Connecting Demand Estimation and Spatial Category Models for Urban Freight: First Attempt and Research Implications

Abstract

This paper proposes a combination of models to estimate in a mesoscopic and microscopic way different patterns of urban goods demand according to the area within the city. The two proposed models are a category classification model for demand estimation and a spatial-based typology model defining different elementary zone within a city based on urban forms characteristics. Both models are applied to the same dataset for the city of Angers (France). In case of the identification of general rules, this new approach will help the transferability of goods practices in urban freight from a zone of a city to the same zone of another city.