and established a three-tier taxonomy that maps specific barriers onto the three dimensions of food accessibility and five barrier classes. For each barrier class, we traced the causal chain and summarized the interventions reported in the literature. A brief comparison between sub-Saharan Africa and Western Europe shows that barriers and interventions vary by region. Based on these findings, we present a decision matrix that links barriers to actionable interventions and analytical tools. The review identifies three research gaps: (1) multidimensional measurement of accessibility, (2) stronger attention to equity, and (3) wider use of analytics-driven decision support tools. These insights offer strategic guidance for future research and practice aimed at enhancing food accessibility through FSC innovations.

粮食可及性涵盖物质、经济和社会层面，是粮食安全的核心支柱，在很大程度上取决于粮食供应链。以前的审查通常检查FSC而不讨论可访问性，或者在FSC上下文之外讨论可访问性。我们通过首次明确地将这两个主题联系起来的系统回顾来缩小这一差距。我们筛选了136项研究，并进行了文献计量学绩效和科学制图分析，以确定研究主题和趋势。我们综合了食物可及性的不同定义和测量方法，分析了影响食物可及性的障碍，并建立了一个三层分类法，将特定的障碍映射到食物可及性的三个维度和五个障碍类别。对于每一类障碍，我们追溯了因果链，并总结了文献中报道的干预措施。对撒哈拉以南非洲和西欧的简要比较表明，障碍和干预措施因区域而异。基于这些发现，我们提出了一个决策矩阵，将障碍与可操作的干预措施和分析工具联系起来。该综述指出了三个研究缺口：(1)可及性的多维测量；(2)对公平的更大关注；(3)更广泛地使用分析驱动的决策支持工具。这些见解为未来的研究和实践提供了战略指导，旨在通过FSC创新提高粮食可及性。

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引用次数: 0

A causal artificial intelligence model for payment delay optimisation in supply chain financing 供应链融资中支付延迟优化的因果人工智能模型

Supply Chain Analytics

Pub Date : 2025-07-19 DOI: 10.1016/j.sca.2025.100138

Lingxuan Kong , Alexandra Brintrup

Supply chain financing (SCF) has become a popular approach for small- and medium-sized enterprises (SMEs) to improve financial resilience. Payment delays within SCF have emerged as a critical operational challenge for both suppliers and SCF providers. This paper aims to integrates causal AI modelling to proposed a framework to discover and optimise the operational treatments for mitigating payment delays in SCF. The proposed framework combines causal machine learning methods such as backdoor adjustment with Inverse Probability Weighting (IPW), and Double Machine Learning models (DoubleML). The proposed causal AI framework implements data-driven learning for the processes of causal discovery, causal effect estimation, and the optimisation of policy trees. This proposed framework aims to establish a cohesive method designed to identify potential treatment effects and assist in making operational decisions to mitigate payment delays. The effectiveness of the proposed framework is demonstrated through a case study on aerospace supply chain network. The generalisability and the industrial insights associated with the case study results have been analysed.

供应链融资（SCF）已成为中小企业（SMEs）提高财务弹性的一种流行方法。SCF内的付款延迟已成为供应商和SCF提供商面临的关键运营挑战。本文旨在整合因果人工智能模型，提出一个框架，以发现和优化减轻SCF支付延迟的操作处理。提出的框架结合了因果机器学习方法，如后门调整与逆概率加权（IPW）和双机器学习模型（DoubleML）。提出的因果AI框架实现了数据驱动的学习，用于因果发现、因果效应估计和策略树优化的过程。该框架旨在建立一种连贯的方法，旨在识别潜在的治疗效果，并协助制定业务决策，以减轻付款延迟。通过对航空航天供应链网络的实例研究，验证了该框架的有效性。分析了与案例研究结果相关的通用性和行业见解。

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引用次数: 0

An explainable decision model for selecting facility locations in supply chain networks 供应链网络中设施选址的可解释决策模型

Supply Chain Analytics

Pub Date : 2025-07-19 DOI: 10.1016/j.sca.2025.100148

Tin-Chih Toly Chen , Yu-Cheng Wang , Yi-Chi Wang

Suitable facility location selection for customer-required capacity localization is an emerging topic in semiconductor supply chain management. However, this topic has not been thoroughly investigated. For this reason, an explainable artificial intelligence (XAI)-interpreted fuzzy group decision-making (FGDM) approach is proposed in this study to assist a wafer foundry company in selecting suitable facility locations for customer-required capacity localization. The XAI-interpreted FGDM approach aims to overcome the shortcomings of existing visualization tools and techniques for explaining the facility location selection process. To this end, several new visualization tools and methods have been proposed, including hanging gradient bar charts, gradient bidirectional scatterplots, and hanging gradient bar charts for traceable aggregation. After applying the XAI-interpreted FGDM approach to a real case, the new XAI tools enhanced the explainability of the facility location selection process and results. The advantage over the existing XAI tools was up to 36 %. In addition, Shapley additive explanations (SHAP) analysis results showed that the factors that impact the assessment results most may be inconsistent with the original judgments of domain experts.

为满足客户需求而选择合适的工厂位置是半导体供应链管理中的一个新兴课题。然而，这个话题还没有得到彻底的研究。因此，本研究提出一种可解释的人工智能（XAI）解释模糊群体决策（FGDM）方法，以协助晶圆代工公司选择合适的工厂位置，以满足客户需求的产能本地化。xai解释的FGDM方法旨在克服现有可视化工具和技术在解释设施选址过程中的缺点。为此，提出了几种新的可视化工具和方法，包括悬挂梯度条形图、梯度双向散点图和用于可追溯聚合的悬挂梯度条形图。在将XAI解释的FGDM方法应用于实际案例后，新的XAI工具增强了设施选址过程和结果的可解释性。与现有的XAI工具相比，优势高达36% %。此外，Shapley加性解释（SHAP）分析结果表明，对评价结果影响最大的因素可能与领域专家的原始判断不一致。

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引用次数: 0

A stochastic programming approach to the location of distribution centers for multinational enterprises under demand uncertainty 需求不确定性下跨国企业配送中心选址的随机规划方法

Supply Chain Analytics

Pub Date : 2025-07-11 DOI: 10.1016/j.sca.2025.100147

Kuancheng Huang , Wei-Ting Chen , Yu-Ching Wu , Jan-Ren Chen

Multinational enterprises (MNEs) often collaborate with local agents to establish initial distribution channels due to their need for market-specific knowledge and experience. As the market matures and upstream suppliers and production plans are solidified, MNEs may transition to developing their distribution systems and supply chain networks. Integrating the transportation network among upstream material suppliers, production facilities, and distribution centers (DCs) becomes crucial at this stage. Since transportation costs constitute a significant portion of enterprise expenses, optimizing upstream transportation is essential for MNEs following this market entry strategy. This study aims to optimize the location decisions of DCs while assuming that suppliers, plants, and retailers have fixed locations. A critical focus is the integration of upstream transportation operations, specifically between suppliers and plants and between plants and DCs, to minimize inefficient empty backhauls. Additionally, demand uncertainty is factored into this long-term strategic design problem. A stochastic programming (SP) model is developed, and a solution procedure based on the Genetic Algorithm (GA) is designed to handle practical-scale problems. Numerical experiments demonstrate that the GA method achieves a solution quality with less than a 1 % gap compared to the optimal solution while also significantly reducing computation time.

跨国企业（MNEs）往往与当地代理商合作建立最初的分销渠道，因为他们需要特定市场的知识和经验。随着市场的成熟和上游供应商和生产计划的固化，跨国公司可能会转向发展他们的分销系统和供应链网络。在这个阶段，整合上游物料供应商、生产设施和配送中心（DCs）之间的运输网络变得至关重要。由于运输成本占企业费用的很大一部分，因此优化上游运输对于跨国公司遵循这种市场进入战略至关重要。本研究旨在优化配送中心的选址决策，同时假设供应商、工厂和零售商有固定的地点。一个关键的焦点是上游运输业务的整合，特别是供应商和工厂之间以及工厂和配送中心之间的整合，以最大限度地减少低效的空载。此外，需求的不确定性也被考虑到这个长期战略设计问题中。建立了随机规划（SP）模型，并设计了基于遗传算法（GA）的求解程序来处理实际问题。数值实验表明，该方法与最优解相比，求解质量差距小于1 %，同时显著减少了计算时间。

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引用次数: 0

An analytical exploration of barriers to resilient circular food supply chains using integrated structural methods 利用综合结构方法对弹性循环食品供应链的障碍进行分析探索

Supply Chain Analytics

Pub Date : 2025-07-09 DOI: 10.1016/j.sca.2025.100144

Emel Yontar

This study addresses the critical research problem of how to achieve resilience in food supply chains transitioning from linear to circular models. While circular food supply chains aim to enhance sustainability, reduce waste, and improve resource efficiency, they face complex systemic barriers that make resilience a challenging goal. To explore these barriers, the research adopts a hybrid methodological framework combining Interpretive Structural Modeling (ISM), MICMAC analysis (Cross-Impact Matrix Multiplication Applied to Classification), and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. This integrative approach enables the identification and classification of key obstacles based on their hierarchical structure and interdependence. The findings reveal that legal uncertainties and lack of incentives, financial difficulties, and technological immaturity are the most influential root barriers undermining Circular Economy-oriented Food Supply Chain Resilience (FSCR). These insights provide a structured understanding of the cause-effect relationships between challenges, offering practical guidance for policymakers, practitioners, and researchers seeking to build resilient and circular food supply chains amid increasing global disruptions.

本研究解决了如何在食品供应链从线性模型向循环模型过渡中实现弹性的关键研究问题。虽然循环食品供应链旨在提高可持续性、减少浪费和提高资源效率，但它们面临复杂的系统性障碍，使恢复力成为一项具有挑战性的目标。为了探索这些障碍，本研究采用了一种混合方法框架，结合了解释结构建模（ISM）、MICMAC分析（交叉影响矩阵乘法应用于分类）和决策试验与评估实验室（DEMATEL）方法。这种综合方法能够根据其层次结构和相互依存关系确定和分类主要障碍。研究结果表明，法律的不确定性和缺乏激励、资金困难和技术不成熟是影响循环经济导向的食品供应链弹性（FSCR）的最重要的根源障碍。这些见解提供了对挑战之间因果关系的结构化理解，为政策制定者、从业者和研究人员在日益严重的全球破坏中寻求建立有弹性和循环的食品供应链提供了实用指导。

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引用次数: 0

An optimization framework for sustainable closed-loop supply chains with green investment and recovery policy 具有绿色投资和回收政策的可持续闭环供应链优化框架

Supply Chain Analytics

Pub Date : 2025-07-08 DOI: 10.1016/j.sca.2025.100146

Wakhid Ahmad Jauhari , Dhea Naomi Kenlaksita , Nughthoh Arfawi Kurdhi , Dana Marsetiya Utama

Sustainability in closed-loop supply chains (CLSCs) is becoming a significant focus due to increasing environmental pressures and carbon regulations. While numerous studies have examined aspects such as carbon emissions, green technology, and the quality of used products, gaps remain in integrating these elements, particularly concerning the influence of collection quality on emissions, various recovery policies, and contract-based coordination mechanisms for sharing green technology investments. This study aims to develop a comprehensive supply chain model by integrating these factors through three main mechanisms: centralized coordination, decentralized, and green technology revenue investment sharing (GRIS) contracts. The model employs a mathematical formulation that considers green technology investment, collection rate, the quality of used products, and carbon emissions. Simulations were conducted with sensitivity analysis to evaluate the impact of parameters such as carbon tax, selling price sensitivity coefficient, green technology investment, and collection effort on system performance. Results indicate that the centralized coordination model excels in maximizing total profit and operational stability when compared to the decentralized model. However, it is more sensitive to changes in parameters. GRIS contracts offer flexibility in profit redistribution between producers and retailers without compromising the system efficiency. The findings also indicate that investments in green technology and collection efforts significantly contribute to enhanced collection quality and reduced carbon emissions, with more pronounced effects in the centralized model. This research offers a comprehensive approach to tackling sustainability challenges in CLSC, providing practical insights for industry stakeholders and policymakers in developing strategies that promote both economic and environmental sustainability.

由于日益增长的环境压力和碳法规，闭环供应链（CLSCs）的可持续性正成为一个重要的焦点。虽然有许多研究考察了碳排放、绿色技术和废旧产品质量等方面，但在整合这些要素方面仍然存在差距，特别是在收集质量对排放的影响、各种回收政策和共享绿色技术投资的基于合同的协调机制方面。本研究旨在通过集中式协调、分散式协调和绿色技术收益投资共享（GRIS）合同三种主要机制，整合这些因素，建立一个综合供应链模型。该模型采用了一个数学公式，考虑了绿色技术投资、收集率、废旧产品质量和碳排放。采用敏感性分析方法，对碳税、销售价格敏感性系数、绿色技术投资和征收力度等参数对系统性能的影响进行了仿真分析。结果表明，集中式协调模式在总利润最大化和运行稳定性方面优于分散式协调模式。然而，它对参数的变化更为敏感。GRIS合同在不影响系统效率的情况下，为生产者和零售商之间的利润再分配提供了灵活性。研究结果还表明，对绿色技术和收集工作的投资显著有助于提高收集质量和减少碳排放，其中集中式模式的效果更为明显。本研究为解决CLSC的可持续性挑战提供了一个全面的方法，为行业利益相关者和决策者制定促进经济和环境可持续性的战略提供了实用的见解。

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引用次数: 0

An analytical framework for optimizing supply chain operations with lean practices 用精益实践优化供应链操作的分析框架

Supply Chain Analytics

Pub Date : 2025-07-06 DOI: 10.1016/j.sca.2025.100145

Amber Batwara , Shailesh Kediya , Ravindra A. Kayande

Integrating lean principles into supply chain (SC) management has gained significant attention, but the emphasis on sustainability remains limited. This study addresses this gap by introducing a comprehensive Supply Chain Value Stream Mapping (SC-VSM) framework to enhance sustainability performance while maintaining operational efficiency. SC-VSM combines lean tools and techniques to streamline processes, reduce waste, and foster continuous improvement within a holistic supply chain system. A detailed literature review identifies key lean practices applicable to SC management, emphasizing the need for a strategic approach to align operational goals, build trust-based partnerships, and address technological uncertainties. The proposed SC-VSM framework is validated through a Fly Ash Brick Manufacturing Plant case study. The study evaluates the framework's effectiveness in optimizing processes, minimizing waste, and enhancing sustainability outcomes. The findings highlight SC-VSM's practical advantages in achieving sustainable supply chain goals, particularly for small and medium-sized enterprises. This research closes the theoretical and practical gap in lean SC management by providing a validated model that integrates sustainability into supply chain operations.

将精益原则整合到供应链（SC）管理中已经引起了极大的关注，但对可持续性的重视仍然有限。本研究通过引入全面的供应链价值流映射（SC-VSM）框架来解决这一差距，以提高可持续性绩效，同时保持运营效率。SC-VSM结合了精益工具和技术，以简化流程，减少浪费，并促进整体供应链系统的持续改进。详细的文献综述确定了适用于供应链管理的关键精益实践，强调需要一种战略方法来协调运营目标，建立基于信任的伙伴关系，并解决技术不确定性。提出的SC-VSM框架通过粉煤灰砖制造工厂的案例研究进行了验证。该研究评估了该框架在优化流程、减少浪费和提高可持续性成果方面的有效性。研究结果强调了SC-VSM在实现可持续供应链目标方面的实际优势，特别是对中小型企业而言。本研究通过提供一个将可持续性整合到供应链运营中的验证模型，缩小了精益供应链管理的理论和实践差距。

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引用次数: 0

An analytics-driven circular supply chain framework integrating quality, warranty, and human efficiency 一个分析驱动的循环供应链框架，集成了质量、保证和人力效率

Supply Chain Analytics

Pub Date : 2025-07-05 DOI: 10.1016/j.sca.2025.100140

Lalji Kumar, Uttam Kumar Khedlekar

This paper presents an advanced human-centric circular supply chain optimization framework that integrates economic, environmental, and behavioral dimensions into a unified multi-objective model. By jointly optimizing selling price, product quality, warranty duration, and production cycle time, the model captures the intricate trade-offs between profitability and sustainability-related penalties. A distinctive feature of the framework is the incorporation of a Human Efficiency Index and a circularity-based return function, enabling dynamic modeling of skill-driven waste minimization and quality-sensitive consumer behavior. The resulting nonlinear optimization problem is addressed using four powerful metaheuristic algorithms—Teaching-Learning-Based Optimization (TLBO), TLBO with Learning Rate, Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Multi-Objective Particle Swarm Optimization (MOPSO). Extensive numerical simulations demonstrate the efficacy of the TLBO-based methods in achieving high-profit, low-penalty solutions, while statistical analyses confirm their robustness and superiority through the Friedman test and the Wilcoxon signed-rank test. From a managerial perspective, the model offers critical insights for aligning operational decisions with sustainability-oriented goals by demonstrating the nonlinear effects of human efficiency and product lifecycle attributes on supply chain performance. From a policy standpoint, the findings advocate for institutional mechanisms that incentivize investment in skill development, recycling, and circularity-driven design practices. Furthermore, the social relevance of this work lies in its contribution to Industry 5.0 paradigms, where inclusive, sustainable, and human-empowered production systems are prioritized. This research thus provides a robust, actionable framework for decision-makers seeking to design resilient and circular supply chains that promote long-term economic value and social welfare.

本文提出了一个先进的以人为中心的循环供应链优化框架，将经济、环境和行为维度整合到一个统一的多目标模型中。通过共同优化销售价格、产品质量、保修期和生产周期，该模型捕获了盈利能力和可持续性相关惩罚之间的复杂权衡。该框架的一个显著特点是结合了人类效率指数和基于循环的回报函数，从而能够对技能驱动的废物最小化和对质量敏感的消费者行为进行动态建模。由此产生的非线性优化问题使用四种强大的元启发式算法-基于教学的优化（TLBO），具有学习率的TLBO，非支配排序遗传算法II （NSGA-II）和多目标粒子群优化（MOPSO）来解决。大量的数值模拟证明了基于tlbo的方法在实现高利润、低惩罚解决方案方面的有效性，而统计分析通过Friedman检验和Wilcoxon符号秩检验证实了它们的稳健性和优越性。从管理的角度来看，该模型通过展示人类效率和产品生命周期属性对供应链绩效的非线性影响，为将运营决策与面向可持续发展的目标相一致提供了关键的见解。从政策的角度来看，研究结果主张建立制度性机制，激励对技能开发、循环利用和循环驱动设计实践的投资。此外，这项工作的社会意义在于它对工业5.0范式的贡献，在工业5.0范式中，包容性、可持续性和以人为本的生产系统被优先考虑。因此，这项研究为决策者提供了一个强大的、可操作的框架，帮助他们设计有弹性的、循环的供应链，促进长期经济价值和社会福利。

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引用次数: 0

An EPQ-based optimization approach to variable-rate screening in supply chain production systems 基于epq的供应链生产系统可变率筛选优化方法

Supply Chain Analytics

Pub Date : 2025-07-05 DOI: 10.1016/j.sca.2025.100143

Amir Hossein Nobil , Erfan Nobil , Ericka Zulema Rodríguez Calvo , Mostafa Hajiaghaei-Keshteli

This study presents a comprehensive framework for optimizing the Economic Production Quantity (EPQ) with variable screening rates under two distinct inspection scenarios: Sufficient-Inspection-Rate (IRS) and Insufficient-Inspection-Rate (IRI). In the IRS scenario, the production system employs a high screening rate exceeding the production rate, enabling immediate inspection post-production to segregate imperfect and perfect items. Conversely, the IRI scenario features a slower screening rate relative to production, with inspection occurring post-production completion. The study incorporates inspection costs, and the percentage of imperfect items detected using decreasing exponential functions dependent on screening rate. A Sequential Quadratic Programming (SQP) approach is employed to solve both nonlinear models efficiently.

The analysis demonstrates that adopting a high screening rate (Model I) offers significant production efficiency and cost-effectiveness advantages. For instance, the total cost under the IRS scenario is approximately $394,522, which is notably lower than that of the IRI scenario. A comprehensive sensitivity analysis shows that holding cost, defect rate, and inspection parameters significantly influence both the production quantity and total cost, with the IRI scenario being more sensitive to these changes. These findings underscore the importance of selecting appropriate inspection strategies based on operational constraints and cost dynamics.

本文提出了在充分检验率（IRS）和不充分检验率（IRI）两种不同检验情景下，以可变筛选率优化经济生产数量（EPQ）的综合框架。在IRS场景中，生产系统采用了高于生产速度的高筛选率，可以在生产后立即进行检查，以区分不完美和完美的项目。相反，相对于生产，IRI方案的筛选率较慢，检查发生在生产完成后。该研究结合了检查成本，以及使用依赖于筛选率的递减指数函数检测到的不完美项目的百分比。采用序列二次规划（SQP）方法有效地求解了这两个非线性模型。分析表明，采用高筛分率（模型一）具有显著的生产效率和成本效益优势。例如，国税局方案下的总费用约为394 522美元，明显低于IRI方案。综合敏感性分析表明，持有成本、不良率和检验参数对生产数量和总成本都有显著影响，IRI场景对这些变化更为敏感。这些发现强调了根据操作限制和成本动态选择适当检查策略的重要性。

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引用次数: 0

A multi-objective analytical framework for sustainable blood supply chain optimization 可持续血液供应链优化的多目标分析框架

Supply Chain Analytics

Pub Date : 2025-06-27 DOI: 10.1016/j.sca.2025.100142

Agus Mansur , Taufiq Hidayat , Novrianty Rizky , Ivan Darma Wangsa

This study presents a multi-objective optimization model for blood supply chain (BSC) management, aiming to maximize total profit and fulfillment rate and minimize carbon emissions. The model is formulated as a mixed-integer linear program (MILP) and solved using the weighted sum method. The BSCM is structured as a multi-echelon network involving blood mobiles, local blood centers, regional blood banks (RBBs), hospitals, and healthcare facilities. Assumptions include deterministic demand and fixed blood shelf life. A case study in East Kalimantan, Indonesia, shows a total revenue of Indonesian Rupiah (IDR) of 13.07 billion and a total cost of IDR 8.58 billion, resulting in a profit of IDR 4.49 billion. The fulfillment rates for hospitals and healthcare facilities are 109.13 % and 154.57 %, respectively. Total emissions reach 203.94-kilogram CO₂ equivalent (kg CO₂e), mainly from production. Sensitivity analysis highlights the impact of demand, capacity, and pricing on supply chain performance. Furthermore, transshipment among RBBs plays a vital role in balancing inventory levels, though excessive transshipment may lead to increased costs and emissions.

提出了一种以利润最大化、履约率最大化、碳排放最小化为目标的血液供应链（BSC）管理多目标优化模型。该模型采用混合整数线性规划（MILP）形式，采用加权和法求解。BSCM的结构是一个多层次的网络，包括血液流动、地方血液中心、区域血库、医院和医疗机构。假设包括确定性需求和固定的血液保质期。印度尼西亚东加里曼丹的一个案例研究显示，总收入为130.7亿印尼盾，总成本为85.8亿印尼盾，利润为44.9亿印尼盾。医院和保健设施的履约率分别为109.13% %和154.57 %。总排放量达到203.94千克二氧化碳当量（kg CO2e），主要来自生产。敏感性分析强调需求、产能和定价对供应链绩效的影响。此外，rbb之间的转运在平衡库存水平方面起着至关重要的作用，尽管过度转运可能导致成本和排放增加。

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引用次数: 0