医疗保健行业供应链合同选择:不确定环境下的混合mcdm方法

IF 0.4 Q4 MANAGEMENT
I. Meidutė-Kavaliauskienė, Shahryar Ghorbani
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引用次数: 2

摘要

本研究的目的是利用逐步权重评估比率分析(SWARA)和基于区域的排名方法(EAMR)评估,解决基于关键成功因素(csf)选择供应链合同的方式和时间的批评。本研究通过EAMR对不确定环境下的供应链合同进行排名,例如在细分医疗保健行业时。这是通过为电信业的可持续创业提供理论框架来实现的,重点是根据生育医院专家确定的一套可持续发展战略,应修改的管理和业务做法。作为一种新颖的策略,本研究通过德尔菲法和EAMR提取定制供应链管理(SCM)选择的初始因素,并将需要初始权重的决策矩阵符号化,该决策矩阵是通过犹豫模糊数的SWARA方法获得的。在生育医院实现SCM合同选择的CSFs被发现依赖于基于有效性、透明度和问责制的三足鼎立,这些都嵌入在管理和操作实践的范围内,例如集中和降低成本,并且必须根据这些因素选择最佳SCM合同。此外,EAMR方法比其他类似的MCDM方法如TOPSIS、MOORA、VIKOR等具有更高的可靠性,本文的主要贡献是将SWARA与EAMR相结合,并在EAMR中使用犹豫模糊集
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
The aim of this research study is to address a critique of how and when a supply chain contract is selected based on critical success factors (CSFs) utilizing stepwise weight assessment ratio analysis (SWARA) and Evaluation by an Areabased Method of ranking (EAMR). This research study ranked supply chain contracts by the EAMR in uncertainty environments, such as when breaking down the health care industry. This is done by providing a theoretical framework for sustainable entrepreneurship in telecommunications industry, focusing on managerial and operational practices that should be modified, in accordance to a set of CSFs identified from experts in fertility hospital. As a novel strategy, in this research, the initial factors of selecting customized Supply Chain Management (SCM) were extracted via a Delphi method along with the EAMR to symbolize a decision matrix that needs primary weights acquired through the SWARA method by hesitant fuzzy number. CSFs for achieving SCM contract selection in fertility hospitals were found to rely on a tripod based on effectiveness, transparency, and accountability that are embedded within the ambit of managerial and operational practices, such as focusing and reducing cost and based on these factors the best SCM contract must be selected. Besides, the EAMR method has more reliability than other similar MCDM methods such as TOPSIS, MOORA, VIKOR, and so on main contribution of this paper is the combination of SWARA, EAMR, and using hesitant fuzzy set in the EAMR
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