Authors: Olatunde O. Aroge; Nejat Rahmanian; Jose Eduardo Munive-Hernandez; M. Reza Abdi
Addresses: Department of Chemical Engineering, Faculty of Engineering and Informatics, University of Bradford, BD7-1DP, UK ' Department of Chemical Engineering, Faculty of Engineering and Informatics, University of Bradford, BD7-1DP, UK ' Department of Mechanical Engineering, Faculty of Engineering and Informatics, University of Bradford, BD7-1DP, UK ' Department of Operation and Information Management, Faculty of Management and Law, University of Bradford, BD7-1DP, UK; Additive Design Ltd Broad Gate, The Headrow, Leeds, LS1-8EQ, UK
Abstract: The purpose of this paper is to develop a decision-making model for supporting the management of risks in supply chains. This proposed model is applied to the case of the oil industry in Nigeria. A partial least squares 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 the 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.
Keywords: risk management; supply chain risk; oil production industry; decision-making; PLS-SEM; Nigeria.
International Journal of Decision Sciences, Risk and Management, 2020 Vol.9 No.4, pp.223 - 240
Accepted: 30 May 2020
Published online: 31 Mar 2021 *