The primary objective of this thesis is to assess the different statistical methods used forcalibrating the Samgods model, which is a transportation planning tool employed in Sweden toforecast the demand for freight transport. By focusing on the specific context of national logisticsmodels, this research aims to enhance the accuracy and reliability of the Samgods model throughproposed improvements.In addition to evaluating the calibration techniques for the Samgods model, this thesisexplores the broader application of statistical estimation methods in national logistics models.It examines their potential benefits and limitations in order to shed light on their significance.The findings of this research highlight the crucial role of statistical estimations in improvingthe accuracy of national logistics models, thus enabling better-informed decision-making intransport planning and logistics management.By estimating the cost sensitivity parameter in the Swedish national logistics model, Samgods,this thesis contributes to a deeper understanding of the role of statistical estimations in optimizingsuch models. It underscores the importance of reliable and accurate data analysis in transportationplanning and logistics management. Ultimately, the aim is to provide valuable insights into howstatistical estimations can enhance the effectiveness of national logistics models.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-98321 |
Date | January 2023 |
Creators | Åkerström, Anton, Morel, Sebastian |
Publisher | Luleå tekniska universitet, Institutionen för ekonomi, teknik, konst och samhälle |
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 |
Page generated in 0.0027 seconds