Decision-making model for supply chain risk management in the petroleum industry
Publication date
2020Rights
(c) 2020 InderScience Publishers. Full-text reproduced in accordance with the publisher's self-archiving policy.Peer-Reviewed
YesOpen Access status
openAccess
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Show full item recordAbstract
The purpose of this paper is to develop a decision-making model for supporting the management of risks in supply chain. This proposed model is applied to the case of the oil industry in Nigeria. A Partial Least Square Structural Equation Model (PLS-SEM) is developed to measure the significance of the influence of risk management strategy on mitigating disruption risks and their correlations with the performance of activities in the supply chain and relevance of key performance measures in the organisation. The model considered seven aspects: behavioural-based management strategy, buffer based oriented management strategy, exploration and production risks, environmental and regulatory compliance risks, geopolitical risks, supply chain performance, and organisational performance measures. A survey questionnaire was applied to collect data to populate the model, with 187 participants from the oil industry. Based on the PLS-SEM methodology, an optimised risk management decision-making method was developed and accomplished. The results show that behavioural-based mechanism predicts the capacity of the organisation to manage risks successfully in its supply chain. The approach proposed provides a new and practical methodology to manage disruption risks in supply chains. Further, the behavioural-based mechanism can help to formulate risk management strategies in the oil industry.Version
Accepted manuscriptCitation
Aroge OO, Rahmanian N, Munive-Hernandez JE et al (2020) Decision Making Model for Supply Chain Risk Management in Petroleum Industry. International Journal of Decision Sciences, Risk and Management. Accepted for publication.Link to Version of Record
https://doi.org/10.1504/IJDSRM.2020.10034972Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1504/IJDSRM.2020.10034972