基于q-Rung正交概率犹豫模糊信息的决策技术在供应链融资中的应用

Shahzaib Ashraf, N. Rehman, Muhammad Naeem, Sumayya Gul, Bushra Batool, Shamsullah Zaland
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引用次数: 1

摘要

新冠肺炎疫情对个人、企业、企业的影响是不容置疑的。许多市场,特别是金融市场,受到严重冲击,遭受重大损失。供应链网络中出现了重大问题,特别是在融资方面。COVID-19的后果对供应链融资(SCF)产生了重大影响,供应链融资负责为供应链组成部分提供资金并改善供应链绩效。供应链融资的主要来源是金融提供者。在金融提供者中,银行部门被认为是主要的融资来源。银行运营系统的任何问题都可能对融资过程产生巨大影响。在本研究中,我们试图了解COVID-19疫情的主要后果,以及如何减轻COVID-19对巴基斯坦银行业的影响。为此,建立了由TOPSIS、VIKOR和Grey组成的三种扩展混合方法,以解决决策专家权重信息和准则未知的q阶正交概率犹豫模糊环境下供应链金融中的不确定性问题。研究分为三个部分。首先,利用qROPHF信息下的广义距离测度,建立了新的q阶正交概率犹豫模糊(qROPHF)熵测度,确定属性的未知权重信息;第二部分以算法的形式采用TOPSIS、VIKOR和GRA三种决策技术来处理qROPHF设置下的不确定信息。最后一部分是对巴基斯坦供应链金融的现实案例研究,分析COVID-19紧急情况对巴基斯坦银行的影响。因此,为了帮助政府,我们选择了最佳替代形式列表,考虑了五种替代方案(投资、政府支持、主张和品牌、渠道、数字和细分市场),并使用提出的算法将COVID-19对巴基斯坦银行供应链金融的影响降至最低。结果表明,本文提出的方法可以有效地解决决策挑战中数据模糊的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decision-Making Techniques Based on q-Rung Orthopair Probabilistic Hesitant Fuzzy Information: Application in Supply Chain Financing
The influence of COVID-19 on individuals, businesses, and corporations is indisputable. Many markets, particularly financial markets, have been severely shaken and have suffered significant losses. Significant issues have arisen in supply chain networks, particularly in terms of financing. The COVID-19 consequences had a significant effect on supply chain financing (SCF), which is responsible for finance supply chain components and improved supply chain performance. The primary source of supply chain financing is financial providers. Among financial providers, the banking sector is referred to as the primary source of financing. Any hiccup in the banking operational systems can have a massive influence on the financing process. In this study, we attempted to comprehend the key consequences of the COVID-19 epidemic and how to mitigate COVID-19’s impact on Pakistan’s banking industry. For this, three extended hybrid approaches which consists of TOPSIS, VIKOR, and Grey are established to address the uncertainty in supply chain finance under q-rung orthopair probabilistic hesitant fuzzy environment with unknown weight information of decision-making experts as well as the criteria. The study is split into three parts. First, the novel q-rung orthopair probabilistic hesitant fuzzy (qROPHF) entropy measure is established using generalized distance measure under qROPHF information to determine the unknown weights information of the attributes. The second part consists of three decision-making techniques (TOPSIS, VIKOR, and GRA) in the form of algorithm to tackle the uncertain information under qROPHF settings. Last part consists of a real-life case study of supply chain finance in Pakistan to analyze the effects of emergency situation of COVID-19 on Pakistani banks. Therefore, to help the government, we chose the best alternative form list of consider five alternatives (investment, government support, propositions and brands, channels, and digital and markets segments) by using proposed algorithm that minimize the effect of COVID-19 on supply chain finance of Pakistani banks. The results indicate that the proposed techniques are applicable and effective to cope with ambiguous data in decision-making challenges.
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