Abstract Date: 2023-05-30 Level: Master thesis in Business Administration, 15 cr Institution: School of Business, Society and Engineering, Mälardalen University Authors: Ramak Amyari Khamneh (84/01/29), Aymen Safi (00/03/27) Title: Artificial Intelligence as a Catalyst for Supply Chain Resilience: A Qualitative Study Comparing Scania and Volvo in the Construction Equipment Industry Supervisor: Emre Yildiz Keywords: Artificial Intelligence (AI), Supply Chain Resilience, Construction Equipment Industry, Disruptions, Agility, Redundancy Research question: How do Scania and Volvo interpret and implement Artificial Intelligence (AI) technologies to enhance supply chain resilience and mitigate disruptions in the construction equipment industry? Purpose: The purpose of this master thesis is to investigate how Scania and Volvo interpret and implement AI technologies to enhance supply chain resilience and mitigate disruptions in the construction equipment industry. Method: Qualitative Conclusion: The conclusion of the master thesis is that Scania and Volvo have successfully implemented AI technologies to enhance supply chain resilience in the construction equipment industry, despite challenges, and see AI as a critical component for future supply chain strategies.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mdh-62755 |
| Date | January 2023 |
| Creators | Safi, Aymen, Amyari Khamneh, Ramak |
| Publisher | Mälardalens universitet, Akademin för ekonomi, samhälle och teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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