Establishing a decision-making model of global supply chain risk management from the perspective of risk and vulnerability

Author(s):  
Cheng Wen Lee
2018 ◽  
Vol 118 (7) ◽  
pp. 1528-1546 ◽  
Author(s):  
Muhammad Naveed Khan ◽  
Pervaiz Akhtar ◽  
Yasmin Merali

Purpose The purpose of this paper is to investigate the knowledge gaps in the published research on terrorism-related risk in supply chains, and to develop a framework of strategies and effective decision-making to enable practitioners to address terrorism-related risks in supply chain risk management (SCRM) and security. Design/methodology/approach The study adopts a novel combination of triangulated methods comprising a systematic literature review (SLR), text mining and network analysis. These methods have not been jointly utilized in past studies, and the approach constitutes a rigorous methodology that cross-validates results and ensures the reliability and validity of qualitative data. Findings The study reveals a number of key themes in the field of SCRM and security linked with terrorism. The authors identify relevant mitigation strategies and practices for effective strategic decision making. This subsequently leads us to develop a strategic framework of strategies and effective decision-making practices to address terrorism-related risk, affecting SCRM and security. The authors also identify key knowledge gaps in the literature and explore the main contributions by disciplines (e.g. business schools, engineering and maritime institutions) and countries. Practical implications The authors provide a strategic framework of strategies and effective decision-making practices that managers can use to minimize terrorism-related risk in the context of SCRM and security. Originality/value This paper introduces a novel methodological combination for improving the quality of SLRs. It uses the approach to systematically review the strategies and effective decision-making practices interlinked with terrorism risk, affecting SCRM and security. It identifies significant knowledge gaps and defines directions for future research.


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