Author, Institution: Valentas Gružauskas, Kaunas University of Technology
Science area, field of science: Social Sciences, Management, S003
Scientific supervisor:
prof. dr. Edita Gimžauskienė, (Kaunas University of Technology, Social Sciences, Management, S 003), 2017-2020
prof. dr. Mantas Vilkas (Kaunas University of Technology, Social Sciences, Management, S 003), 2016-2017 m.
Dissertation Defence Board of Management Science Field:
Prof. Dr. Asta Pundzienė (Kaunas University of Technology, Social Sciences, Management, S 003), chairperson,
Assoc. Prof. Dr. Renzo Akkerman (Wageningen University, The Netherlands, Social Sciences, Management, S 003),
Assoc. Prof. Dr. Aurelija Burinskienė (Vilnius Gediminas Technical UniversitySocial Sciences, Management, S 003),
Assoc. Prof. Dr. Žaneta Piligrimienė (Kaunas University of Technology, Social Sciences, Management, S 003),
Assoc. Prof. Dr. Alina Stundžienė (Kaunas University of Technology, Social Sciences, Economics, S 004).
The doctoral dissertation is available at the library of Kaunas University of Technology (K. Donelaičio g. 20, Kaunas).
Annotation:
In the dissertation the food industry singularities are being analyzed, which consist of growing food demand and high complexity of the supply chain. The focus of the thesis is on organic food product delivery to end-consumer. During the research it was identified that the most problematic areas of the food supply chain management are related with last-mile deliveries, inaccurate demand forecasting and ineffective collaboration. To solve the problem, it is recommended to form a logistic cluster, which would guarantee information sharing between the supply chain members. The additional information can be used together with supply chain resilience approaches such as redundancy and flexibility, which would improve sustainability. Higher level of information sharing might increase the management complexity, however integration of cyber-physical systems allows to increase management efficiency. Two computer simulations based on agent-based modelling were developed in the thesis. One simulation focused on redundancy approach, which analyzed the effectiveness of collaborative demand forecasting. The second simulation focused on application of autonomous vehicles, which can adapt to the disruptions of traffic and improve delivery on time. The main result of the thesis is a management framework, which allows achieving sustainable and resilient supply chain management.
