TY - JOUR
T1 - A unified model of supply risk mitigation
AU - Al-Balushi, Zainab
AU - Durugbo, Christopher M.
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/3
Y1 - 2023/3
N2 - Supply risk (SR) pervades the structures and behaviour of supply networks (SNs) and the potential economic significance of deviant, disruptive, and disastrous incidents motivate significant investments by organisations in strategies for SR mitigation to lessen adverse organisational effects and vulnerability of SNs. Thus, a key challenge for researchers is to design analytical tools, techniques, and methodologies that enhance intelligence for SR mitigation. Guided by contingency theory, this study aims to propose a unified model for descriptively characterising the process for SR mitigation and assessing SR mitigation methodologies for SNs. A multi-case study conducted with four companies in petroleum and aluminium industry sectors, aids in evaluating the proposed model. Theoretically, the research is original in offering a formal approach for prescribing SR mitigation actions, and for formulating benchmarks that comparatively analyse the uncertainty level, perception scrutiny, and mechanism deployment of risk mitigation methodologies. Managerially, the research is valuable in shedding light on the significance of SN control mechanisms in SR management and a controllability–predictability continuum that elaborates on dimensions of potential incidents associated with SRs in SNs.
AB - Supply risk (SR) pervades the structures and behaviour of supply networks (SNs) and the potential economic significance of deviant, disruptive, and disastrous incidents motivate significant investments by organisations in strategies for SR mitigation to lessen adverse organisational effects and vulnerability of SNs. Thus, a key challenge for researchers is to design analytical tools, techniques, and methodologies that enhance intelligence for SR mitigation. Guided by contingency theory, this study aims to propose a unified model for descriptively characterising the process for SR mitigation and assessing SR mitigation methodologies for SNs. A multi-case study conducted with four companies in petroleum and aluminium industry sectors, aids in evaluating the proposed model. Theoretically, the research is original in offering a formal approach for prescribing SR mitigation actions, and for formulating benchmarks that comparatively analyse the uncertainty level, perception scrutiny, and mechanism deployment of risk mitigation methodologies. Managerially, the research is valuable in shedding light on the significance of SN control mechanisms in SR management and a controllability–predictability continuum that elaborates on dimensions of potential incidents associated with SRs in SNs.
KW - Risk mitigation
KW - Supply disruption
KW - Supply networks
KW - Supply risk
KW - Uncertainty
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U2 - 10.1016/j.cie.2023.109019
DO - 10.1016/j.cie.2023.109019
M3 - Article
AN - SCOPUS:85147193288
SN - 0360-8352
VL - 177
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
M1 - 109019
ER -