Temporal integration of the spatial autoregressive model for analyzing European multimodal freight transport demand

Abstract

The industry of freight transport is recognized as one of the most important sectors for sustainable economic development, both on a regional and global scale. Although significant research has been produced for modeling demand for freight cargo, the incorporation of multimodality, connectivity, and proximity still needs to be further advanced supported by recent methodological advances. Concentrating on the close relationship of freight activity with the national economy, transport infrastructure, and the social context, a multi-dimensional approach should be considered for capturing and interpreting the dynamics of freight demand and services. Taking into account the spatial and temporal integration of regional characteristics into a coherent model may accurately reveal latent perspectives of freight demand that other approaches are not designed to capture. In the current paper, a robust model able to incorporate the multiple dimensions of freight demand at a regional scale, into one Spatio-temporal model form is developed and proposed for future spatio-temporal analyses. To achieve this, an extended form of the Spatial Autoregressive (SAR) model has been developed, estimated as the Linear Mixed Effect (LME) model, and named the Spatio-Temporal Linear Mixed Effect (STLME) model. The implementation has been applied to the European region for 5 years, providing valuable evidence on the factors that mostly affect freight demand. The results of this paper provide significant information on the spatial and temporal dynamics of the phenomenon.