Harnessing generative AI to enhance mid stream supply chain operations : a cross sector study of adoption and sustainability in logistics and supply chain providers
Rafin, Md (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025121636811
https://urn.fi/URN:NBN:fi:amk-2025121636811
Tiivistelmä
The thesis examines how generative artificial intelligence (GenAI) can enhance midstream supply chain operations, including warehousing, inventory management, internal transport, and order processing. The study compares global logistics companies with logistics providers operating in Finland.
The research uses a qualitative approach based on document analysis and an expert interview. Information was collected from materials such as reports and other digital statements from global ((DHL, UPS, DB Schenker Global, and Kuehne+Nagel Global) and providers operating in Finland (Posti, PostNord, DB Schenker Finland, Kuehne+Nagel Finland, and Nurminen Logistics). Thematic analysis was applied to identify patterns such as technological adoption patterns and organisational readiness from the documentation and expert interviews.
The findings show that global companies are at an early stage of GenAI adoption. GenAI is used in tasks such as data cleansing, document processing, and content generation, but these are not yet directly integrated into midstream operations. Logistics providers operating in Finland remain at an early stage of AI adoption and other digital technology adoption due to many limitations. No direct sustainability benefits linked to GenAI in midstream supply were identified. Future research can overcome the current limitation of research and directly communicate with the company.
The research uses a qualitative approach based on document analysis and an expert interview. Information was collected from materials such as reports and other digital statements from global ((DHL, UPS, DB Schenker Global, and Kuehne+Nagel Global) and providers operating in Finland (Posti, PostNord, DB Schenker Finland, Kuehne+Nagel Finland, and Nurminen Logistics). Thematic analysis was applied to identify patterns such as technological adoption patterns and organisational readiness from the documentation and expert interviews.
The findings show that global companies are at an early stage of GenAI adoption. GenAI is used in tasks such as data cleansing, document processing, and content generation, but these are not yet directly integrated into midstream operations. Logistics providers operating in Finland remain at an early stage of AI adoption and other digital technology adoption due to many limitations. No direct sustainability benefits linked to GenAI in midstream supply were identified. Future research can overcome the current limitation of research and directly communicate with the company.