An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chain
The oil and gas industry, with numerous supply chain partners, significantly contributes to the world economy. This industry's operations involve complex processes and interactions with different stakeholders, leading to many drivers contributing to its complexity. This study identifies sevente...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Supply Chain Analytics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949863525000044 |
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| author | Sujan Piya Yahya Al-Hinai Nasr Al Hinai Mohammad Khadem Mohammad Shamsuzzaman |
| author_facet | Sujan Piya Yahya Al-Hinai Nasr Al Hinai Mohammad Khadem Mohammad Shamsuzzaman |
| author_sort | Sujan Piya |
| collection | DOAJ |
| description | The oil and gas industry, with numerous supply chain partners, significantly contributes to the world economy. This industry's operations involve complex processes and interactions with different stakeholders, leading to many drivers contributing to its complexity. This study identifies seventeen complexity drivers in the oil and gas supply chain based on an extensive literature review and the Pareto principle. The identified drivers were then analyzed using an integrated Analytical Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approaches. The analysis reveals that the procurement system is the most important driver, followed by process synchronization among supply chain partners. Government regulation is the least influential driver in creating complexity in the oil and gas supply chain. Further analysis indicated that seven of the seventeen identified drivers were classified as causes, while the remaining ones fell under the effect group. The results of this study are expected to help decision-makers devise strategies based on the drivers with significant impact to minimize complexity and mitigate its effects on the oil and gas industry supply chain. |
| format | Article |
| id | doaj-art-e3777064dfa64a139dcb87e6e72f9f7b |
| institution | OA Journals |
| issn | 2949-8635 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Supply Chain Analytics |
| spelling | doaj-art-e3777064dfa64a139dcb87e6e72f9f7b2025-08-20T02:37:39ZengElsevierSupply Chain Analytics2949-86352025-06-011010010410.1016/j.sca.2025.100104An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chainSujan Piya0Yahya Al-Hinai1Nasr Al Hinai2Mohammad Khadem3Mohammad Shamsuzzaman4Department of Industrial Engineering and Engineering Management, College of Engineering, University of Sharjah, UAE; Corresponding author.Petroleum Development Oman, OmanDepartment of Mechanical and Industrial Engineering, College of Engineering, Sultan Qaboos University, OmanDepartment of Industrial Engineering and Engineering Management, College of Engineering, University of Sharjah, UAEDepartment of Industrial Engineering and Engineering Management, College of Engineering, University of Sharjah, UAEThe oil and gas industry, with numerous supply chain partners, significantly contributes to the world economy. This industry's operations involve complex processes and interactions with different stakeholders, leading to many drivers contributing to its complexity. This study identifies seventeen complexity drivers in the oil and gas supply chain based on an extensive literature review and the Pareto principle. The identified drivers were then analyzed using an integrated Analytical Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approaches. The analysis reveals that the procurement system is the most important driver, followed by process synchronization among supply chain partners. Government regulation is the least influential driver in creating complexity in the oil and gas supply chain. Further analysis indicated that seven of the seventeen identified drivers were classified as causes, while the remaining ones fell under the effect group. The results of this study are expected to help decision-makers devise strategies based on the drivers with significant impact to minimize complexity and mitigate its effects on the oil and gas industry supply chain.http://www.sciencedirect.com/science/article/pii/S2949863525000044Multi-criteria-decision makingOil and Gas IndustrySupply Chain ComplexityComplexity DriverAnalytical Hierarchy ProcessDecision-Making Trial and Evaluation Laboratory |
| spellingShingle | Sujan Piya Yahya Al-Hinai Nasr Al Hinai Mohammad Khadem Mohammad Shamsuzzaman An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chain Supply Chain Analytics Multi-criteria-decision making Oil and Gas Industry Supply Chain Complexity Complexity Driver Analytical Hierarchy Process Decision-Making Trial and Evaluation Laboratory |
| title | An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chain |
| title_full | An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chain |
| title_fullStr | An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chain |
| title_full_unstemmed | An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chain |
| title_short | An integrated multi-criteria decision-making model for identifying complexity drivers in the oil and gas supply chain |
| title_sort | integrated multi criteria decision making model for identifying complexity drivers in the oil and gas supply chain |
| topic | Multi-criteria-decision making Oil and Gas Industry Supply Chain Complexity Complexity Driver Analytical Hierarchy Process Decision-Making Trial and Evaluation Laboratory |
| url | http://www.sciencedirect.com/science/article/pii/S2949863525000044 |
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