2 research outputs found
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Assessment Of Disruption Risk In Supply Chain The Case Of Nigeria’s Oil Industry
evaluate disruption risks in the supply chain of petroleum production. This methodology is developed to formalise and facilitate the systematic integration and implementation of various models; such as analytical hierarchy process (AHP) and partial least squares structural equation model (PLS-SEM) and various statistical tests. The methodology is validated with the case of Nigeria’s oil industry.
The study revealed the need to provide a responsive approach to managing the influence of geopolitical risk factors affecting supply chain in the petroleum production industry. However, the exploration and production risk, and geopolitical risk were identified as concomitant risk factors that impact performance in Nigeria’s oil industry. The research findings show that behavioural-based mechanisms successfully predict the ability of the petroleum industry to manage supply chain risks. The significant implication for this study is that the current theoretical debate on the supply chain risk management creates the understanding of agency theory as a governing mechanism for supply chain risk in the Nigerian oil industry. The systematic approach results provide an insight and objective information for decisions-making in resolving disruption risk to the petroleum supply chain in Nigeria. Furthermore, this study highlights to stakeholders on how to develop supply chain risk management strategies for mitigating and building resilience in the supply chain in the Nigerian oil industry.
The developed systematic method is associated with supply chain risk management and performance measure. The approach facilitates an effective way for the stakeholders to plan according to their risk mitigation strategies. This will consistently help the stakeholders to evaluate supply chain risk and respond to disruptions in supply chain. This capability will allow for efficient management of supply chain and provide the organization with quicker response to customer needs, continuity of supply, lower costs of operations and improve return on investment in the Nigeria oil industry. Therefore, the methodology applied provide a new way for implementing good practice for managing disruption risk in supply chain. Further, the systematic approach provides a simplistic modelling process for disruption risk evaluation for researchers and oil industry professionals. This approach would develop a holistic procedure for monitoring and controlling disruption risk in supply chains practices in Nigeria
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Decision-making model for supply chain risk management in the petroleum industry
YesThe 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.The full-text of this article will be released for public view at the end of the publisher embargo, 12 months from first publication date