一个评估服装、纺织和皮革行业可持续供应链创新风险的整体框架

Mohammad J Aladaileh , Eva Lahuerta-Otero
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引用次数: 0

摘要

本研究开发了一个整体框架,用于评估约旦服装、纺织和皮革(GTL)行业可持续供应链创新(SSCI)的风险,解决需求波动、客户集中和价格竞争带来的关键挑战。利用AHP和敏感性分析等多准则决策工具,研究将风险划分为高、中、低敏感性三类。高度敏感的风险,包括与需求相关的挑战,需要动态和自适应的策略,而中等敏感的风险,如供应商不匹配,则受益于增强的可见性和协作。低敏感性风险,如文化阻力和能源消耗,可以通过长期可持续性举措得到更好的管理。该研究的方法涉及六位专家的意见和系统分析,以确保SSCI风险的强大优先级。主要研究结果强调了针对特定风险敏感性定制风险缓解方法的必要性,为供应链管理人员提供了可操作的见解。该框架的独特之处在于将可持续性纳入风险优先级,提供了一种适用于类似行业的结构化方法。本研究通过在不断变化的情景中推进风险评估的决策理论,为SSCI文献做出了贡献。它强调了应对高敏感性风险的动态战略和应对低优先级风险的分阶段方法的重要性。未来的研究可以探索这一框架在全球供应链网络中的适用性,或通过人工智能等先进技术扩大其使用范围,以增强风险预测和管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A holistic framework for assessing risks in sustainable supply chain innovation in the garment, textile, and leather industry
This study develops a holistic framework for assessing risks in sustainable supply chain innovation (SSCI) within Jordan's garment, textile, and leather (GTL) industry, addressing critical challenges posed by demand volatility, customer concentration, and price competition. Using multi-criteria decision-making tools such as AHP and sensitivity analysis, the research prioritizes risks into high, moderate, and low sensitivity categories. Highly sensitive risks, including demand-related challenges, require dynamic and adaptive strategies, while moderately sensitive risks, like supplier mismatches, benefit from enhanced visibility and collaboration. Low-sensitivity risks, such as cultural resistance and energy consumption, are better managed through long-term sustainability initiatives.
The study's methodology involved input from six experts and systematic analyses to ensure robust prioritization of SSCI risks. Key findings highlight the necessity of tailoring risk mitigation approaches to specific risk sensitivities, offering actionable insights for supply chain managers. The framework is distinctive in integrating sustainability into risk prioritization, providing a structured approach adaptable across similar industries.
This research contributes to SSCI literature by advancing decision theory for risk evaluation in evolving scenarios. It underscores the importance of dynamic strategies for high-sensitivity risks and phased approaches for addressing lower-priority risks. Future research could explore the applicability of this framework in global supply chain networks or extend its use through advanced technologies like artificial intelligence for enhanced risk forecasting and management.
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CiteScore
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