Approaches to upstream agricultural supply chain and logistics challenges
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
OP Auditorium (L10), Linnanmaa Campus
Topic of the dissertation
Approaches to upstream agricultural supply chain and logistics challenges
Doctoral candidate
Master of Science Taha Karasu
Faculty and unit
University of Oulu Graduate School, Faculty of Technology, Civil Engineering
Subject of study
Infrastructure and Transport
Opponent
Professor Teuku Yuri M Zagloel, University of Indonesia
Custos
Professor Pekka Leviäkangas, University of Oulu
Challenges in getting farm products from producers to customers: Information to support improvements and decisions
Agriculture is essential for global food security, but it is under growing pressure to produce more food while also responding to climate change and sustainability requirements. The early stages of agricultural transport and logistics are especially important, yet planning in this area is often reactive and vulnerable to delays, inefficiencies, and disruptions.
This dissertation examines how planning and preparation in agricultural logistics can be improved. It focuses on the first stages of the supply chain, including the movement of agricultural products from farms, as well as the future demand for transport and agricultural machinery.
The dissertation consists of four connected studies. The first study reviewed 66 scientific studies and reports to identify and rank the main challenges in the early stages of agricultural supply chains. The second study examined how these broader challenges could be turned into practical priorities for an agricultural machinery company. The third study investigated whether information on cereal production and stocks could be used to estimate future road freight activity. The fourth study examined how agricultural tractor demand in Finland could be forecast using registration data, statistical methods, and expert interviews.
The results show that the most common challenges include overly long and complicated supply chains, high levels of waste, poor and complex road networks, and problems related to climate and weather. The case study also showed that cooperation with regulators, farmers, and other supply-chain actors is important when addressing these challenges.
The findings further suggest that annual road freight volumes and agricultural equipment demand can be estimated in advance. This information can support decisions about transport capacity, investments, and infrastructure planning. Overall, the dissertation shows that more structured use of existing information can help agricultural companies and public decision-makers prepare better for future needs and disruptions.
This dissertation examines how planning and preparation in agricultural logistics can be improved. It focuses on the first stages of the supply chain, including the movement of agricultural products from farms, as well as the future demand for transport and agricultural machinery.
The dissertation consists of four connected studies. The first study reviewed 66 scientific studies and reports to identify and rank the main challenges in the early stages of agricultural supply chains. The second study examined how these broader challenges could be turned into practical priorities for an agricultural machinery company. The third study investigated whether information on cereal production and stocks could be used to estimate future road freight activity. The fourth study examined how agricultural tractor demand in Finland could be forecast using registration data, statistical methods, and expert interviews.
The results show that the most common challenges include overly long and complicated supply chains, high levels of waste, poor and complex road networks, and problems related to climate and weather. The case study also showed that cooperation with regulators, farmers, and other supply-chain actors is important when addressing these challenges.
The findings further suggest that annual road freight volumes and agricultural equipment demand can be estimated in advance. This information can support decisions about transport capacity, investments, and infrastructure planning. Overall, the dissertation shows that more structured use of existing information can help agricultural companies and public decision-makers prepare better for future needs and disruptions.
Created 4.8.2026 | Updated 5.8.2026