scholarly journals Retraction notice to ‘Corrigendum to “A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain”’ [Future Gener. Comput. Syst. (2019) 1076–1077]

2021 ◽  
Vol 120 ◽  
pp. 127
Author(s):  
Mohamed Abdel-Basset
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Retraction Notice

scholarly journals Retraction notice to “Risk-assessment of photovoltaic-wind-battery-grid based large industrial consumer using information gap decision theory” [Sol. Energy 169 (2018) 343–352]

Solar Energy ◽  
2021 ◽  
Vol 217 ◽  
pp. 399
Author(s):  
Hamid Asadi Bagal ◽  
Yashar Nouri Soltanabad ◽  
Milad Dadjuo ◽  
Karzan Wakil ◽  
Noradin Ghadimi
Keyword(s):  
Risk Assessment ◽  
Decision Theory ◽  
Information Gap ◽  
Retraction Notice ◽  
Grid Based

Supply Chain Risk Assessment Using Fuzzy Logic

2021 ◽  
Author(s):  
Abdelrahman Ibrahim Mostafa ◽  
Abdelrahman Mostafa Rashed ◽  
Yasmin Ashraf Alsherif ◽  
Yomna Nagah Enien ◽  
Menatalla Kaoud ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Supply Chain ◽  
Supply Chain Risk

Benchmarking the risk assessment in green supply chain using fuzzy approach to FMEA

2018 ◽  
Vol 25 (8) ◽  
pp. 2660-2687 ◽  
Author(s):  
Sachin Kumar Mangla ◽  
Sunil Luthra ◽  
Suresh Jakhar
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Failure Mode ◽  
Failure Modes ◽  
Research Work ◽  
Evaluation Framework ◽  
Green Supply Chain ◽  
Content Type ◽  
Efficient Management ◽  
Fmea Analysis

PurposeThe purpose of this paper is to facilitate green supply chain (GSC) managers and planners to model and access GSC risks and probable failures. This paper proposes to use the fuzzy failure mode and effects analysis (FMEA) approach for assessing the risks associated with GSC for benchmarking the performance in terms of effective GSC management adoption and sustainable production.Design/methodology/approachInitially, different failure modes are defined using FMEA analysis, and in order to decide the risk priority, the risk priority number (RPN) is determined. Such priority numbers are typically acquired from the judgment decisions of experts that could contain the element of vagueness and imperfection due to human biases, and it may lead to inaccuracy in the process of risk assessment in GSC. In this study, fuzzy logic is applied to conventional FMEA to overcome the issues in assigning RPNs. A plastic manufacturer GSC case exemplar of the proposed model is illustrated to present the authenticity of this method of risk assessment.FindingsResults indicate that the failure modes, given as improper green operating procedure, i.e. process, operations, etc. (R6), and green issues while closing the loop of GSC (R14) hold the highest RPN and FRPN scores in classical as well as fuzzy FMEA analysis.Originality/valueThe present research work attempts to propose an evaluation framework for risk assessment in GSC. This paper explores both sustainable developments and risks related to efficient management of GSC initiatives in a plastic industry supply chain context. From a managerial perspective, suggestions are also provided with respect to each failure mode.

scholarly journals Risk Evaluation and Control of Supply Chain Finance

2018 ◽  
Vol 6 (1) ◽  
pp. 21
Author(s):  
Ying Yu Du ◽  
Jun Bin Zhong ◽  
Zi Yue Su ◽  
Xin Peng Yang ◽  
Yi Lan Yao
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Key Factors ◽  
Supply Chain Risk ◽  
Analytic Hierarchy ◽  
Industry Chain ◽  
Supply Chain Finance ◽  
Financial Index ◽  
And Control ◽  
Hierarchy Process

As an effective way of enterprises financing, supply chain finance has attracted much attention in recent years. However, since supply chain finance has some problems like long financing period, numerous stakeholders and complex effects, banks are at a higher risk carrying out this kind of service. The purpose of this paper is to explore the key factors in supply chain finance risk assessment and study the effective mode of risk elevation. Based on the existing literature and research, this paper uses Z-score to standardize the financial index of 344 medium-sized enterprises in automotive industry chain from October, 2016 to October, 2017 and build a model of supply chain risk assessment and control basing on analytic hierarchy process, principal components analysis and logistic regression analysis. Finally, we summarize how each index affects risk assessment and then analyze the reasons.

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