Road Freight Demand Forecasting Using National Accounts’ Data—The Case of Cereals

Taha Karasu (), Pekka Leviäkangas and David John Edwards
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Taha Karasu: Department of Civil Engineering, University of Oulu, 90570 Oulu, Finland
Pekka Leviäkangas: Department of Civil Engineering, University of Oulu, 90570 Oulu, Finland
David John Edwards: School of Engineering and Built Environment, Birmingham City University, Birmingham B4 7XG, UK

Agriculture, 2024, vol. 14, issue 11, 1-19

Abstract: This paper investigates the potential of utilising historical agricultural production data for enhancing road freight transport forecasting, focusing on cereal production. This study applies a multiple linear regression analysis using national statistical accounts and secondary data. The data were sourced from Finland’s Statistics Agency and the Natural Resources Institute. The analysis identifies an observable correlation between agricultural production and road freight volumes, although this correlation is not statistically significant. The highest adjusted R² observed in the models was 0.62. The analysis reveals that previous years’ production data can help forecast future road freight volumes, with vehicle mileage estimable from recent production and stock levels. Additionally, annual percentage changes in the volume of transported cereals can be partially predicted by the changes in total available cereals and opening stocks from two years prior. This exploratory research highlights the untapped predictive potential of agricultural production variables in forecasting road freight demand, suggesting areas for further forecasting enhancement.

Keywords: supply chains; demand forecasting; road freight; agriculture; regression; cereals (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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