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A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management
Mini Dissertation (MBA)--University of Pretoria, 2025.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2026
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| _version_ | 1867613500166111232 |
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| access_status_str | Open Access |
| author2 | Wolf-Piggott, Brendon Bernard |
| author_browse | Wolf-Piggott, Brendon Bernard |
| author_facet | Wolf-Piggott, Brendon Bernard |
| collection | Thesis |
| dc_rights_str_mv | © 2025 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Mini Dissertation (MBA)--University of Pretoria, 2025. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/109146 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:08.061Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/109146 A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management Wolf-Piggott, Brendon Bernard ichelp@gibs.co.za Hooblal, Diajal UCTD Artificial intelligence Supply chain risk management Downstream oil and gas Socio-technical systems Organisational readiness Digital transformation Data quality Cultural resistance Alignment AI adoption Mini Dissertation (MBA)--University of Pretoria, 2025. The downstream oil and gas supply chain industry is becoming more and more vulnerable to unplanned disruptions that have already proven to threaten efficiency, resilience and continuity. While artificial intelligence has surfaced as a promising tool that can enhance operations through predictive analytics and data-driven decision-making support, the implementation within downstream oil and gas supply chains has been underwhelming. The Socio-Technical System theory guides this qualitative study as it explores how organisational readiness and socio-technical alignment can be leveraged to achieve effective AI integration in downstream SCRM. Semi-structured interviews were performed with 12 individuals who occupy relevant roles in supply, trading, risk management and digital operations in the industry. The thematic analysis reveals three interconnected themes that represent factors that need to be improved for an organisation to achieve operational readiness. These factors include barriers to AI adoption, operational inefficiencies and cultural and general tensions. A further four themes emerge as invaluable enabling factors that can be leveraged to assist with achieving socio-technical alignment. These include organisational foundations, workforce capability and engagement, alignment strategies and leadership as a driver. Ultimately, this research culminates in a conceptual framework that converges organisational readiness with socio-technical alignment to provide a roadmap for downstream O&G SC organisations and leaders to use as a guide to achieve adaptive AI-enabled SCRM. Gordon Institute of Business Science (GIBS) MBA Unrestricted Gordon Institute of Business Science (GIBS) SDG-09: Industry, innovation and infrastructure 2026-03-23T09:15:55Z 2026-03-23T09:15:55Z 2026-05-05 2025 Mini Dissertation * A2025 http://hdl.handle.net/2263/109146 en © 2025 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Artificial intelligence Supply chain risk management Downstream oil and gas Socio-technical systems Organisational readiness Digital transformation Data quality Cultural resistance Alignment AI adoption A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management |
| title | A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management |
| title_full | A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management |
| title_fullStr | A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management |
| title_full_unstemmed | A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management |
| title_short | A qualitative study on the influence of organisational readiness and socio-technical alignment of AI integration within the downstream oil and gas supply chain risk management |
| title_sort | qualitative study on the influence of organisational readiness and socio technical alignment of ai integration within the downstream oil and gas supply chain risk management |
| topic | UCTD Artificial intelligence Supply chain risk management Downstream oil and gas Socio-technical systems Organisational readiness Digital transformation Data quality Cultural resistance Alignment AI adoption |
| url | http://hdl.handle.net/2263/109146 |