Assessing the Impact of AI on Operational and Supply-Chain Decision-Making: Evidence from Companies in the Kingdom of Saudi Arabia (KSA)
| dc.contributor.advisor | Tahirov, Nail | |
| dc.contributor.author | Shalhoob, Huda Shafiq | |
| dc.date.accessioned | 2025-12-02T22:07:37Z | |
| dc.date.issued | 2025 | |
| dc.description | This master’s thesis was submitted to Durham University in partial fulfillment of the requirements for the Master of Science (MSc) in Management (Supply Chain Logistics). The research provides an empirical examination of the influence of Artificial Intelligence (AI) on operational and supply-chain decision-making within enterprises operating in the Kingdom of Saudi Arabia (KSA). Employing a rigorous mixed-methods design, the study integrates qualitative insights derived from semi-structured interviews with quantitative evidence obtained through a structured survey. The thesis contributes to the academic discourse on AI-driven organizational transformation by identifying the enablers, challenges, and performance implications associated with AI adoption in supply-chain contexts. | |
| dc.description.abstract | This study investigates the impact of Artificial Intelligence (AI) on flexible and responsive supply chain decision-making within Saudi Arabian enterprises. Using a mixed-methods approach, the research incorporates qualitative insights from seven semi-structured interviews and quantitative data from 96 survey respondents. The findings show that AI enhances supply chain flexibility and responsiveness; however, challenges remain related to strategic integration, cultural readiness, and financial accountability. Although AI adoption in Saudi enterprises is still at an early stage, it has significant potential to transform decision-making, improve agility, and strengthen competitiveness in global markets. The study highlights that current AI integration is fragmented and uneven, suggesting that further research is needed to explore sector-specific adoption patterns and long-term financial impacts, as well as the cultural and leadership barriers influencing AI-enabled supply chain transformation. | |
| dc.format.extent | 77 | |
| dc.identifier.citation | Shalhoob, Huda Shafiq (2025). Assessing the Impact of AI on Operational and Supply-Chain Decision-Making: Evidence from Companies in the Kingdom of Saudi Arabia (KSA). Durham University. | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14154/77308 | |
| dc.language.iso | en | |
| dc.publisher | Saudi Digital Library | |
| dc.subject | Supply Chain | |
| dc.subject | SMEs | |
| dc.subject | Saudi Arabia | |
| dc.subject | Operations Management | |
| dc.subject | Global Operation | |
| dc.subject | SML enterprises | |
| dc.subject | Flexibility | |
| dc.subject | Decision-Making | |
| dc.title | Assessing the Impact of AI on Operational and Supply-Chain Decision-Making: Evidence from Companies in the Kingdom of Saudi Arabia (KSA) | |
| dc.type | Thesis | |
| sdl.degree.department | Management and Marketing | |
| sdl.degree.discipline | Supply Chain Logistics | |
| sdl.degree.grantor | Durham University | |
| sdl.degree.name | MSc Management |
