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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Supply Chain Analytics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949863525000044 |
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| Summary: | 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. |
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| ISSN: | 2949-8635 |