多准则决策分析
质量功能配置
弹性(材料科学)
风险分析(工程)
层次分析法
供应链
背景(考古学)
计算机科学
业务
供应链风险管理
模糊逻辑
脆弱性(计算)
供应链管理
过程管理
运筹学
营销
新产品开发
工程类
人工智能
古生物学
物理
热力学
服务管理
计算机安全
生物
作者
Obaid Ur Rehman,Yousaf Ali
标识
DOI:10.1108/ijlm-01-2021-0004
摘要
Purpose Resilience is a fundamental component of healthcare supply chains, as the quality and endurance of human life are dependent on them. However, there are numerous resilience-building measures, and there is a need for prioritization of those strategies. This research study aims to prioritize resilience strategies for healthcare supply chains while considering the risks that most severe, probable to occur and have the lengthiest periods of recovery. Design/methodology/approach This research study has used multi-criteria decision-making (MCDM) techniques for analysis. Initially, the criteria for prioritization of risks, i.e. severity, probability of occurrence and recovery time were assigned with importance weights through the fuzzy analytical hierarchy process (AHP). Then, these weights were used in the fuzzy technique for order preference by similarity to ideal solution (TOPIS) analysis for prioritization of risks. Subsequently, the identified risks were used for highlighting the appropriate resilience strategies through the fuzzy quality function deployment (QFD) technique. Findings Results indicate that Industry 4.0, multiple sourcing, risk awareness, agility and global diversification of suppliers, markets and operations are the most significant resilience strategies. Research limitations/implications This study's limitation is that it is conducted in a general perspective, rather than reducing the context to a developing or developed country. Different areas have variable market factors, due to which potential risks occur in a different form. Moreover, resilience strategies work differently in different environments. Therefore, for future endeavors, the studies should be carried out in a limited context. Originality/value This research study proposes a novel MCDM-based approach for ranking resilience strategies, in light of the most probable, severe and long-lasting risks. In addition, this approach has been employed for the enhancement of resilience in healthcare supply chains.
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