供应链
大流行
医疗保健
业务
2019年冠状病毒病(COVID-19)
冠状病毒
分布(数学)
风险分析(工程)
医学
营销
经济
疾病
传染病(医学专业)
经济增长
病理
数学分析
数学
作者
Omid Abdolazimi,Mitra Salehi Esfandarani,Maryam Salehi,Davood Shishebori,Majid Shakhsi–Niaei
出处
期刊:The International Journal of Logistics Management
[Emerald (MCB UP)]
日期:2021-10-29
卷期号:34 (2): 363-389
被引量:26
标识
DOI:10.1108/ijlm-04-2021-0232
摘要
Purpose This study evaluated the influence of the coronavirus pandemic on the healthcare and non-cold pharmaceutical care distribution supply chain. Design/methodology/approach The model involves four objective functions to minimize the total costs, environmental impacts, lead time and the probability of a healthcare provider being infected by a sick person was developed. An improved version of the augmented e-constraint method was applied to solve the proposed model for a case study of a distribution company to show the effectiveness of the proposed model. A sensitivity analysis was conducted to identify the sensitive parameters. Finally, two robust models were developed to overcome the innate uncertainty of sensitive parameters. Findings The result demonstrated a significant reduction in total costs, environmental impacts, lead time and probability of a healthcare worker being infected from a sick person by 40%, 30%, 75% and 54%, respectively, under the coronavirus pandemic compared to the normal condition. It should be noted that decreasing lead time and disease infection rate could reduce mortality and promote the model's effectiveness. Practical implications Implementing this model could assist the healthcare and pharmaceutical distributors to make more informed decisions to minimize the cost, lead time, environmental impacts and enhance their supply chain resiliency. Originality/value This study introduced an objective function to consider the coronavirus infection rates among the healthcare workers impacted by the pharmaceutical/healthcare products supply chain. This study considered both economic and environmental consequences caused by the coronavirus pandemic condition, which occurred on a significantly larger scale than past pandemic and epidemic crises.
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