可持续和弹性供应链网络设计的范围回顾和文献计量学分析

Supply Chain Analytics Pub Date : 2025-09-08 DOI:10.1016/j.sca.2025.100162

Rahmi Yuniarti , Suparno , Niniet Indah Arvitrida

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引用次数: 0

摘要

在不断加剧的环境压力、市场波动、流行病破坏以及地缘政治不确定性（如贸易战、资源民族主义和地区冲突）的背景下，设计可持续和有弹性的供应链网络（SRSCND）已成为战略重点。本研究采用混合文献计量学-范围审查（ScoRBA）与PAGER框架相结合，系统地绘制和综合了2015年至2025年间发表的528篇同行评议文章。该分析确定了五个主题集群：(1)可持续决策的数字化；(2)低碳供应链的能源和环境优先事项；(3)不确定性下的弹性和战略规划；(4)价值导向和数据驱动的逆向供应链；(5)绿色闭环系统的启发式优化。跨集群洞察强调，最具创新性的解决方案出现在这些主题的交叉点上，例如，将数字决策支持系统与实时网络重构的自适应启发式优化相结合；将循环经济战略与弹性规划相结合，创建低碳但可应对破坏的系统；将可追溯性基础设施与闭环网络中的价值恢复优化相结合。虽然概念成熟度已经建立，但操作成熟度仍然有限：大多数研究依赖于理论建模、模拟或孤立的案例研究，很少有特定部门的实际应用。社会和行为维度、治理集成和多部门中断建模仍未得到充分探索。未来的研究应优先考虑将试点项目扩展到多部门的工业实施中，将社会、文化和行为因素嵌入定量模型中，并开发整合环境、经济和社会目标的自适应实时决策系统。在复杂的全球风险时代，加强产学研合作、改善开放数据获取和利用数字孪生技术，对于加速从理论进步向可扩展、以实践为导向的解决方案的转变，对于构建可持续和有弹性的供应链至关重要。

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A scoping review and bibliometric analysis of sustainable and resilient supply chain network design

Designing sustainable and resilient supply chain networks (SRSCND) has become a strategic priority amid intensifying environmental pressures, market volatility, pandemic disruptions, and geopolitical uncertainties such as trade wars, resource nationalism, and regional conflicts. This study employs a hybrid bibliometric–scoping review (ScoRBA) combined with the PAGER framework to systematically map and synthesize 528 peer-reviewed articles published between 2015 and 2025. The analysis identifies five thematic clusters: (1) digitalization for sustainable decision-making, (2) energy and environmental priorities in low-carbon supply chains, (3) resilience and strategic planning under uncertainty, (4) value-oriented and data-driven reverse supply chains, and (5) heuristic optimization in green and closed-loop systems. Cross-cluster insights highlight that the most innovative solutions emerge at the intersections of these themes—for example, integrating digital decision-support systems with adaptive heuristic optimization for real-time network reconfiguration; coupling circular economy strategies with resilience planning to create low-carbon yet disruption-ready systems; and combining traceability infrastructures with value-recovery optimization in closed-loop networks. Although conceptual maturity is well established, operational maturity remains limited: most studies rely on theoretical modeling, simulation, or isolated case studies, with few sector-specific real-world applications. Social and behavioral dimensions, governance integration, and multi-sector disruption modeling remain underexplored. Future research should prioritize scaling pilot projects into multi-sector industrial implementations, embedding social, cultural, and behavioral factors into quantitative models, and developing adaptive real-time decision systems that integrate environmental, economic, and social objectives. Strengthening industry–academia collaboration, improving open-data access, and leveraging digital twin technologies will be critical to accelerate the transition from theoretical advances to scalable, practice-oriented solutions for building sustainable and resilient supply chains in an era of complex global risks.

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Supply Chain Analytics

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