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| References | Methodology | Strategy | Research focus | Industry |
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| [4] | Hybrid fuzzy and data-driven robust optimization | Vendor-managed inventory | Supply inventory management | Health care |
| [5] | A systematic literature review | Three resilience dimensions analysis | Measurement of supply chain resilience | — |
| [6] | Partial least squares-based structural equation modelling | Three dimensions analysis | Scale of supply chain resilience | Global supply chains |
| [7] | Total interpretive structural modelling | Test the proposed methodology | Driving factors of supply chain resilience | COVID-19 |
| [8] | AHP and fuzzy | Consider the drivers of the resilience and vulnerability | Driving factors of supply chain resilience | E-commerce |
| [9] | Quality function deployment | Identify the major risks and vulnerability factors | Improving supply chain resilience | Agricultural food |
| [10] | Fuzzy cognitive maps | Analyze the domino effect | Driving factors of supply chain resilience | Fashion |
| [11] | Evaluation of extraction and processing parameters | Discuss mineral economic implications relevant to coltan supply | Mineral economic implications related to the supply chain | Tantalum |
| [12] | — | Provide a holistic complex system governance | Supply chain resilience assessment | Oil and gas |
| [14] | GIS remote sensing technology | Builds a resource reserve management information system | Mineral resource reserve system | Mineral resources |
| [15] | — | Analyze many ways to increase the scale of reserves | Mineral resource reserve scale | Copper |
| [16] | Reserves assessment and resource optimization | Discovery of resource rich areas | Optimal reserve | Oil and gas |
| [17] | — | Estimate future ore reserves and energy consumption | Optimal reserve | Copper ore |
| Present study | SD | Analysis of supply chain resilience by simulating mineral resource reserves | Supply chain resilience | Mineral resources |
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