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Deng H, Zhang A. Fuzzy hierarchy analytic method of enterprise supply chain financial risk. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-189840] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Supply chain finance refers to one or more companies upstream and downstream of the industrial supply chain. According to the core company of each node, based on actual transactions, use customized and standardized financing transaction methods to control capital flows or control assets. The right to provide comprehensive financial products and services between supply chain nodes. This article only needs to introduce the financial risk analysis of the enterprise supply chain based on the fuzzy analytic hierarchy process. This paper proposes a fuzzy analytic hierarchy process, which uses a combination of qualitative and quantitative risk assessment methods to assess financial risks, and designs a financial risk assessment system by constructing a fuzzy judgment matrix. It also proposes a comprehensive judgment of the financial risk assessment method. The impact of various risk factors on financial services provides a basis for risk prevention. The experimental results of this paper show that the fuzzy analytic hierarchy process evaluation method is relatively objective and can effectively evaluate the financial risks of the enterprise supply chain. From the weight analysis, it can be concluded that the technical risk weight value is 0.47, which accounts for the largest proportion and is the most important risk.
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Affiliation(s)
- Huali Deng
- School of Finance and Economics, Guangzhou Panyu Polytechnic, Guangzhou, Guangdong, China
| | - Aoduo Zhang
- School of Computer Science and Engineering, The University of New South Wales, Sydney 2020, New South Wales, Australia
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Rehman SU, Chen Z, Raza M, Wang P, Zhang Q. Person re-identification post-rank optimization via hypergraph-based learning. Neurocomputing 2018. [DOI: 10.1016/j.neucom.2018.01.086] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Raza M, Chen Z, Ur Rehman S, Wang P, Wang JK. Framework for estimating distance and dimension attributes of pedestrians in real-time environments using monocular camera. Neurocomputing 2018. [DOI: 10.1016/j.neucom.2017.08.052] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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